Influence of Combined Transcranial and Peripheral Electromagnetic Stimulation on the Autonomous Nerve System on Delayed Onset Muscle Soreness in Young Athletes. A Randomized Clinical Trial.

Influence of Combined Transcranial and Peripheral Electromagnetic Stimulation on the Autonomous Nerve System on Delayed Onset Muscle Soreness in Young Athletes. 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A Randomized Clinical Trial. Hugo Keirven, Alberto Sánchez Sierra, Ángel González-de-la-Flor, and 7 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-5225529/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 10 Mar, 2025 Read the published version in Journal of Translational Medicine → Version 1 posted 5 You are reading this latest preprint version Abstract Background Delayed Onset Muscle Soreness (DOMS) has been extensively studied by scientists and sports teams over the last few decades. Eccentric exercises impact physiology and recovery, as shown in recent studies. This study investigates the effects of combined transcranial and peripheral electromagnetic stimulation on the autonomic nervous system in 48 young athletes. Participants were divided into four groups: Control (n = 12), Peripheral (n = 13), Transcranial (n = 11), and Combined (n = 12). The autonomic nervous system was assessed through Heart Rate Variability (HRV) monitoring before and after the eccentric session that induced DOMS and at 24h, 48h, and 72h post-session. Results The Combined Group showed increased activation in various HRV parameters, including LF (p < 0.001), HF (p < 0.001), and the LF/HF power ratio (p < 0.001). These results indicate that combined transcranial and peripheral electromagnetic stimulation enhances recovery in athletes after 72 hours. Conclusions Paired-associative electromagnetic stimulation positively influences the autonomic nervous system response in young athletes, promoting recovery without disrupting the typical physiological recovery process in DOMS. Delayed Onset Muscle Soreness transcranial electromagnetic stimulation peripheral electromagnetic stimulation athletes recovery heart rate variability Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 INTRODUCTION For nearly the last few decades, scientists and sports performance teams have diligently investigated the etiology and origins of Delayed Onset Muscle Soreness (DOMS). Substantial research, including notable contributions by Sonkodi in 2021 and Sonkodi et al. in 2020, has emphasized that DOMS may not only be a manifestation of muscle fatigue but could also serve as a precursor to more severe muscle injuries during athletic activities (Sonkodi, 2021 ; Sonkodi et al., 2020 ). This understanding necessitates a deeper recognition of DOMS' potential impacts on sports participation and performance. The ramifications for athletes and sports organizations are significant, as evidenced by the findings of Hayashi et al. ( 2017 ) and Hickey et al. ( 2014 ), who have documented the broad and sometimes severe consequences of these muscle conditions on the athletic community (Hayashi et al., 2017 ; Hickey et al., 2014 ). Such insights underline the importance of comprehensive studies and targeted interventions aimed at mitigating the onset and severity of DOMS to enhance athletic performance and prevent injury. Indeed, DOMS typically follows activities that involve a high degree of eccentric contractions, often occurring after periods of rest such as the preseason in various team sports (Mori et al., 2014 ). This condition is mediated by a cascade of biochemical events, including the secretion of bradykinin through perspiration and an upregulation of nerve growth factor, both of which contribute to the sensitization of nociceptors and consequently, an enhanced perception of muscle soreness (Colón et al., 2017 ; Murase et al., 2010 ). Furthermore, advancements in the understanding of DOMS propose that its underlying mechanism may be rooted in acute axonopathy, which results from the physical compression and damage of muscle fibers. This axonopathy is believed to trigger hyperalgesia, specifically at the neuromuscular spindle, a process that is characterized by two distinct phases: the initial acute muscle compression followed by excitotoxicity, which is primarily due to the release of glutamate (Kingsley & Figueroa, 2016 ; THOMAS et al., 2018 ). This conceptual framework is further reinforced by recent theories presented by Sonkodi et al. ( 2020 ), which suggest that DOMS may arise specifically due to acute axonopathy, emphasizing the significant role of peripheral nerves and the inflammation of surrounding tissues (Sonkodi et al., 2020 ). This perspective underscores a critical shift in understanding DOMS not just as a mere aftermath of physical exertion but as a complex interplay of neurological and inflammatory responses that are pivotal to developing more effective treatments and preventive measures in sports medicine. Building on the newly developed theories about the pathophysiology of DOMS, recent research has demonstrated the pivotal role of the peripheral nervous system in individuals experiencing DOMS. This has led to the exploration of novel therapeutic approaches, including the combination of transcranial and peripheral electromagnetic stimulation (Beltrá et al., 2022 ; Keriven et al., 2023 ). The innovative aspect of this treatment lies in its dual approach: targeting both central and peripheral components of the nervous system to potentially enhance recovery processes. In this line, Transcranial Electromagnetic Stimulation (TMS) has been utilized since 1985, primarily within the realm of sports medicine, to non-invasively examine cortical excitability and its implications on muscle function. Over the years, the application of TMS has expanded, showing safety and efficacy in treating neurological conditions like fibromyalgia and aiding post-stroke rehabilitation. It also plays a significant role in understanding the relationship between muscle fatigue and brain activation, thus influencing sports performance and recovery (Delaval et al., 2022 ; Lefaucheur et al., 2017 ; Moscatelli et al., 2021 ; Vernillo et al., 2021 ). On the other hand, Peripheral Electromagnetic Stimulation (PES) serves as a complementary technique, distinct from TMS due to its focus on the peripheral bodily regions. PES employs rapid pulses of high-intensity electricity combined with a magnetic field to stimulate peripheral afferents. This not only aids in the recruitment of these nerve pathways but also facilitates proprioceptive responses, which are crucial for initiating brain neuroplasticity and enhancing motor control (Barker, 1991 ; Fan & Sdrulla, 2020 ; Moscatelli et al., 2021 ; Sdrulla et al., 2015 ). Together, these techniques have significantly advanced the field of neuromodulation, offering new insights into the integration of cortical and peripheral stimuli in managing conditions like DOMS. Their combined use underscores a strategic shift towards holistic approaches in sports medicine, focusing on the interconnectivity of brain and peripheral functions to optimize athlete recovery and performance. Another critical aspect of this research is the demonstrated interrelationship between the central nervous system, specifically the motor cortex, and the modifications in Heart Rate Variability (HRV) observed following transcranial stimulation. This relationship is pivotal due to the direct connection between the cortical regions of the brain and the autonomic centers, which regulate bodily functions such as heart rate and stress responses (Cabrerizo et al., 2014 ). HRV serves as a quantifiable index of the autonomic nervous system's response to environmental stressors. It provides insights into how personal conditions, such as psychological stress, may influence the recovery processes, thereby affecting overall athletic performance and rehabilitation (Makovac et al., 2017 ). In this line, extensive research has shown that modifications in HRV can be directly linked to the application of Transcranial Magnetic Stimulation (TMS) on the primary motor cortex (M1). These changes in HRV reflect alterations in muscle activity, potentially influencing the response of the autonomic nervous system. Such findings underscore the sensitivity of HRV as a marker for neurophysiological changes and its utility in assessing the impact of neurological interventions on systemic physiological functions (Schmaußer et al., 2022 ). Thus, the primary objective of this study is to explore the potential effects of the innovative combined approach of transcranial and peripheral electromagnetic stimulation on the Autonomic Nervous System. Moreover, this investigation aims to thoroughly analyze the dual treatment's influence on the recovery process from physical sports activities, particularly assessing its efficacy in enhancing autonomic regulation and facilitating faster and more effective recovery in athletes. This holistic approach highlights the integration of neurostimulation techniques in sports medicine, aiming to optimize the recovery strategies post-exercise, which could significantly benefit athletic performance and well-being. METHODS Study Design The present study was conducted as a randomized, double-blind investigation that examined young athletes, adhering to the ethical guidelines stipulated in the "World Association Declaration of Helsinki: Ethical Principles for Medical Research Involving Human Subjects" (World Medical Association, 1991). Furthermore, compliance with the Consolidated Standards of Reporting Trials (CONSORT) guidelines was ensured throughout the study. The research was approved by the Research Ethics Committee (reference number: C.I.23/048-F), and it was also registered with the Australian New Zealand Clinical Trials Registry (ACTRN12623000677606), affirming its adherence to recognized ethical standards. Employing a prospective, randomized trial design, the study included a control group to facilitate comparative analysis. Participants were systematically allocated into one of four distinct groups: the Control group (Cont), which received no intervention; the Super Induction group (P), subjected to Peripheral Electromagnetic Stimulation (PES); the Transcranial group (T), which underwent Transcranial Electromagnetic Stimulation (TES); and the Combination of Stimulation group (Comb), which experienced a synergistic application of both TES and PES modalities. This setup was designed to rigorously evaluate the individual and combined effects of the interventions on the autonomic nervous system and recovery processes in athletes. To enhance the blinding of the study and maintain objectivity, a specific, neutral location was designated for administering the treatments. This strategic approach was instrumental in ensuring that both participants and researchers remained unaware of the group allocations, thereby minimizing bias and enhancing the validity of the findings. Researchers assigned to the treatment stations were solely involved in delivering the interventions and were explicitly instructed not to engage in discussions with other members of the research team or with participants regarding group assignments or treatment specifics. These meticulous measures were implemented to ensure that the study conformed to the highest standards of scientific rigor and ethical conduct. The aim was to collect unbiased data that could provide reliable and valuable insights into the effects of electromagnetic and electrical stimulation on young athletes. This commitment to rigorous methodology underpins the study's contribution to the field, potentially informing future therapeutic strategies and enhancing sports performance management. Sample size calculation The sample size was determined using an alpha error of 0.05, a beta error of 0.20, and a standard deviation of 2.61. Utilizing G-Power software (version 3.1), it was established that 22 participants per group were required. Accounting for an anticipated 15% dropout rate, the total sample size was set at 80 participants, divided into four groups of 20 each. Participants Students from the European University of Madrid were selectively recruited for the study, employing targeted strategies within the Faculty of Sports Sciences. Recruitment utilized multiple communication channels including flyers, posters, and strategically positioned advertisements, ensuring broad outreach within the university community. The inclusion criteria were meticulously defined to capture a specific demographic and health profile conducive to the study's objectives. Participants were required to be male, aged between 18 and 35 years, as delineated by Chen et al. (2019) (Chen et al., 2019). Furthermore, these individuals were expected to engage in regular physical activity, defined as participating in exercise at least three times a week for a minimum duration of one year, and were to have no hypersensitivity in areas designated for peripheral stimulation. The screening process also included assessments for any diagnosed chronic diseases, recent musculoskeletal injuries to the lower extremity within the past six months, and smoking habits, as noted by Dominguez-Balmaseda et al. (2020) (Dominguez-Balmaseda et al., 2020). Exclusion criteria were rigorously applied to ensure the safety and appropriateness of the study participants. Individuals with medical conditions that were incompatible with exercise, those unable to understand the objectives of the exercise sessions, or those failing to meet any of the specified inclusion criteria were excluded from participation. This thorough screening process was integral to maintaining the integrity and reliability of the study's outcomes. Randomization The randomization of participants into study groups was meticulously conducted using the randomization function of Microsoft Office Excel (Microsoft Corporation, Redmond, Washington, USA). This approach ensured that the allocation of subjects to the four predefined study groups was carried out in an unbiased and systematic manner. By employing a widely recognized tool for data manipulation and randomization, the study upheld the principles of fairness and scientific integrity essential for experimental reliability. This methodological choice facilitated the equitable distribution of participants across the Control group, Super Induction group, Transcranial group, and the Combination of Stimulation group, as previously detailed. Procedure Participants were required to attend a total of five assessment sessions as delineated in the study's methodology outlined in Figure 1. A preliminary familiarization session was held one week prior to the initial study assessment to ensure that all participants were well-acquainted with the experimental procedures and equipment. The inaugural assessment session (Day 1) was dedicated to comprehensively evaluating various physiological and biomechanical data. This included the measurement of creatine kinase (CK) levels, blood lactate concentrations, and heart rate variability with parameters such as SDNN, LF, HF, and Power. Additionally, a suite of anthropometric data was collected, facilitating a thorough understanding of the study population's baseline physiological and physical state. Subsequent sessions were meticulously scheduled at specific post-exercise intervals—1 hour, 24 hours, 48 hours, and 72 hours after the muscle-damaging exercise—to monitor the progression and recovery during these critical periods. During each session, the parameters previously mentioned were measured again to deepen the understanding of or observe any changes, thereby assessing the impact of the muscle-damaging protocol. The analysis of blood concentrations of CK and lactate was prioritized as the primary method to gauge muscle damage. Blood samples were collected and analyzed using electrophoretic techniques (Lactate Scout Pro, Musimedic S.L Donostia, Spain), providing detailed insights into the extent of muscle damage and the recovery dynamics within the participant group. To ensure the accuracy of enzyme measurements, participants were instructed to refrain from any physical activities two days prior to the study commencement. This precaution was essential to prevent the potential elevation of enzyme levels caused by recent physical exertion, which could skew the interpretation of the results, thus maintaining the integrity and accuracy of the study findings. Intervention . Eccentric Exercise Protocol The exercise session was meticulously structured into three distinct phases, each designed to induce DOMS effectively while minimizing injury risks. These phases incorporated specific strength exercises tailored to meet the study's rigorous scientific objectives. General Warm-Up The initial phase comprised a warm-up aimed at enhancing joint mobility in the lower limbs, supplemented by bodyweight strength exercises. This preparatory phase was critical for acclimatizing athletes to the physical demands of the subsequent exercises designed to induce DOMS. Intervention Exercises The second phase involved participants executing a series of three targeted exercises, with the encoder-controlled squat exercise serving as the focal point. The performance of the squat was meticulously monitored using a linear accelerometer, calibrated to assess 60% of each participant's one-repetition maximum. This specific intensity was determined based on a protocol developed by González-Badillo (2011), which considers the speed (measured in meters per second) that a subject can manage the prescribed load (González-Badillo et al., 2011). Eccentric Workout Routine The concluding phase of the session included the following three exercises: a) Squat Forward: Participants executed 10 sets of 10 repetitions at 60% of their 1-RM, as established during the pre-study assessment. b) Bulgarian Squat: This exercise required participants to perform three sets of 10 repetitions on each leg, with the option of adding an additional 5 or 10 kilograms of weight. c) Forward Beam (Split): This exercise also consisted of three sets of 10 repetitions on each leg, with participants having the option to add between 5 and 10 kilograms of weight. Each phase was strategically planned to ensure that the exercises were both challenging and safe for participants, aligning meticulously with the study's objectives to investigate the effects and mechanisms of DOMS in an athletic population. Protocol for Transcranial and Peripheral Electromagnetic Stimulation in the Study The study employed various methods to administer electromagnetic stimulation treatments, tailored to the specific group each participant was assigned to. Control (Cont) Group Participants in the Cont group interacted with the same device as those in the active treatment groups, but with a crucial modification: the machine was turned off. To sustain the placebo effect—particularly critical in the context of transcranial treatments—a recording of the machine's operation was played during the session. Additionally, for the transcranial aspect, simply wearing the device's flap, corresponding to TES, was deemed sufficient to maintain the placebo effect. Super Inductive (P) Group Participants in the P group were treated using PES according to the Long-Term Potentiation protocol. This involved five cycles of stimulation at 100 Hz for 5 seconds each, followed by a 55-second rest period. The total duration of treatment for this group was approximately 10 minutes, a protocol based on the findings by Lang et al. (2007) and Milanović et al. (2011) (Lang et al., 2007; Milanović et al., 2011). Transcranial Stimulation (T) Group In the T group, the treatment included 2000 pulses of TES administered over a minimum of 20 minutes, targeting the cortical area M1 (Dietmann et al., 2023; Todd et al., 2003). Comb Stimulation (Comb) Group Participants in the Comb group underwent a total stimulation time of about 30 minutes, as a combination of both PES and TES treatments. All groups commenced treatment one hour after the eccentric exercise session, aligning with the onset of fatigue denoted as time T2 in the study. The duration of the stimulation varied depending on the group assignment, ranging from 10 minutes for the P group to 30 minutes for those in the Comb group.A Magrex stimulator equipped with a ring-shaped coil/8-shaped coil was utilized to administer the TES and PES treatments (MR Inc., Republic of Korea, http://www.mrev.co.kr). The equipment was selected for its ability to deliver the specified electromagnetic stimulation protocols with pinpoint accuracy and efficiency ( Figure 3). Outcome Measures: Heart Rate Variability In this study, the response of the Autonomic Nervous System was meticulously analyzed through Heart Rate Variability (HRV). HRV measurements were recorded for each participant during a 10-minute period in a supine position to obtain data across different phases: baseline (T1), post-exercise (T2), and during the recovery procedure (T3 to T5), as depicted in Figure 4. To adhere to established protocols and ensure the reliability of the data, participants were instructed to abstain from consuming substances such as alcohol, caffeine, and drugs that could affect the autonomic nervous system's response during the study period (Santos et al., 2022). Measurements were conducted using the Polar H10 heart rate monitor, which is recognized for its accuracy in HRV assessments (Martínez-Pascual et al., 2022; Tornero Aguilera et al., 2021). Various parameters of HRV were extracted at each designated time point. In the time domain, the standard deviation of all normal-to-normal RR intervals (SDNN) was calculated. In the frequency domain, parameters such as the low frequency (LF) in ms², the high frequency (HF) in ms², the LF/HF ratio, and the total power were meticulously analyzed (Martínez-Pascual et al., 2022; Sánchez-Conde & Clemente-Suárez, 2021) . These metrics provided a comprehensive overview of the autonomic nervous system's dynamics throughout the study's various stages. Statistical analysis An amount of 80 volunteers consented to participate in the present work. Nevertheless, 26 participants could not to begin the study at the initial assessment time, and a total of 4 more participants did not complete all the timeline and evaluation needed (Figure 5). Therefore, 48 male athletes completed all the assessment and were comprised in the final analysis, with a standard of 21.95 ± 4.23 years, 74.58 ± 8.94 kg of weight, 179.00 ± 7.31 cm of height, and 23.27 ± 2.41 kg/m 2 for the Body Mass Index. With no significant differences detected between the study groups for all the demographics variables (p>0.005). RESULTS In an aim to confirm these highlights, a T1 measurement analysis was handling specifically. The present analysis corroborates the homogeneity of the population, as no significant differences were observed between the study groups (Table 1 ). Table 1 Analysis of the general measures in the pre-exercise (T1). Variable Cont (n = 12) P (n = 13) T (n = 11) Comb (n = 12) P-value Lactate (mmol/L) 2.34 ± 3.04 1.38 ± 0.17 2.43 ± 3.50 1.52 ± 0.24 0.560 Creatin Kinase (mmol/L) 66.58 ± 6.88 65.61 ± 6.22 67 ± 7.91 66.25 ± 8.41 0.972 SDNN (ms) 135.53 ± 2.88 135.66 ± 2.77 134.91 ± 3.01 135.93 ± 2.88 0.996 LF (Hz) 67.13 ± 1.8 62.67 ± 1.73 67.73 ± 1.88 65.1 ± 1.8 0.192 HF (Hz) 32.12 ± 2.03 37.24 ± 1.95 32.19 ± 2.12 36.43 ± 2.03 0.161 Power (n.u) 2.15 ± 0.18 1.8 ± 0.17 2.19 ± 0.19 1.95 ± 0.18 0.419 P, super inductive group; Cont, control group; T, transcranial group; Comb, combined group; SDNN, RR-interval; LF, Low Frequency; HF, High Frequency; Power, LF/HF. Enzymes monitored during the study as was the CK did showed an increase in concentrations at 1-, 24-, 48-, and 72-hours post-exercise in all groups (p < 0.001). Although, no significant differences were detected between the study groups at the pre-exercise (p = 0.972), 1-hout post-exercise, 24 hours post-exercise (p = 0.103), 48-hours post exercise (p = 0.105), and 72-hours post-exercise (p = 0.616). Similar tendance was noted for the blood lactate levels express with a significant increase at 1-hour post exercise comparing to the base line time (p < 0.001). Following the analysis, no significant differences were detected between groups at pre-exercise (p = 0.560), 1-hour post-exercise (p = 0.782), 24-hours post-exercise (p = 0.687), 48-hours post-exercise (p = 0.389), and post 72-hours post-exercise (p = 0.170) (Table 1 ). Outcome Measure A first perspective, after caring out an analysis using ANOVA statistically significant differences was observed among the study groups at 72hrs post-DOMS (T5), those results are shown in Table 2 . The insights bring by the results show significant differences between the four groups for LF, HF and Power (p < 0.05), but no for the SDNN parameter. Table 2 Differences between the study groups for the dependent variables. SDNN (ms) F p value \(\:\varvec{\eta\:}\) 2 p Cont (n = 12) 135.53 ± 2.88 110 ± 1.64 122.55 ± 1.32 121.99 ± 1.34 126.76 ± 1.09 0.957 0.42 0.01 P (n = 13) 135.66 ± 2.77 110.4 ± 1.57 122.47 ± 1.27 122.41 ± 1.28 124.43 ± 1.04 T (n = 11) 134.91 ± 3.01 110.88 ± 1.71 122.68 ± 1.38 122.97 ± 1.4 125.46 ± 1.13 Comb (n = 12) 135.93 ± 2.88 109.64 ± 1.64 123.01 ± 1.32 124.18 ± 1.34 126.4 ± 1.09 LF (Hz) Cont (n = 12) 67.13 ± 1.8 76.34 ± 1.95 70.57 ± 2.13 a,c 68.96 ± 1.9 a,c 69.55 ± 1.73 a,c 66.876 < 0.001 0.82 P (n = 13) 62.67 ± 1.73 71.09 ± 1.87 64.86 ± 2.05 65.13 ± 1.83 a,c 65.03 ± 1.66 a,c T (n = 11) 67.73 ± 1.88 74.51 ± 2.03 62 ± 2.23 56.11 ± 1.99 48.79 ± 1.81 a Comb (n = 12) 65.1 ± 1.8 73.71 ± 1.95 58.76 ± 2.13 49.24 ± 1.9 39.09 ± 1.73 HF (Hz) Cont (n = 12) 32.12 ± 2.03 24.18 ± 2.13 29.48 ± 2.15 a,c 31.04 ± 2.12 a,c 32.25 ± 1.96 a,c 48.224 < 0.001 0.767 P (n = 13) 37.24 ± 1.95 29.17 ± 2.04 35.57 ± 2.07 35.65 ± 2.03 a 34.87 ± 1.89 a,c T (n = 11) 32.19 ± 2.12 25.53 ± 2.22 38.17 ± 2.25 43.95 ± 2.21 51.14 ± 2.05 a Comb (n = 12) 36.43 ± 2.03 27.06 ± 2.13 41.5 ± 2.15 49.33 ± 2.12 60.9 ± 1.96 Power (n.u) Cont (n = 12) 2.15 ± 0.18 3.37 ± 0.36 2.61 ± 0.18 a,c 2.41 ± 0.15 a,c 2.34 ± 0.14 a,c 31.082 < 0.001 0.679 P (n = 13) 1.8 ± 0.17 2.62 ± 0.35 1.92 ± 0.17 1.9 ± 0.14 a 1.92 ± 0.13 a,c T (n = 11) 2.19 ± 0.19 3.1 ± 0.38 1.72 ± 0.19 1.31 ± 0.16 0.98 ± 0.14 Comb (n = 12) 1.95 ± 0.18 3.29 ± 0.36 1.48 ± 0.18 1.04 ± 0.15 0.65 ± 0.14 P, super inductive group; Cont, control group; T, transcranial group; Comb, combined group; SDNN, RR-interval; LF, Low Frequency; HF, High Frequency; Power, LF/HF ; 2 p, partial eta squared; a, interaction with the Comb group (p<0.001); b, interaction with the P group (p<0.001); c, interaction with the T group (p<0.001) The clinical outcome analysis reveals significant differences within the groups for two study time, as shown in Table 3 . Statistically significant differences in mean values of all outcome variables measures were found whitin a group comparing the baseline (T1) and at 24hrs post-DOMS (T3) as a mid-term treatment analysis and, comparing the baseline (T1) and at 72hrs post-DOMS (T5) as a long-term analysis, in all groups (p < 0.05). Table 3 Analysis of clinical outcome measures among the group for T3 and T5 study time. Variables SDNN (ms) Mean ± SD LF (Hz) Mean ± SD HF (Hz) Mean ± SD Power Mean ± SD T3-T1 Analysis Cont Group T1 135.53 ± 2.89 67.13 ± 1.82 32.12 ± 2.05 2.15 ± 0.18 T3 122.55 ± 1.32 70.57 ± 2.15 29.48 ± 2.17 2.61 ± 0.18 95% Confidence interval -9.57 5.12 -8.21 21.39 p-values 0.003* 0.328 1.000 0.084 P Group T1 136.24 ± 2.89 62.88 ± 1.82 37.02 ± 2.05 1.82 ± 0.18 T3 122.83 ± 1.32 64.53 ± 2.15 35.94 ± 2.17 1.89 ± 0.18 95% Confidence interval -9.84 2.62 -2.91 3.84 p-values 0.002* 1.000 1.000 1.000 T group T1 134.91 ± 3.02 67.73 ± 1.9 32.19 ± 2.14 2.19 ± 0.19 T3 122.68 ± 1.38 62 ± 2.25 38.17 ± 2.26 1.72 ± 0.19 95% Confidence interval -9.06 -8.46 18.57 -21.46 p-values 0.009* 0.010* 0.025* 0.098 Comb Group T1 135.93 ± 2.89 65.1 ± 1.82 36.43 ± 2.05 1.95 ± 0.18 T3 123.01 ± 1.32 58.76 ± 2.15 41.5 ± 2.17 1.48 ± 0.18 95% Confidence interval -9.5 -9.73 13.91 -24.1 p-values 0.003* 0.002* 0.069 0.075 T5-T1 Analysis Variables SDNN (ms) Mean ± SD LF (Hz) Mean ± SD HF (Hz) Mean ± SD Power Mean ± SD Cont Group T1 135.53 ± 2.89 67.13 ± 1.82 32.12 ± 2.05 2.15 ± 0.18 T5 126.76 ± 1.1 69.55 ± 1.74 32.25 ± 1.97 2.34 ± 0.14 95% Confidence interval -6.47 3.6 0.4 8.83 p-values 0.154 1.000 1.000 1.000 P Group T1 136.24 ± 2.89 62.88 ± 1.82 37.02 ± 2.05 1.82 ± 0.18 T5 124.36 ± 1.1 64.63 ± 1.74 35.26 ± 1.97 1.89 ± 0.14 95% Confidence interval -8.71 2.78 -4.75 3.84 p-values 0.014* 1.000 1.000 1.000 T group T1 134.91 ± 3.02 67.73 ± 1.9 32.19 ± 2.14 2.19 ± 0.19 T5 125.46 ± 1.15 48.79 ± 1.82 51.14 ± 2.06 0.98 ± 0.14 95% Confidence interval -7 -27.96 58.86 -55.25 p-values 0.126 < 0.001** < 0.001** < 0.001** Comb Group T1 135.93 ± 2.89 65.1 ± 1.82 36.43 ± 2.05 1.95 ± 0.18 T5 126.4 ± 1.1 39.09 ± 1.74 60.9 ± 1.97 0.65 ± 0.14 95% Confidence interval -7.01 -39.95 67.16 -66.67 p-values 0.188 < 0.001** < 0.001** < 0.001** P, super inductive group; Cont, control group; T, transcranial group; Comb, combined group; SDNN, RR-interval; LF, Low Frequency; HF, High Frequency; Power, LF/HF ; significant differences with p<0.05; **, Significant differences with p<0.001. Afterwards, a post-hoc analysis for both T3 (24hrs post-DOMS) and T5 (72hrs post-DOMS) was applied with the Comb group as the reference respectful the three other study groups, to find out where the differences between groups took place as giving perspective for mid-term and long-term analysis. Statistically significant differences at the T3 (24hrs post-DOMS) express as improvement changes in the outcome measures were found between the Comb group and the Cont group (p < 0.05), except for the SDNN. No other significant differences were found between the Comb group and both P group and T group, for the T3 study time analysis, as shown in Table 4 . Table 4 Post-hoc analysis of changes in clinical outcome measures between Comb & Cont, Comb & P and Comb & T for the T3 study time. Outcome Measures Post-hoc analysis Between Comb and Cont groups at 24h (T3 vs T1 across groups) Comb group Mean ± SD Cont group Mean ± SD p SDNN 123.01 ± 1.32 122.55 ± 1.32 1.000 LF 58.76 ± 2.15 70.57 ± 2.15 0.002* HF 41.5 ± 2.17 29.48 ± 2.17 0.002* Power 1.48 ± 0.18 2.61 ± 0.18 < 0.001** Outcome Measures Post-hoc analysis Between Comb and P groups at 24h (T3) Comb group Mean ± SD P Group Mean ± SD P SDNN 123.01 ± 1.32 122.83 ± 1.32 1.000 LF 58.76 ± 2.15 64.53 ± 2.15 0.393 HF 41.5 ± 2.17 35.94 ± 2.17 0.462 Power 1.48 ± 0.18 1.89 ± 0.18 0.779 Outcome Measures Post-hoc analysis Between Comb and T groups at 24h (T3) Comb group Mean ± SD T Group Mean ± SD P SDNN 123.01 ± 1.32 122.68 ± 1.38 1.000 LF 58.76 ± 2.15 62 ± 2.25 1.000 HF 41.5 ± 2.17 38.17 ± 2.26 1.000 Power 1.48 ± 0.18 1.72 ± 0.19 1.000 P, super inductive group; Cont, control group; T, transcranial group; Comb, combined group; SDNN, RR-interval; LF, Low Frequency; HF, High Frequency; Power, LF/HF ; significant differences with p<0.05; **, Significant differences with p<0.001. Finally, the same post-hoc analysis showed statistically significant differences at the T5 study time (72hrs post-DOMS) respect the outcome measures between the Comb group and the Cont group for every outcome (p < 0.05), except for the SDNN. Similar findings at the same time were shown between the Comb group and the P group (p < 0.05), except for the SDNN parameter. The last comparison between the Comb group and the T group showed also significant differences for the LF and HF parameter (p < 0.05), but no differences were found for the SDNN and Power outcome, as shown in Table 5 . Table 5. Post-hoc analysis of changes in clinical outcome measures between Comb & Cont, Comb & P and Comb & T for the T5 study time. Outcome Measures Post-hoc analysis Between Comb and Cont groups at 72h (T5 vs T1 across groups) Comb group Mean ± SD Cont group Mean ± SD P SDNN 126.4 ± 1.1 126.76 ± 1.1 1.000 LF 39.09 ± 1.74 69.55 ± 1.74 < 0.001** HF 60.9 ± 1.97 32.25 ± 1.97 < 0.001** Power 0.65 ± 0.14 2.34 ± 0.14 < 0.001** Outcome Measures Post-hoc analysis Between Comb and P groups at 72h (T5) Comb group Mean ± SD P Mean ± SD P SDNN 126.4 ± 1.1 124.36 ± 1.1 1.000 LF 39.09 ± 1.74 64.63 ± 1.74 < 0.001** HF 60.9 ± 1.97 35.26 ± 1.97 < 0.001** Power 0.65 ± 0.14 1.89 ± 0.14 < 0.001** Outcome Measures Post-hoc analysis Between Comb and T groups at 72h (T5) Comb group Mean ± SD T Mean ± SD P SDNN 126.4 ± 1.1 125.46 ± 1.15 1.000 LF 39.09 ± 1.74 48.79 ± 1.82 0.002* HF 60.9 ± 1.97 51.14 ± 2.06 0.009* Power 0.65 ± 0.14 0.98 ± 0.14 0.694 P, super inductive group; Cont, control group; T, transcranial group; Comb, combined group; SDNN, RR-interval; LF, Low Frequency; HF, High Frequency; Power, LF/HF ; significant differences with p<0.05; **, Significant differences with p<0.001. DISCUSSION In our study, we observed discernible differences among the intervention groups, reflecting diverse effects on autonomic nervous system regulation. Notably, the Super Inductive Group (P) and the Transcranial Group (T) demonstrated distinct changes in Heart Rate Variability (HRV) metrics over time, which suggested differential modulation of sympathetic and parasympathetic nervous system activities. A reduction in low-frequency (LF) components across these groups may indicate a decrease in sympathetic nervous system dominance, typically associated with stress and arousal states. Conversely, an increase in high-frequency (HF) components, especially observed in the Combined Group (Comb), highlighted a shift toward parasympathetic dominance, emphasizing enhanced vagal tone and potential improvements in recovery and stress resilience (Clemente-Suárez, 2018 ). Such a shift is crucial for athletes and individuals experiencing stress, as higher vagal tone is linked to better stress management, recovery, and overall cardiovascular health (Bustamante-Sánchez et al., 2020 ). These findings imply that specific interventions, either alone or in combination, can significantly influence the balance of the autonomic nervous system, with potential implications for enhancing human performance and well-being. The P group likely experienced changes due to the direct impact of physical stimuli on muscle and neural pathways, influencing sympathetic nervous system activity. The Super Inductive System employs high-intensity electromagnetic fields to treat conditions of the neuromusculoskeletal system, potentially affecting muscle and neural pathways (Neculăeș & Lucaci, 2017 ). In contrast, the T group, through non-invasive brain stimulation, might have affected the central nervous system's regulation of autonomic functions, altering the balance towards either increased sympathetic or parasympathetic activity, depending on the stimulation parameters (Thayer & Lane, 2000 ). The Comb group experienced the synergistic effects of both physical and neural interventions, leading to a more pronounced shift towards parasympathetic dominance. This comprehensive approach potentially maximizes benefits by targeting multiple pathways for autonomic regulation, illustrating the intricate interplay between different types of interventions and the autonomic nervous system's adaptability (Critchley et al., 2013 ). The variations in HRV responses observed in our study, as compared to prior research, underscore the complex interplay between intervention specifics and individual differences. Foundational insights provided by Thayer et al. ( 2012 ) and Laborde et al. ( 2017 ) on how lifestyle modifications can modulate autonomic functions emphasize HRV's role as a biomarker for stress and recovery (Laborde et al., 2017 ; Thayer et al., 2012 ). Our results extend this narrative, illustrating that interventions do not exert uniform effects on HRV, likely due to variances in methodological approaches, including the intensity, duration, and nature of the interventions. Additionally, the distinct physiological and psychological backgrounds of participants introduce another layer of complexity, as evidenced by Kiviniemi et al. ( 2007 ), where the impact of aerobic training on HRV varied with the fitness level of the individuals (Kiviniemi et al., 2007 ). These discrepancies highlight the need for personalized approaches in designing interventions aimed at optimizing autonomic balance and underscore the necessity for further research to unravel the mechanisms underlying these effects. Delving deeper into the influence of electromagnetic stimulation on the autonomic nervous system, it is imperative to highlight the significant parasympathetic activation observed in our results, particularly concerning the HRV parameters across different groups. The use of both Transcranial Magnetic Stimulation (TMS) and Peripheral Electromagnetic Stimulation (PES) in our Comb group not only enhanced parasympathetic activity but also suggests an optimization of recovery processes in athletes. This contrasts with studies focusing solely on TMS, where results often show increased sympathetic activity, particularly in clinical settings involving patients with depression. The parasympathetic influence, critical for recovery and stress resilience, is supported by our findings showing significant differences in HRV measures among the groups, with a notable increase in HF components (Carnevali et al., 2018 ). Such observations are crucial, as they indicate a shift towards parasympathetic dominance. This shift, associated with improved vagal tone, underscores the compounded benefits of combining TMS with PES. Moreover, the absence of negative effects on the autonomic nervous system underscores the safety and suitability of these treatments. Our treatments did not disrupt the normal physiological recovery processes associated DOMS. Furthermore, the data provided in Table 1 further substantiates these points. While the creatine kinase and lactate levels indicated increases post-exercise—a typical response indicating muscle stress and recovery—there were no significant differences between the groups at any measured time point (Callegari et al., 2017 ). This uniformity suggests that while the exercise protocol effectively induced muscle stress, the electromagnetic treatments managed to modulate recovery without exacerbating muscle damage or stress response, as evidenced by stable enzyme levels across all groups. In contrast to other studies, such as those analyzing the effects of nutritional interventions on HRV (e.g., energy drinks leading to changes primarily in high-frequency indices), our approach using TMS combined with PES showcases a broader regulatory impact on both high and low-frequency components of HRV. This suggests a more comprehensive modulation of the autonomic nervous system, potentially offering a more effective means of enhancing athletic recovery and performance. In contrast to other studies, such as those analyzing the effects of nutritional interventions on HRV, our approach using TMS combined with PES showcases a broader regulatory impact on both high and low-frequency components of HRV (Lopresti, 2020 ; “Nutrition and Athletic Performance,” 2016; Zahar et al., 2023 ). This suggests a more comprehensive modulation of the autonomic nervous system, potentially offering a more effective means of enhancing athletic recovery and performance. Furthermore, our study's group-by-time interactions, as detailed in the subsequent analysis, reveal significant differences in HRV parameters such as LF and HF, not just at a single post-exercise point but across multiple recovery phases. This progressive monitoring highlights the dynamic changes in autonomic nervous system activity and provides a more detailed understanding of how these interventions influence recovery over time. In conclusion, our research underscores the importance of considering combined electromagnetic stimulation therapies in sports medicine and rehabilitation. By demonstrating no adverse effects and highlighting significant enhancements in autonomic regulation, this study not only reaffirms the safety of these interventions but also their potential efficacy in improving physiological recovery and athletic performance. Future research should continue to explore these interactions, ideally incorporating a broader demographic and varied athletic disciplines to fully ascertain the generalizability and scope of these findings. Study Limitations and future research lines While our findings contribute valuable insights into the effects of combined electromagnetic stimulation on autonomic nervous system regulation and recovery processes, several limitations must be acknowledged. First, the generalizability of our results may be restricted. The study focused on active, young male athletes, which raises questions about the applicability of our findings to less active populations or women. Future research should, therefore, aim to explore the effects of combined treatment modalities across a more diverse demographic to enhance the universality of the findings. Furthermore, the biomarkers used in our study primarily included creatine kinase and lactate levels. While these are indicative of muscle stress and recovery, expanding future analyses to include a broader range of biomarkers could provide deeper insights into the physiological impacts of the treatments. Studies could investigate how these interventions influence other recovery-related parameters, such as inflammatory markers and additional metabolic enzymes, which may further elucidate the mechanisms driving the DOMS recovery process (Kyriakidou et al., 2021 ). Additionally, the potential interactions between electromagnetic stimulation treatments and long-term medication use or recovery processes in patients with chronic conditions, such as cancer, warrant exploration. Understanding these interactions could significantly expand the scope of practice for these treatments, potentially offering new therapeutic avenues for managing symptoms and enhancing recovery in clinical populations (He et al., 2022 ). Lastly, incorporating psychological assessments into future studies could provide a more comprehensive understanding of the recovery process. Parameters such as central fatigue and recovery sensation are critical yet often overlooked aspects of post-exercise recovery. Including psychological questionnaires and subjective measures of wellness and fatigue could reveal important insights into the mental and emotional dimensions of recovery, which are integral to holistic treatment approaches. Practical applications and keypoints Enhanced Recovery Protocols: The study demonstrates the potential of combined transcranial and peripheral electromagnetic stimulation to facilitate recovery in athletes. This can be incorporated into sports medicine practices to reduce downtime and improve recovery rates after intense physical activities. Non-Invasive Treatment Options: The safety and efficacy of the non-invasive treatment modalities presented in the study suggest that they can be used as alternatives to more invasive recovery methods. This is particularly relevant for athletes who are sensitive to traditional medical treatments or who prefer less invasive recovery techniques. Autonomic Nervous System Regulation: The findings emphasize the role of autonomic nervous system regulation in athletic performance and recovery. Training programs and rehabilitation protocols can be designed to target this system, potentially enhancing overall athletic performance and well-being. Holistic Approach to Athlete Health: The study supports a holistic approach to athlete health, where both physical and neurological aspects are considered. This could lead to more comprehensive health management strategies in sports organizations and teams. Tailored Therapeutic Strategies: Given the differential effects observed across various groups in the study, sports medicine professionals can tailor electromagnetic stimulation protocols based on individual athlete needs and responses, optimizing performance outcomes. Research and Development: The findings encourage further research and development in electromagnetic stimulation technologies. This could lead to more refined devices and treatment protocols specifically optimized for different sports and activities. Conclusion The results from this clinical trial highlight the potential and safety of combined transcranial and peripheral electromagnetic stimulation as a therapeutic modality. This innovative approach illuminates the recovery processes within the Autonomic Nervous System, facilitating a deeper and more comprehensive understanding of both the mechanisms and recovery associated with Delayed Onset Muscle Soreness (DOMS). Crucially, the findings demonstrate that the natural physiological processes of DOMS recovery were not adversely affected by the treatments administered. This observation suggests that this non-invasive approach could represent a novel strategy in the management and enhancement of athletic performance and rehabilitation. By preserving the body's inherent recovery dynamics while effectively aiding in the recovery process, combined electromagnetic stimulation may offer a valuable tool in sports medicine, potentially setting a new standard for athlete care and performance optimization. Declarations Ethics approval and consent to participate : The study was approved by the Research Ethics Committee of the Clinical Hospital San Carlos (reference number: C.I. 23/048-E). Consent for publication : We have the consent for publication. We register our study in the Australian New Zealand Clinical Trials Registry (reference number: ACTRN12623000677606). Availability of data and materials : We have the availability of the data, and the materials are available at the request of the publisher. Conflicts of interest: The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article. Funding: The authors received no financial support for the research, authorship, and/or publication of this article. Acknowledgements : We would like to thank to the students at the European University of Madrid for participating in the study and to the University itself. And MR Inc. (Republic of Korea) for provide us the devices MagRex magnetic stimulator. Author contributions : ASS and HK carried out the design and idea of the project, HK, JFTA and DDB wrote the introduction to the manuscript, AGF, MGA and MBA wrote the methodology and statistics part, DDB, MPSF and HK wrote the Discussion and conclusions part, GGPS, VJCS and AGF prepared figures 1 & 2. All authors reviewed the manuscript. Contribution to the field: This work represents an advance in finding the appropriate therapeutic strategies to improve the symptoms of DOMS and thus be able to anticipate athletes to their training without risk of injury, and with the certainty of adding stimuli to the muscles to be able to provoke physiological adaptations derived from eccentric exercise. Therefore, based on the new theory of DOMS caused by axonopathy, paired-associative electromagnetic stimulation peripheral and transcranial treatment could improve muscle pain and sports performance in athletes. 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Brain Sciences , 13 (8), 1177. https://doi.org/10.3390/brainsci13081177 Cite Share Download PDF Status: Published Journal Publication published 10 Mar, 2025 Read the published version in Journal of Translational Medicine → Version 1 posted Editorial decision: Major revision 20 Dec, 2024 Reviewers agreed at journal 04 Nov, 2024 Reviewers invited by journal 04 Nov, 2024 Editor assigned by journal 23 Oct, 2024 First submitted to journal 08 Oct, 2024 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-5225529","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":373832383,"identity":"92d74265-6ff5-4c7f-bda3-cb2ccad58c31","order_by":0,"name":"Hugo Keirven","email":"","orcid":"","institution":"European University of Madrid: Universidad Europea de Madrid SLU","correspondingAuthor":false,"prefix":"","firstName":"Hugo","middleName":"","lastName":"Keirven","suffix":""},{"id":373832384,"identity":"2e423a98-ceb9-4c7f-933a-e97685cb3e2b","order_by":1,"name":"Alberto Sánchez Sierra","email":"","orcid":"","institution":"European University of Madrid: Universidad Europea de Madrid SLU","correspondingAuthor":false,"prefix":"","firstName":"Alberto","middleName":"Sánchez","lastName":"Sierra","suffix":""},{"id":373832385,"identity":"c515dd49-5e19-4e5d-8aab-8308c2f5d839","order_by":2,"name":"Ángel González-de-la-Flor","email":"","orcid":"","institution":"Universidad Europea de Madrid Campus de Villaviciosa de Odón: Universidad Europea de Madrid SLU","correspondingAuthor":false,"prefix":"","firstName":"Ángel","middleName":"","lastName":"González-de-la-Flor","suffix":""},{"id":373832386,"identity":"200eec88-bd72-4e2f-ab7b-fb622930e012","order_by":3,"name":"María García Arrabé","email":"","orcid":"","institution":"Universidad Europea de Madrid Campus de Villaviciosa de Odón: Universidad Europea de Madrid SLU","correspondingAuthor":false,"prefix":"","firstName":"María","middleName":"García","lastName":"Arrabé","suffix":""},{"id":373832387,"identity":"3a71b3ca-82de-4978-96ea-208d34e0e43b","order_by":4,"name":"Marta de la Plaza San 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Tornero","lastName":"Aguilera","suffix":""},{"id":373832391,"identity":"9c4e70e6-cc1a-4742-945b-dd90c458ab04","order_by":8,"name":"Vicente Javier Clemente Suarez","email":"","orcid":"","institution":"Universidad Europea de Madrid Campus de Villaviciosa de Odón: Universidad Europea de Madrid SLU","correspondingAuthor":false,"prefix":"","firstName":"Vicente","middleName":"Javier Clemente","lastName":"Suarez","suffix":""},{"id":373832392,"identity":"637774fc-eb48-4924-b6d2-796760219ccd","order_by":9,"name":"Diego Domínguez Balmaseda","email":"","orcid":"","institution":"Universidad Europea de Madrid Campus de Villaviciosa de Odón: Universidad Europea de Madrid SLU","correspondingAuthor":false,"prefix":"","firstName":"Diego","middleName":"Domínguez","lastName":"Balmaseda","suffix":""}],"badges":[],"createdAt":"2024-10-08 12:59:52","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-5225529/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-5225529/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1186/s12967-025-06238-3","type":"published","date":"2025-03-10T15:57:47+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":70386632,"identity":"e6640a29-c133-4fb3-8970-f734e253a0e3","added_by":"auto","created_at":"2024-12-02 17:22:08","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":156256,"visible":true,"origin":"","legend":"\u003cp\u003eOverview of the Assessment Timeline and Intervention Protocol.\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-5225529/v1/0054c749f26890f2792a239b.png"},{"id":70386548,"identity":"bdf00193-aa66-47f1-9483-3d260e1255ad","added_by":"auto","created_at":"2024-12-02 17:21:20","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":312944,"visible":true,"origin":"","legend":"\u003cp\u003eIllustration of Participants Engaged in the Eccentric Exercise Protocol. Exercise Demonstrations Include: a) Squat Forward; b) Bulgarian Squat; c) Forward Lunge.\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-5225529/v1/4e9890d1011a6b1536eb0b00.png"},{"id":70386552,"identity":"7a4d24ae-f119-4b99-9c92-85300e2d922b","added_by":"auto","created_at":"2024-12-02 17:21:22","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":411711,"visible":true,"origin":"","legend":"\u003cp\u003eIllustration of Study Participants Undergoing Electromagnetic Stimulation: a) Transcranial and Peripheral Stimulation Devices; b) Transcranial Stimulation Setup; c) Peripheral Stimulation Setup.\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-5225529/v1/203c0f47ce27f5ba64c4f625.png"},{"id":70386631,"identity":"e7fa715c-2a7c-4bb5-ae22-d0dcc6aed4ad","added_by":"auto","created_at":"2024-12-02 17:22:07","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":213923,"visible":true,"origin":"","legend":"\u003cp\u003eParticipant in supine position with the Polar H10 sensor collocated.\u003c/p\u003e","description":"","filename":"4.png","url":"https://assets-eu.researchsquare.com/files/rs-5225529/v1/4b9623c66e6fe14e76cacf6d.png"},{"id":70386635,"identity":"9c4aa87b-2671-4986-a484-90c6092ec363","added_by":"auto","created_at":"2024-12-02 17:22:13","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":102097,"visible":true,"origin":"","legend":"\u003cp\u003eFlowchart of the study following the CONSORT regulations.\u003c/p\u003e","description":"","filename":"5.png","url":"https://assets-eu.researchsquare.com/files/rs-5225529/v1/51b019dacf3604fbdfa3bf31.png"},{"id":78688971,"identity":"cb523245-265d-4a63-8316-fb0579c90546","added_by":"auto","created_at":"2025-03-17 16:09:32","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2770417,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-5225529/v1/137a2c14-9537-4ba1-ab48-5014a13e0303.pdf"}],"financialInterests":"","formattedTitle":"Influence of Combined Transcranial and Peripheral Electromagnetic Stimulation on the Autonomous Nerve System on Delayed Onset Muscle Soreness in Young Athletes. A Randomized Clinical Trial.","fulltext":[{"header":"INTRODUCTION","content":"\u003cp\u003eFor nearly the last few decades, scientists and sports performance teams have diligently investigated the etiology and origins of Delayed Onset Muscle Soreness (DOMS). Substantial research, including notable contributions by Sonkodi in 2021 and Sonkodi et al. in 2020, has emphasized that DOMS may not only be a manifestation of muscle fatigue but could also serve as a precursor to more severe muscle injuries during athletic activities (Sonkodi, \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Sonkodi et al., \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). This understanding necessitates a deeper recognition of DOMS' potential impacts on sports participation and performance. The ramifications for athletes and sports organizations are significant, as evidenced by the findings of Hayashi et al. (\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2017\u003c/span\u003e) and Hickey et al. (\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2014\u003c/span\u003e), who have documented the broad and sometimes severe consequences of these muscle conditions on the athletic community (Hayashi et al., \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Hickey et al., \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2014\u003c/span\u003e). Such insights underline the importance of comprehensive studies and targeted interventions aimed at mitigating the onset and severity of DOMS to enhance athletic performance and prevent injury.\u003c/p\u003e \u003cp\u003eIndeed, DOMS typically follows activities that involve a high degree of eccentric contractions, often occurring after periods of rest such as the preseason in various team sports (Mori et al., \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2014\u003c/span\u003e). This condition is mediated by a cascade of biochemical events, including the secretion of bradykinin through perspiration and an upregulation of nerve growth factor, both of which contribute to the sensitization of nociceptors and consequently, an enhanced perception of muscle soreness (Col\u0026oacute;n et al., \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Murase et al., \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2010\u003c/span\u003e). Furthermore, advancements in the understanding of DOMS propose that its underlying mechanism may be rooted in acute axonopathy, which results from the physical compression and damage of muscle fibers. This axonopathy is believed to trigger hyperalgesia, specifically at the neuromuscular spindle, a process that is characterized by two distinct phases: the initial acute muscle compression followed by excitotoxicity, which is primarily due to the release of glutamate (Kingsley \u0026amp; Figueroa, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; THOMAS et al., \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e2018\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThis conceptual framework is further reinforced by recent theories presented by Sonkodi et al. (\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2020\u003c/span\u003e), which suggest that DOMS may arise specifically due to acute axonopathy, emphasizing the significant role of peripheral nerves and the inflammation of surrounding tissues (Sonkodi et al., \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). This perspective underscores a critical shift in understanding DOMS not just as a mere aftermath of physical exertion but as a complex interplay of neurological and inflammatory responses that are pivotal to developing more effective treatments and preventive measures in sports medicine.\u003c/p\u003e \u003cp\u003eBuilding on the newly developed theories about the pathophysiology of DOMS, recent research has demonstrated the pivotal role of the peripheral nervous system in individuals experiencing DOMS. This has led to the exploration of novel therapeutic approaches, including the combination of transcranial and peripheral electromagnetic stimulation (Beltr\u0026aacute; et al., \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Keriven et al., \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). The innovative aspect of this treatment lies in its dual approach: targeting both central and peripheral components of the nervous system to potentially enhance recovery processes. In this line, Transcranial Electromagnetic Stimulation (TMS) has been utilized since 1985, primarily within the realm of sports medicine, to non-invasively examine cortical excitability and its implications on muscle function. Over the years, the application of TMS has expanded, showing safety and efficacy in treating neurological conditions like fibromyalgia and aiding post-stroke rehabilitation. It also plays a significant role in understanding the relationship between muscle fatigue and brain activation, thus influencing sports performance and recovery (Delaval et al., \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Lefaucheur et al., \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Moscatelli et al., \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Vernillo et al., \u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e2021\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eOn the other hand, Peripheral Electromagnetic Stimulation (PES) serves as a complementary technique, distinct from TMS due to its focus on the peripheral bodily regions. PES employs rapid pulses of high-intensity electricity combined with a magnetic field to stimulate peripheral afferents. This not only aids in the recruitment of these nerve pathways but also facilitates proprioceptive responses, which are crucial for initiating brain neuroplasticity and enhancing motor control (Barker, \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1991\u003c/span\u003e; Fan \u0026amp; Sdrulla, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Moscatelli et al., \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Sdrulla et al., \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2015\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eTogether, these techniques have significantly advanced the field of neuromodulation, offering new insights into the integration of cortical and peripheral stimuli in managing conditions like DOMS. Their combined use underscores a strategic shift towards holistic approaches in sports medicine, focusing on the interconnectivity of brain and peripheral functions to optimize athlete recovery and performance.\u003c/p\u003e \u003cp\u003eAnother critical aspect of this research is the demonstrated interrelationship between the central nervous system, specifically the motor cortex, and the modifications in Heart Rate Variability (HRV) observed following transcranial stimulation. This relationship is pivotal due to the direct connection between the cortical regions of the brain and the autonomic centers, which regulate bodily functions such as heart rate and stress responses (Cabrerizo et al., \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2014\u003c/span\u003e). HRV serves as a quantifiable index of the autonomic nervous system's response to environmental stressors. It provides insights into how personal conditions, such as psychological stress, may influence the recovery processes, thereby affecting overall athletic performance and rehabilitation (Makovac et al., \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). In this line, extensive research has shown that modifications in HRV can be directly linked to the application of Transcranial Magnetic Stimulation (TMS) on the primary motor cortex (M1). These changes in HRV reflect alterations in muscle activity, potentially influencing the response of the autonomic nervous system. Such findings underscore the sensitivity of HRV as a marker for neurophysiological changes and its utility in assessing the impact of neurological interventions on systemic physiological functions (Schmau\u0026szlig;er et al., \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2022\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThus, the primary objective of this study is to explore the potential effects of the innovative combined approach of transcranial and peripheral electromagnetic stimulation on the Autonomic Nervous System. Moreover, this investigation aims to thoroughly analyze the dual treatment's influence on the recovery process from physical sports activities, particularly assessing its efficacy in enhancing autonomic regulation and facilitating faster and more effective recovery in athletes. This holistic approach highlights the integration of neurostimulation techniques in sports medicine, aiming to optimize the recovery strategies post-exercise, which could significantly benefit athletic performance and well-being.\u003c/p\u003e"},{"header":"METHODS","content":"\u003cp\u003e\u003cstrong\u003eStudy Design\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe present study was conducted as a randomized, double-blind investigation that examined young athletes, adhering to the ethical guidelines stipulated in the \u0026quot;World Association Declaration of Helsinki: Ethical Principles for Medical Research Involving Human Subjects\u0026quot; (World Medical Association, 1991). Furthermore, compliance with the Consolidated Standards of Reporting Trials (CONSORT) guidelines was ensured throughout the study.\u003c/p\u003e\n\u003cp\u003eThe research was approved by the Research Ethics Committee (reference number: C.I.23/048-F), and it was also registered with the Australian New Zealand Clinical Trials Registry (ACTRN12623000677606), affirming its adherence to recognized ethical standards.\u003c/p\u003e\n\u003cp\u003eEmploying a prospective, randomized trial design, the study included a control group to facilitate comparative analysis. Participants were systematically allocated into one of four distinct groups: the Control group (Cont), which received no intervention; the Super Induction group (P), subjected to Peripheral Electromagnetic Stimulation (PES); the Transcranial group (T), which underwent Transcranial Electromagnetic Stimulation (TES); and the Combination of Stimulation group (Comb), which experienced a synergistic application of both TES and PES modalities. This setup was designed to rigorously evaluate the individual and combined effects of the interventions on the autonomic nervous system and recovery processes in athletes.\u003c/p\u003e\n\u003cp\u003eTo enhance the blinding of the study and maintain objectivity, a specific, neutral location was designated for administering the treatments. This strategic approach was instrumental in ensuring that both participants and researchers remained unaware of the group allocations, thereby minimizing bias and enhancing the validity of the findings. Researchers assigned to the treatment stations were solely involved in delivering the interventions and were explicitly instructed not to engage in discussions with other members of the research team or with participants regarding group assignments or treatment specifics.\u003c/p\u003e\n\u003cp\u003eThese meticulous measures were implemented to ensure that the study conformed to the highest standards of scientific rigor and ethical conduct. The aim was to collect unbiased data that could provide reliable and valuable insights into the effects of electromagnetic and electrical stimulation on young athletes. This commitment to rigorous methodology underpins the study\u0026apos;s contribution to the field, potentially informing future therapeutic strategies and enhancing sports performance management.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSample size calculation\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe sample size was determined using an alpha error of 0.05, a beta error of 0.20, and a standard deviation of 2.61. Utilizing G-Power software (version 3.1), it was established that 22 participants per group were required. Accounting for an anticipated 15% dropout rate, the total sample size was set at 80 participants, divided into four groups of 20 each.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eParticipants\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eStudents from the European University of Madrid were selectively recruited for the study, employing targeted strategies within the Faculty of Sports Sciences. Recruitment utilized multiple communication channels including flyers, posters, and strategically positioned advertisements, ensuring broad outreach within the university community.\u003c/p\u003e\n\u003cp\u003eThe inclusion criteria were meticulously defined to capture a specific demographic and health profile conducive to the study\u0026apos;s objectives. Participants were required to be male, aged between 18 and 35 years, as delineated by Chen et al. (2019) (Chen et al., 2019). Furthermore, these individuals were expected to engage in regular physical activity, defined as participating in exercise at least three times a week for a minimum duration of one year, and were to have no hypersensitivity in areas designated for peripheral stimulation. The screening process also included assessments for any diagnosed chronic diseases, recent musculoskeletal injuries to the lower extremity within the past six months, and smoking habits, as noted by Dominguez-Balmaseda et al. (2020) (Dominguez-Balmaseda et al., 2020).\u003c/p\u003e\n\u003cp\u003eExclusion criteria were rigorously applied to ensure the safety and appropriateness of the study participants. Individuals with medical conditions that were incompatible with exercise, those unable to understand the objectives of the exercise sessions, or those failing to meet any of the specified inclusion criteria were excluded from participation. This thorough screening process was integral to maintaining the integrity and reliability of the study\u0026apos;s outcomes.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eRandomization\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe randomization of participants into study groups was meticulously conducted using the randomization function of Microsoft Office Excel (Microsoft Corporation, Redmond, Washington, USA). This approach ensured that the allocation of subjects to the four predefined study groups was carried out in an unbiased and systematic manner. By employing a widely recognized tool for data manipulation and randomization, the study upheld the principles of fairness and scientific integrity essential for experimental reliability. This methodological choice facilitated the equitable distribution of participants across the Control group, Super Induction group, Transcranial group, and the Combination of Stimulation group, as previously detailed.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eProcedure\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eParticipants were required to attend a total of five assessment sessions as delineated in the study\u0026apos;s methodology outlined in Figure 1. A preliminary familiarization session was held one week prior to the initial study assessment to ensure that all participants were well-acquainted with the experimental procedures and equipment.\u003c/p\u003e\n\u003cp\u003eThe inaugural assessment session (Day 1) was dedicated to comprehensively evaluating various physiological and biomechanical data. This included the measurement of creatine kinase (CK) levels, blood lactate concentrations, and heart rate variability with parameters such as SDNN, LF, HF, and Power. Additionally, a suite of anthropometric data was collected, facilitating a thorough understanding of the study population\u0026apos;s baseline physiological and physical state.\u003c/p\u003e\n\u003cp\u003eSubsequent sessions were meticulously scheduled at specific post-exercise intervals\u0026mdash;1 hour, 24 hours, 48 hours, and 72 hours after the muscle-damaging exercise\u0026mdash;to monitor the progression and recovery during these critical periods. During each session, the parameters previously mentioned were measured again to deepen the understanding of or observe any changes, thereby assessing the impact of the muscle-damaging protocol.\u003c/p\u003e\n\u003cp\u003eThe analysis of blood concentrations of CK and lactate was prioritized as the primary method to gauge muscle damage. Blood samples were collected and analyzed using electrophoretic techniques (Lactate Scout Pro, Musimedic S.L Donostia, Spain), providing detailed insights into the extent of muscle damage and the recovery dynamics within the participant group.\u003c/p\u003e\n\u003cp\u003eTo ensure the accuracy of enzyme measurements, participants were instructed to refrain from any physical activities two days prior to the study commencement. This precaution was essential to prevent the potential elevation of enzyme levels caused by recent physical exertion, which could skew the interpretation of the results, thus maintaining the integrity and accuracy of the study findings.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eIntervention\u003c/strong\u003e\u003cstrong\u003e. \u003cem\u003eEccentric Exercise Protocol\u0026nbsp;\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe exercise session was meticulously structured into three distinct phases, each designed to induce DOMS effectively while minimizing injury risks. These phases incorporated specific strength exercises tailored to meet the study\u0026apos;s rigorous scientific objectives.\u003c/p\u003e\n\u003cp\u003eGeneral Warm-Up\u003c/p\u003e\n\u003cp\u003eThe initial phase comprised a warm-up aimed at enhancing joint mobility in the lower limbs, supplemented by bodyweight strength exercises. This preparatory phase was critical for acclimatizing athletes to the physical demands of the subsequent exercises designed to induce DOMS.\u003c/p\u003e\n\u003cp\u003eIntervention Exercises\u003c/p\u003e\n\u003cp\u003eThe second phase involved participants executing a series of three targeted exercises, with the encoder-controlled squat exercise serving as the focal point. The performance of the squat was meticulously monitored using a linear accelerometer, calibrated to assess 60% of each participant\u0026apos;s one-repetition maximum. This specific intensity was determined based on a protocol developed by Gonz\u0026aacute;lez-Badillo (2011), which considers the speed (measured in meters per second) that a subject can manage the prescribed load (Gonz\u0026aacute;lez-Badillo et al., 2011).\u003c/p\u003e\n\u003cp\u003eEccentric Workout Routine\u003c/p\u003e\n\u003cp\u003eThe concluding phase of the session included the following three exercises:\u003c/p\u003e\n\u003cp\u003ea) Squat Forward: Participants executed 10 sets of 10 repetitions at 60% of their 1-RM, as established during the pre-study assessment.\u003c/p\u003e\n\u003cp\u003eb) Bulgarian Squat: This exercise required participants to perform three sets of 10 repetitions on each leg, with the option of adding an additional 5 or 10 kilograms of weight.\u003c/p\u003e\n\u003cp\u003ec) Forward Beam (Split): This exercise also consisted of three sets of 10 repetitions on each leg, with participants having the option to add between 5 and 10 kilograms of weight.\u003c/p\u003e\n\u003cp\u003eEach phase was strategically planned to ensure that the exercises were both challenging and safe for participants, aligning meticulously with the study\u0026apos;s objectives to investigate the effects and mechanisms of DOMS in an athletic population.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eProtocol for Transcranial and Peripheral Electromagnetic Stimulation in the Study\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe study employed various methods to administer electromagnetic stimulation treatments, tailored to the specific group each participant was assigned to.\u003c/p\u003e\n\u003cp\u003eControl (Cont) Group\u003c/p\u003e\n\u003cp\u003eParticipants in the Cont group interacted with the same device as those in the active treatment groups, but with a crucial modification: the machine was turned off. To sustain the placebo effect\u0026mdash;particularly critical in the context of transcranial treatments\u0026mdash;a recording of the machine\u0026apos;s operation was played during the session. Additionally, for the transcranial aspect, simply wearing the device\u0026apos;s flap, corresponding to TES, was deemed sufficient to maintain the placebo effect.\u003c/p\u003e\n\u003cp\u003eSuper Inductive (P) Group\u003c/p\u003e\n\u003cp\u003eParticipants in the P group were treated using PES according to the Long-Term Potentiation protocol. This involved five cycles of stimulation at 100 Hz for 5 seconds each, followed by a 55-second rest period. The total duration of treatment for this group was approximately 10 minutes, a protocol based on the findings by Lang et al.\u0026nbsp;(2007) and Milanović et al. (2011)\u0026nbsp;(Lang et al., 2007; Milanović et al., 2011).\u003c/p\u003e\n\u003cp\u003eTranscranial Stimulation (T) Group\u003c/p\u003e\n\u003cp\u003eIn the T group, the treatment included 2000 pulses of TES administered over a minimum of 20 minutes, targeting the cortical area M1\u0026nbsp;(Dietmann et al., 2023; Todd et al., 2003).\u003c/p\u003e\n\u003cp\u003eComb Stimulation (Comb) Group\u003c/p\u003e\n\u003cp\u003eParticipants in the Comb group underwent a total stimulation time of about 30 minutes, as a combination of both PES and TES treatments.\u003c/p\u003e\n\u003cp\u003eAll groups commenced treatment one hour after the eccentric exercise session, aligning with the onset of fatigue denoted as time T2 in the study. The duration of the stimulation varied depending on the group assignment, ranging from 10 minutes for the P group to 30 minutes for those in the Comb group.A Magrex stimulator equipped with a ring-shaped coil/8-shaped coil was utilized to administer the TES and PES treatments (MR Inc., Republic of Korea, http://www.mrev.co.kr). The equipment was selected for its ability to deliver the specified electromagnetic stimulation protocols with pinpoint accuracy and efficiency (\u003cstrong\u003eFigure 3).\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eOutcome Measures: Heart Rate Variability\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eIn this study, the response of the Autonomic Nervous System was meticulously analyzed through Heart Rate Variability (HRV). HRV measurements were recorded for each participant during a 10-minute period in a supine position to obtain data across different phases: baseline (T1), post-exercise (T2), and during the recovery procedure (T3 to T5), as depicted in Figure 4. To adhere to established protocols and ensure the reliability of the data, participants were instructed to abstain from consuming substances such as alcohol, caffeine, and drugs that could affect the autonomic nervous system\u0026apos;s response during the study period (Santos et al., 2022).\u003c/p\u003e\n\u003cp\u003eMeasurements were conducted using the Polar H10 heart rate monitor, which is recognized for its accuracy in HRV assessments (Mart\u0026iacute;nez-Pascual et al., 2022; Tornero Aguilera et al., 2021). Various parameters of HRV were extracted at each designated time point. In the time domain, the standard deviation of all normal-to-normal RR intervals (SDNN) was calculated. In the frequency domain, parameters such as the low frequency (LF) in ms\u0026sup2;, the high frequency (HF) in ms\u0026sup2;, the LF/HF ratio, and the total power were meticulously analyzed \u003csup\u003e(Mart\u0026iacute;nez-Pascual et al., 2022; S\u0026aacute;nchez-Conde \u0026amp; Clemente-Su\u0026aacute;rez, 2021)\u003c/sup\u003e. These metrics provided a comprehensive overview of the autonomic nervous system\u0026apos;s dynamics throughout the study\u0026apos;s various stages.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eStatistical analysis\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAn amount of 80 volunteers consented to participate in the present work. Nevertheless, 26 participants could not to begin the study at the initial assessment time, and a total of 4 more participants did not complete all the timeline and evaluation needed (Figure 5). Therefore, 48 male athletes completed all the assessment and were comprised in the final analysis, with a standard of 21.95 \u0026plusmn; 4.23 years, 74.58 \u0026plusmn; 8.94 kg of weight, 179.00 \u0026plusmn; 7.31 cm of height, and 23.27 \u0026plusmn; 2.41 kg/m\u003csup\u003e2\u003c/sup\u003e for the Body Mass Index. With no significant differences detected between the study groups for all the demographics variables (p\u0026gt;0.005). \u003c/p\u003e"},{"header":"RESULTS","content":"\u003cp\u003eIn an aim to confirm these highlights, a T1 measurement analysis was handling specifically. The present analysis corroborates the homogeneity of the population, as no significant differences were observed between the study groups (Table \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e\n\u003ctable id=\"Tab1\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eAnalysis of the general measures in the pre-exercise (T1).\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eVariable\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eCont (n\u0026thinsp;=\u0026thinsp;12)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eP (n\u0026thinsp;=\u0026thinsp;13)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eT (n\u0026thinsp;=\u0026thinsp;11)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eComb (n\u0026thinsp;=\u0026thinsp;12)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eP-value\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLactate (mmol/L)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2.34\u0026thinsp;\u0026plusmn;\u0026thinsp;3.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1.38\u0026thinsp;\u0026plusmn;\u0026thinsp;0.17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2.43\u0026thinsp;\u0026plusmn;\u0026thinsp;3.50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1.52\u0026thinsp;\u0026plusmn;\u0026thinsp;0.24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.560\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCreatin Kinase (mmol/L)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e66.58\u0026thinsp;\u0026plusmn;\u0026thinsp;6.88\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e65.61\u0026thinsp;\u0026plusmn;\u0026thinsp;6.22\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e67\u0026thinsp;\u0026plusmn;\u0026thinsp;7.91\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e66.25\u0026thinsp;\u0026plusmn;\u0026thinsp;8.41\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.972\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSDNN (ms)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e135.53\u0026thinsp;\u0026plusmn;\u0026thinsp;2.88\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e135.66\u0026thinsp;\u0026plusmn;\u0026thinsp;2.77\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e134.91\u0026thinsp;\u0026plusmn;\u0026thinsp;3.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e135.93\u0026thinsp;\u0026plusmn;\u0026thinsp;2.88\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.996\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLF (Hz)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e67.13\u0026thinsp;\u0026plusmn;\u0026thinsp;1.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e62.67\u0026thinsp;\u0026plusmn;\u0026thinsp;1.73\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e67.73\u0026thinsp;\u0026plusmn;\u0026thinsp;1.88\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e65.1\u0026thinsp;\u0026plusmn;\u0026thinsp;1.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.192\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHF (Hz)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e32.12\u0026thinsp;\u0026plusmn;\u0026thinsp;2.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e37.24\u0026thinsp;\u0026plusmn;\u0026thinsp;1.95\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e32.19\u0026thinsp;\u0026plusmn;\u0026thinsp;2.12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e36.43\u0026thinsp;\u0026plusmn;\u0026thinsp;2.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.161\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePower (n.u)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2.15\u0026thinsp;\u0026plusmn;\u0026thinsp;0.18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1.8\u0026thinsp;\u0026plusmn;\u0026thinsp;0.17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2.19\u0026thinsp;\u0026plusmn;\u0026thinsp;0.19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1.95\u0026thinsp;\u0026plusmn;\u0026thinsp;0.18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.419\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003c/p\u003e\n\u003cp\u003eP, super inductive group; Cont, control group; T, transcranial group; Comb, combined group; SDNN, RR-interval; LF, Low Frequency; HF, High Frequency; Power, LF/HF.\u003c/p\u003e\n\u003cp\u003eEnzymes monitored during the study as was the CK did showed an increase in concentrations at 1-, 24-, 48-, and 72-hours post-exercise in all groups (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Although, no significant differences were detected between the study groups at the pre-exercise (p\u0026thinsp;=\u0026thinsp;0.972), 1-hout post-exercise, 24 hours post-exercise (p\u0026thinsp;=\u0026thinsp;0.103), 48-hours post exercise (p\u0026thinsp;=\u0026thinsp;0.105), and 72-hours post-exercise (p\u0026thinsp;=\u0026thinsp;0.616). Similar tendance was noted for the blood lactate levels express with a significant increase at 1-hour post exercise comparing to the base line time (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Following the analysis, no significant differences were detected between groups at pre-exercise (p\u0026thinsp;=\u0026thinsp;0.560), 1-hour post-exercise (p\u0026thinsp;=\u0026thinsp;0.782), 24-hours post-exercise (p\u0026thinsp;=\u0026thinsp;0.687), 48-hours post-exercise (p\u0026thinsp;=\u0026thinsp;0.389), and post 72-hours post-exercise (p\u0026thinsp;=\u0026thinsp;0.170) (Table \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e\n\u003cdiv id=\"Sec12\" class=\"Section2\"\u003e\n \u003ch2\u003eOutcome Measure\u003c/h2\u003e\n \u003cp\u003eA first perspective, after caring out an analysis using ANOVA statistically significant differences was observed among the study groups at 72hrs post-DOMS (T5), those results are shown in Table \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e. The insights bring by the results show significant differences between the four groups for LF, HF and Power (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05), but no for the SDNN parameter.\u003c/p\u003e\n \u003ctable id=\"Tab2\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eDifferences between the study groups for the dependent variables.\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003cth align=\"left\" colspan=\"8\"\u003e\n \u003cp\u003eSDNN (ms) F p value \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\varvec{\\eta\\:}\\)\u003c/span\u003e\u003c/span\u003e\u003csup\u003e2\u003c/sup\u003ep\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eCont (n\u0026thinsp;=\u0026thinsp;12)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e135.53\u0026thinsp;\u0026plusmn;\u0026thinsp;2.88\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e110\u0026thinsp;\u0026plusmn;\u0026thinsp;1.64\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e122.55\u0026thinsp;\u0026plusmn;\u0026thinsp;1.32\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e121.99\u0026thinsp;\u0026plusmn;\u0026thinsp;1.34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e126.76\u0026thinsp;\u0026plusmn;\u0026thinsp;1.09\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"4\"\u003e\n \u003cp\u003e0.957\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"4\"\u003e\n \u003cp\u003e0.42\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"4\"\u003e\n \u003cp\u003e0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eP (n\u0026thinsp;=\u0026thinsp;13)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e135.66\u0026thinsp;\u0026plusmn;\u0026thinsp;2.77\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e110.4\u0026thinsp;\u0026plusmn;\u0026thinsp;1.57\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e122.47\u0026thinsp;\u0026plusmn;\u0026thinsp;1.27\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e122.41\u0026thinsp;\u0026plusmn;\u0026thinsp;1.28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e124.43\u0026thinsp;\u0026plusmn;\u0026thinsp;1.04\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eT (n\u0026thinsp;=\u0026thinsp;11)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e134.91\u0026thinsp;\u0026plusmn;\u0026thinsp;3.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e110.88\u0026thinsp;\u0026plusmn;\u0026thinsp;1.71\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e122.68\u0026thinsp;\u0026plusmn;\u0026thinsp;1.38\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e122.97\u0026thinsp;\u0026plusmn;\u0026thinsp;1.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e125.46\u0026thinsp;\u0026plusmn;\u0026thinsp;1.13\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eComb (n\u0026thinsp;=\u0026thinsp;12)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e135.93\u0026thinsp;\u0026plusmn;\u0026thinsp;2.88\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e109.64\u0026thinsp;\u0026plusmn;\u0026thinsp;1.64\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e123.01\u0026thinsp;\u0026plusmn;\u0026thinsp;1.32\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e124.18\u0026thinsp;\u0026plusmn;\u0026thinsp;1.34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e126.4\u0026thinsp;\u0026plusmn;\u0026thinsp;1.09\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"8\"\u003e\n \u003cp\u003eLF (Hz)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eCont (n\u0026thinsp;=\u0026thinsp;12)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e67.13\u0026thinsp;\u0026plusmn;\u0026thinsp;1.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e76.34\u0026thinsp;\u0026plusmn;\u0026thinsp;1.95\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e70.57\u0026thinsp;\u0026plusmn;\u0026thinsp;2.13\u003csup\u003ea,c\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e68.96\u0026thinsp;\u0026plusmn;\u0026thinsp;1.9\u003csup\u003ea,c\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e69.55\u0026thinsp;\u0026plusmn;\u0026thinsp;1.73\u003csup\u003ea,c\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"4\"\u003e\n \u003cp\u003e66.876\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"4\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"4\"\u003e\n \u003cp\u003e0.82\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eP (n\u0026thinsp;=\u0026thinsp;13)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e62.67\u0026thinsp;\u0026plusmn;\u0026thinsp;1.73\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e71.09\u0026thinsp;\u0026plusmn;\u0026thinsp;1.87\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e64.86\u0026thinsp;\u0026plusmn;\u0026thinsp;2.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e65.13\u0026thinsp;\u0026plusmn;\u0026thinsp;1.83\u003csup\u003ea,c\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e65.03\u0026thinsp;\u0026plusmn;\u0026thinsp;1.66\u003csup\u003ea,c\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eT (n\u0026thinsp;=\u0026thinsp;11)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e67.73\u0026thinsp;\u0026plusmn;\u0026thinsp;1.88\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e74.51\u0026thinsp;\u0026plusmn;\u0026thinsp;2.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e62\u0026thinsp;\u0026plusmn;\u0026thinsp;2.23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e56.11\u0026thinsp;\u0026plusmn;\u0026thinsp;1.99\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e48.79\u0026thinsp;\u0026plusmn;\u0026thinsp;1.81\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eComb (n\u0026thinsp;=\u0026thinsp;12)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e65.1\u0026thinsp;\u0026plusmn;\u0026thinsp;1.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e73.71\u0026thinsp;\u0026plusmn;\u0026thinsp;1.95\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e58.76\u0026thinsp;\u0026plusmn;\u0026thinsp;2.13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e49.24\u0026thinsp;\u0026plusmn;\u0026thinsp;1.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e39.09\u0026thinsp;\u0026plusmn;\u0026thinsp;1.73\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"8\"\u003e\n \u003cp\u003eHF (Hz)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eCont (n\u0026thinsp;=\u0026thinsp;12)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e32.12\u0026thinsp;\u0026plusmn;\u0026thinsp;2.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e24.18\u0026thinsp;\u0026plusmn;\u0026thinsp;2.13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e29.48\u0026thinsp;\u0026plusmn;\u0026thinsp;2.15\u003csup\u003ea,c\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e31.04\u0026thinsp;\u0026plusmn;\u0026thinsp;2.12\u003csup\u003ea,c\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e32.25\u0026thinsp;\u0026plusmn;\u0026thinsp;1.96\u003csup\u003ea,c\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"4\"\u003e\n \u003cp\u003e48.224\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"4\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"4\"\u003e\n \u003cp\u003e0.767\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eP (n\u0026thinsp;=\u0026thinsp;13)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e37.24\u0026thinsp;\u0026plusmn;\u0026thinsp;1.95\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e29.17\u0026thinsp;\u0026plusmn;\u0026thinsp;2.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e35.57\u0026thinsp;\u0026plusmn;\u0026thinsp;2.07\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e35.65\u0026thinsp;\u0026plusmn;\u0026thinsp;2.03\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e34.87\u0026thinsp;\u0026plusmn;\u0026thinsp;1.89\u003csup\u003ea,c\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eT (n\u0026thinsp;=\u0026thinsp;11)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e32.19\u0026thinsp;\u0026plusmn;\u0026thinsp;2.12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e25.53\u0026thinsp;\u0026plusmn;\u0026thinsp;2.22\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e38.17\u0026thinsp;\u0026plusmn;\u0026thinsp;2.25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e43.95\u0026thinsp;\u0026plusmn;\u0026thinsp;2.21\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e51.14\u0026thinsp;\u0026plusmn;\u0026thinsp;2.05\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eComb (n\u0026thinsp;=\u0026thinsp;12)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e36.43\u0026thinsp;\u0026plusmn;\u0026thinsp;2.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e27.06\u0026thinsp;\u0026plusmn;\u0026thinsp;2.13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e41.5\u0026thinsp;\u0026plusmn;\u0026thinsp;2.15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e49.33\u0026thinsp;\u0026plusmn;\u0026thinsp;2.12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e60.9\u0026thinsp;\u0026plusmn;\u0026thinsp;1.96\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"8\"\u003e\n \u003cp\u003ePower (n.u)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eCont (n\u0026thinsp;=\u0026thinsp;12)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.15\u0026thinsp;\u0026plusmn;\u0026thinsp;0.18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3.37\u0026thinsp;\u0026plusmn;\u0026thinsp;0.36\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.61\u0026thinsp;\u0026plusmn;\u0026thinsp;0.18\u003csup\u003ea,c\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.41\u0026thinsp;\u0026plusmn;\u0026thinsp;0.15\u003csup\u003ea,c\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.34\u0026thinsp;\u0026plusmn;\u0026thinsp;0.14\u003csup\u003ea,c\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"4\"\u003e\n \u003cp\u003e31.082\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"4\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"4\"\u003e\n \u003cp\u003e0.679\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eP (n\u0026thinsp;=\u0026thinsp;13)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.8\u0026thinsp;\u0026plusmn;\u0026thinsp;0.17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.62\u0026thinsp;\u0026plusmn;\u0026thinsp;0.35\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.92\u0026thinsp;\u0026plusmn;\u0026thinsp;0.17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.9\u0026thinsp;\u0026plusmn;\u0026thinsp;0.14\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.92\u0026thinsp;\u0026plusmn;\u0026thinsp;0.13\u003csup\u003ea,c\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eT (n\u0026thinsp;=\u0026thinsp;11)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.19\u0026thinsp;\u0026plusmn;\u0026thinsp;0.19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3.1\u0026thinsp;\u0026plusmn;\u0026thinsp;0.38\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.72\u0026thinsp;\u0026plusmn;\u0026thinsp;0.19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.31\u0026thinsp;\u0026plusmn;\u0026thinsp;0.16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.98\u0026thinsp;\u0026plusmn;\u0026thinsp;0.14\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eComb (n\u0026thinsp;=\u0026thinsp;12)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.95\u0026thinsp;\u0026plusmn;\u0026thinsp;0.18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3.29\u0026thinsp;\u0026plusmn;\u0026thinsp;0.36\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.48\u0026thinsp;\u0026plusmn;\u0026thinsp;0.18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.04\u0026thinsp;\u0026plusmn;\u0026thinsp;0.15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.65\u0026thinsp;\u0026plusmn;\u0026thinsp;0.14\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003cp\u003e\u003c/p\u003e\n \u003cp\u003eP, super inductive group; Cont, control group; T, transcranial group; Comb, combined group; SDNN, RR-interval; LF, Low Frequency; HF, High Frequency; Power, LF/HF ; \u003csup\u003e2\u003c/sup\u003ep, partial eta squared; a, interaction with the Comb group (p\u0026lt;0.001); b, interaction with the P group (p\u0026lt;0.001); c, interaction with the T group (p\u0026lt;0.001)\u003c/p\u003e\n \u003cp\u003eThe clinical outcome analysis reveals significant differences within the groups for two study time, as shown in Table \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e. Statistically significant differences in mean values of all outcome variables measures were found whitin a group comparing the baseline (T1) and at 24hrs post-DOMS (T3) as a mid-term treatment analysis and, comparing the baseline (T1) and at 72hrs post-DOMS (T5) as a long-term analysis, in all groups (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05).\u003c/p\u003e\n \u003ctable id=\"Tab3\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eAnalysis of clinical outcome measures among the group for T3 and T5 study time.\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eVariables\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eSDNN (ms)\u003c/p\u003e\n \u003cp\u003eMean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003eLF (Hz)\u003c/p\u003e\n \u003cp\u003eMean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003eHF (Hz)\u003c/p\u003e\n \u003cp\u003eMean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003ePower\u003c/p\u003e\n \u003cp\u003eMean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"7\"\u003e\n \u003cp\u003e\u003cstrong\u003eT3-T1 Analysis\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCont Group\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eT1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e135.53\u0026thinsp;\u0026plusmn;\u0026thinsp;2.89\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e67.13\u0026thinsp;\u0026plusmn;\u0026thinsp;1.82\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e32.12\u0026thinsp;\u0026plusmn;\u0026thinsp;2.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e2.15\u0026thinsp;\u0026plusmn;\u0026thinsp;0.18\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eT3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e122.55\u0026thinsp;\u0026plusmn;\u0026thinsp;1.32\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e70.57\u0026thinsp;\u0026plusmn;\u0026thinsp;2.15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e29.48\u0026thinsp;\u0026plusmn;\u0026thinsp;2.17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e2.61\u0026thinsp;\u0026plusmn;\u0026thinsp;0.18\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e95% Confidence interval\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-9.57\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e5.12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e-8.21\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e21.39\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ep-values\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.003*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e0.328\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e1.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e0.084\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eP Group\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eT1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e136.24\u0026thinsp;\u0026plusmn;\u0026thinsp;2.89\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e62.88\u0026thinsp;\u0026plusmn;\u0026thinsp;1.82\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e37.02\u0026thinsp;\u0026plusmn;\u0026thinsp;2.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e1.82\u0026thinsp;\u0026plusmn;\u0026thinsp;0.18\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eT3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e122.83\u0026thinsp;\u0026plusmn;\u0026thinsp;1.32\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e64.53\u0026thinsp;\u0026plusmn;\u0026thinsp;2.15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e35.94\u0026thinsp;\u0026plusmn;\u0026thinsp;2.17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e1.89\u0026thinsp;\u0026plusmn;\u0026thinsp;0.18\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e95% Confidence interval\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-9.84\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e2.62\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e-2.91\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e3.84\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ep-values\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.002*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e1.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e1.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e1.000\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eT group\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eT1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e134.91\u0026thinsp;\u0026plusmn;\u0026thinsp;3.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e67.73\u0026thinsp;\u0026plusmn;\u0026thinsp;1.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e32.19\u0026thinsp;\u0026plusmn;\u0026thinsp;2.14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e2.19\u0026thinsp;\u0026plusmn;\u0026thinsp;0.19\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eT3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e122.68\u0026thinsp;\u0026plusmn;\u0026thinsp;1.38\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e62\u0026thinsp;\u0026plusmn;\u0026thinsp;2.25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e38.17\u0026thinsp;\u0026plusmn;\u0026thinsp;2.26\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e1.72\u0026thinsp;\u0026plusmn;\u0026thinsp;0.19\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e95% Confidence interval\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-9.06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e-8.46\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e18.57\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e-21.46\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ep-values\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.009*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e0.010*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e0.025*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e0.098\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eComb Group\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eT1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e135.93\u0026thinsp;\u0026plusmn;\u0026thinsp;2.89\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e65.1\u0026thinsp;\u0026plusmn;\u0026thinsp;1.82\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e36.43\u0026thinsp;\u0026plusmn;\u0026thinsp;2.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e1.95\u0026thinsp;\u0026plusmn;\u0026thinsp;0.18\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eT3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e123.01\u0026thinsp;\u0026plusmn;\u0026thinsp;1.32\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e58.76\u0026thinsp;\u0026plusmn;\u0026thinsp;2.15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e41.5\u0026thinsp;\u0026plusmn;\u0026thinsp;2.17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e1.48\u0026thinsp;\u0026plusmn;\u0026thinsp;0.18\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e95% Confidence interval\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-9.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e-9.73\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e13.91\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e-24.1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ep-values\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.003*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e0.002*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e0.069\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e0.075\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"7\"\u003e\n \u003cp\u003e\u003cstrong\u003eT5-T1 Analysis\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eVariables\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003eSDNN (ms)\u003c/p\u003e\n \u003cp\u003eMean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003eLF (Hz)\u003c/p\u003e\n \u003cp\u003eMean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003eHF (Hz)\u003c/p\u003e\n \u003cp\u003eMean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePower\u003c/p\u003e\n \u003cp\u003eMean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCont Group\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eT1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e135.53\u0026thinsp;\u0026plusmn;\u0026thinsp;2.89\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e67.13\u0026thinsp;\u0026plusmn;\u0026thinsp;1.82\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e32.12\u0026thinsp;\u0026plusmn;\u0026thinsp;2.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.15\u0026thinsp;\u0026plusmn;\u0026thinsp;0.18\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eT5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e126.76\u0026thinsp;\u0026plusmn;\u0026thinsp;1.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e69.55\u0026thinsp;\u0026plusmn;\u0026thinsp;1.74\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e32.25\u0026thinsp;\u0026plusmn;\u0026thinsp;1.97\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.34\u0026thinsp;\u0026plusmn;\u0026thinsp;0.14\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e95% Confidence interval\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e-6.47\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e3.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e0.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e8.83\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ep-values\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e0.154\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e1.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e1.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.000\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eP Group\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eT1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e136.24\u0026thinsp;\u0026plusmn;\u0026thinsp;2.89\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e62.88\u0026thinsp;\u0026plusmn;\u0026thinsp;1.82\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e37.02\u0026thinsp;\u0026plusmn;\u0026thinsp;2.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.82\u0026thinsp;\u0026plusmn;\u0026thinsp;0.18\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eT5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e124.36\u0026thinsp;\u0026plusmn;\u0026thinsp;1.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e64.63\u0026thinsp;\u0026plusmn;\u0026thinsp;1.74\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e35.26\u0026thinsp;\u0026plusmn;\u0026thinsp;1.97\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.89\u0026thinsp;\u0026plusmn;\u0026thinsp;0.14\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e95% Confidence interval\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e-8.71\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e2.78\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e-4.75\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3.84\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ep-values\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e0.014*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e1.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e1.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.000\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eT group\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eT1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e134.91\u0026thinsp;\u0026plusmn;\u0026thinsp;3.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e67.73\u0026thinsp;\u0026plusmn;\u0026thinsp;1.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e32.19\u0026thinsp;\u0026plusmn;\u0026thinsp;2.14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.19\u0026thinsp;\u0026plusmn;\u0026thinsp;0.19\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eT5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e125.46\u0026thinsp;\u0026plusmn;\u0026thinsp;1.15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e48.79\u0026thinsp;\u0026plusmn;\u0026thinsp;1.82\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e51.14\u0026thinsp;\u0026plusmn;\u0026thinsp;2.06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.98\u0026thinsp;\u0026plusmn;\u0026thinsp;0.14\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e95% Confidence interval\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e-7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e-27.96\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e58.86\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-55.25\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ep-values\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e0.126\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.001**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.001**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.001**\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eComb Group\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eT1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e135.93\u0026thinsp;\u0026plusmn;\u0026thinsp;2.89\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e65.1\u0026thinsp;\u0026plusmn;\u0026thinsp;1.82\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e36.43\u0026thinsp;\u0026plusmn;\u0026thinsp;2.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.95\u0026thinsp;\u0026plusmn;\u0026thinsp;0.18\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eT5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e126.4\u0026thinsp;\u0026plusmn;\u0026thinsp;1.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e39.09\u0026thinsp;\u0026plusmn;\u0026thinsp;1.74\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e60.9\u0026thinsp;\u0026plusmn;\u0026thinsp;1.97\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.65\u0026thinsp;\u0026plusmn;\u0026thinsp;0.14\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e95% Confidence interval\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e-7.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e-39.95\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e67.16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-66.67\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ep-values\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e0.188\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.001**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.001**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.001**\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003cp\u003e\u003c/p\u003e\n \u003cp\u003eP, super inductive group; Cont, control group; T, transcranial group; Comb, combined group; SDNN, RR-interval; LF, Low Frequency; HF, High Frequency; Power, LF/HF ; significant differences with p\u0026lt;0.05; **, Significant differences with p\u0026lt;0.001.\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eAfterwards, a post-hoc analysis for both T3 (24hrs post-DOMS) and T5 (72hrs post-DOMS) was applied with the Comb group as the reference respectful the three other study groups, to find out where the differences between groups took place as giving perspective for mid-term and long-term analysis. Statistically significant differences at the T3 (24hrs post-DOMS) express as improvement changes in the outcome measures were found between the Comb group and the Cont group (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05), except for the SDNN. No other significant differences were found between the Comb group and both P group and T group, for the T3 study time analysis, as shown in Table \u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003e.\u003c/p\u003e\n \u003ctable id=\"Tab4\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003ePost-hoc analysis of changes in clinical outcome measures between Comb \u0026amp; Cont, Comb \u0026amp; P and Comb \u0026amp; T for the T3 study time.\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eOutcome Measures\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colspan=\"3\"\u003e\n \u003cp\u003ePost-hoc analysis Between Comb and Cont groups at 24h (T3 vs T1 across groups)\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eComb group\u003c/p\u003e\n \u003cp\u003eMean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCont group\u003c/p\u003e\n \u003cp\u003eMean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSDNN\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e123.01\u0026thinsp;\u0026plusmn;\u0026thinsp;1.32\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e122.55\u0026thinsp;\u0026plusmn;\u0026thinsp;1.32\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.000\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLF\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e58.76\u0026thinsp;\u0026plusmn;\u0026thinsp;2.15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e70.57\u0026thinsp;\u0026plusmn;\u0026thinsp;2.15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.002*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHF\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e41.5\u0026thinsp;\u0026plusmn;\u0026thinsp;2.17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e29.48\u0026thinsp;\u0026plusmn;\u0026thinsp;2.17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.002*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePower\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.48\u0026thinsp;\u0026plusmn;\u0026thinsp;0.18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.61\u0026thinsp;\u0026plusmn;\u0026thinsp;0.18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.001**\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eOutcome Measures\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"3\"\u003e\n \u003cp\u003ePost-hoc analysis Between Comb and P groups at 24h (T3)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eComb group\u003c/p\u003e\n \u003cp\u003eMean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eP Group\u003c/p\u003e\n \u003cp\u003eMean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSDNN\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e123.01\u0026thinsp;\u0026plusmn;\u0026thinsp;1.32\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e122.83\u0026thinsp;\u0026plusmn;\u0026thinsp;1.32\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.000\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLF\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e58.76\u0026thinsp;\u0026plusmn;\u0026thinsp;2.15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e64.53\u0026thinsp;\u0026plusmn;\u0026thinsp;2.15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.393\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHF\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e41.5\u0026thinsp;\u0026plusmn;\u0026thinsp;2.17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e35.94\u0026thinsp;\u0026plusmn;\u0026thinsp;2.17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.462\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePower\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.48\u0026thinsp;\u0026plusmn;\u0026thinsp;0.18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.89\u0026thinsp;\u0026plusmn;\u0026thinsp;0.18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.779\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eOutcome Measures\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"3\"\u003e\n \u003cp\u003ePost-hoc analysis Between Comb and T groups at 24h (T3)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eComb group\u003c/p\u003e\n \u003cp\u003eMean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eT Group\u003c/p\u003e\n \u003cp\u003eMean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSDNN\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e123.01\u0026thinsp;\u0026plusmn;\u0026thinsp;1.32\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e122.68\u0026thinsp;\u0026plusmn;\u0026thinsp;1.38\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.000\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLF\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e58.76\u0026thinsp;\u0026plusmn;\u0026thinsp;2.15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e62\u0026thinsp;\u0026plusmn;\u0026thinsp;2.25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.000\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHF\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e41.5\u0026thinsp;\u0026plusmn;\u0026thinsp;2.17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e38.17\u0026thinsp;\u0026plusmn;\u0026thinsp;2.26\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.000\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePower\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.48\u0026thinsp;\u0026plusmn;\u0026thinsp;0.18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.72\u0026thinsp;\u0026plusmn;\u0026thinsp;0.19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.000\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003cp\u003e\u003c/p\u003e\n \u003cp\u003eP, super inductive group; Cont, control group; T, transcranial group; Comb, combined group; SDNN, RR-interval; LF, Low Frequency; HF, High Frequency; Power, LF/HF ; significant differences with p\u0026lt;0.05; **, Significant differences with p\u0026lt;0.001.\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eFinally, the same post-hoc analysis showed statistically significant differences at the T5 study time (72hrs post-DOMS) respect the outcome measures between the Comb group and the Cont group for every outcome (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05), except for the SDNN. Similar findings at the same time were shown between the Comb group and the P group (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05), except for the SDNN parameter. The last comparison between the Comb group and the T group showed also significant differences for the LF and HF parameter (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05), but no differences were found for the SDNN and Power outcome, as shown in Table \u003cspan class=\"InternalRef\"\u003e5\u003c/span\u003e.\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eTable 5.\u003c/strong\u003e Post-hoc analysis of changes in clinical outcome measures between Comb \u0026amp; Cont, Comb \u0026amp; P and Comb \u0026amp; T for the T5 study time.\u003c/p\u003e\n \u003ctable id=\"Taba\" border=\"1\"\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eOutcome Measures\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colspan=\"3\"\u003e\n \u003cp\u003ePost-hoc analysis Between Comb and Cont groups at 72h (T5 vs T1 across groups)\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eComb group\u003c/p\u003e\n \u003cp\u003eMean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCont group\u003c/p\u003e\n \u003cp\u003eMean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSDNN\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e126.4\u0026thinsp;\u0026plusmn;\u0026thinsp;1.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e126.76\u0026thinsp;\u0026plusmn;\u0026thinsp;1.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.000\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLF\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e39.09\u0026thinsp;\u0026plusmn;\u0026thinsp;1.74\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e69.55\u0026thinsp;\u0026plusmn;\u0026thinsp;1.74\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.001**\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHF\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e60.9\u0026thinsp;\u0026plusmn;\u0026thinsp;1.97\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e32.25\u0026thinsp;\u0026plusmn;\u0026thinsp;1.97\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.001**\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePower\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.65\u0026thinsp;\u0026plusmn;\u0026thinsp;0.14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.34\u0026thinsp;\u0026plusmn;\u0026thinsp;0.14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.001**\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eOutcome Measures\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"3\"\u003e\n \u003cp\u003ePost-hoc analysis Between Comb and P groups at 72h (T5)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eComb group\u003c/p\u003e\n \u003cp\u003eMean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eP\u003c/p\u003e\n \u003cp\u003eMean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSDNN\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e126.4\u0026thinsp;\u0026plusmn;\u0026thinsp;1.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e124.36\u0026thinsp;\u0026plusmn;\u0026thinsp;1.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.000\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLF\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e39.09\u0026thinsp;\u0026plusmn;\u0026thinsp;1.74\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e64.63\u0026thinsp;\u0026plusmn;\u0026thinsp;1.74\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.001**\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHF\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e60.9\u0026thinsp;\u0026plusmn;\u0026thinsp;1.97\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e35.26\u0026thinsp;\u0026plusmn;\u0026thinsp;1.97\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.001**\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePower\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.65\u0026thinsp;\u0026plusmn;\u0026thinsp;0.14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.89\u0026thinsp;\u0026plusmn;\u0026thinsp;0.14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.001**\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eOutcome Measures\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"3\"\u003e\n \u003cp\u003ePost-hoc analysis Between Comb and T groups at 72h (T5)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eComb group\u003c/p\u003e\n \u003cp\u003eMean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eT\u003c/p\u003e\n \u003cp\u003eMean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSDNN\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e126.4\u0026thinsp;\u0026plusmn;\u0026thinsp;1.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e125.46\u0026thinsp;\u0026plusmn;\u0026thinsp;1.15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.000\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLF\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e39.09\u0026thinsp;\u0026plusmn;\u0026thinsp;1.74\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e48.79\u0026thinsp;\u0026plusmn;\u0026thinsp;1.82\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.002*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHF\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e60.9\u0026thinsp;\u0026plusmn;\u0026thinsp;1.97\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e51.14\u0026thinsp;\u0026plusmn;\u0026thinsp;2.06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.009*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePower\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.65\u0026thinsp;\u0026plusmn;\u0026thinsp;0.14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.98\u0026thinsp;\u0026plusmn;\u0026thinsp;0.14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.694\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003cp\u003e\u003c/p\u003e\n \u003cp\u003eP, super inductive group; Cont, control group; T, transcranial group; Comb, combined group; SDNN, RR-interval; LF, Low Frequency; HF, High Frequency; Power, LF/HF ; significant differences with p\u0026lt;0.05; **, Significant differences with p\u0026lt;0.001.\u0026nbsp;\u003c/p\u003e\n\u003c/div\u003e"},{"header":"DISCUSSION","content":"\u003cp\u003eIn our study, we observed discernible differences among the intervention groups, reflecting diverse effects on autonomic nervous system regulation. Notably, the Super Inductive Group (P) and the Transcranial Group (T) demonstrated distinct changes in Heart Rate Variability (HRV) metrics over time, which suggested differential modulation of sympathetic and parasympathetic nervous system activities. A reduction in low-frequency (LF) components across these groups may indicate a decrease in sympathetic nervous system dominance, typically associated with stress and arousal states. Conversely, an increase in high-frequency (HF) components, especially observed in the Combined Group (Comb), highlighted a shift toward parasympathetic dominance, emphasizing enhanced vagal tone and potential improvements in recovery and stress resilience (Clemente-Su\u0026aacute;rez, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). Such a shift is crucial for athletes and individuals experiencing stress, as higher vagal tone is linked to better stress management, recovery, and overall cardiovascular health (Bustamante-S\u0026aacute;nchez et al., \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). These findings imply that specific interventions, either alone or in combination, can significantly influence the balance of the autonomic nervous system, with potential implications for enhancing human performance and well-being.\u003c/p\u003e \u003cp\u003eThe P group likely experienced changes due to the direct impact of physical stimuli on muscle and neural pathways, influencing sympathetic nervous system activity. The Super Inductive System employs high-intensity electromagnetic fields to treat conditions of the neuromusculoskeletal system, potentially affecting muscle and neural pathways (Neculăeș \u0026amp; Lucaci, \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). In contrast, the T group, through non-invasive brain stimulation, might have affected the central nervous system's regulation of autonomic functions, altering the balance towards either increased sympathetic or parasympathetic activity, depending on the stimulation parameters (Thayer \u0026amp; Lane, \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e2000\u003c/span\u003e). The Comb group experienced the synergistic effects of both physical and neural interventions, leading to a more pronounced shift towards parasympathetic dominance. This comprehensive approach potentially maximizes benefits by targeting multiple pathways for autonomic regulation, illustrating the intricate interplay between different types of interventions and the autonomic nervous system's adaptability (Critchley et al., \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2013\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe variations in HRV responses observed in our study, as compared to prior research, underscore the complex interplay between intervention specifics and individual differences. Foundational insights provided by Thayer et al. (\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e2012\u003c/span\u003e) and Laborde et al. (\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2017\u003c/span\u003e) on how lifestyle modifications can modulate autonomic functions emphasize HRV's role as a biomarker for stress and recovery (Laborde et al., \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Thayer et al., \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e2012\u003c/span\u003e). Our results extend this narrative, illustrating that interventions do not exert uniform effects on HRV, likely due to variances in methodological approaches, including the intensity, duration, and nature of the interventions. Additionally, the distinct physiological and psychological backgrounds of participants introduce another layer of complexity, as evidenced by Kiviniemi et al. (\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2007\u003c/span\u003e), where the impact of aerobic training on HRV varied with the fitness level of the individuals (Kiviniemi et al., \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2007\u003c/span\u003e). These discrepancies highlight the need for personalized approaches in designing interventions aimed at optimizing autonomic balance and underscore the necessity for further research to unravel the mechanisms underlying these effects.\u003c/p\u003e \u003cp\u003eDelving deeper into the influence of electromagnetic stimulation on the autonomic nervous system, it is imperative to highlight the significant parasympathetic activation observed in our results, particularly concerning the HRV parameters across different groups. The use of both Transcranial Magnetic Stimulation (TMS) and Peripheral Electromagnetic Stimulation (PES) in our Comb group not only enhanced parasympathetic activity but also suggests an optimization of recovery processes in athletes. This contrasts with studies focusing solely on TMS, where results often show increased sympathetic activity, particularly in clinical settings involving patients with depression. The parasympathetic influence, critical for recovery and stress resilience, is supported by our findings showing significant differences in HRV measures among the groups, with a notable increase in HF components (Carnevali et al., \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). Such observations are crucial, as they indicate a shift towards parasympathetic dominance. This shift, associated with improved vagal tone, underscores the compounded benefits of combining TMS with PES.\u003c/p\u003e \u003cp\u003eMoreover, the absence of negative effects on the autonomic nervous system underscores the safety and suitability of these treatments. Our treatments did not disrupt the normal physiological recovery processes associated DOMS. Furthermore, the data provided in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e further substantiates these points. While the creatine kinase and lactate levels indicated increases post-exercise\u0026mdash;a typical response indicating muscle stress and recovery\u0026mdash;there were no significant differences between the groups at any measured time point (Callegari et al., \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). This uniformity suggests that while the exercise protocol effectively induced muscle stress, the electromagnetic treatments managed to modulate recovery without exacerbating muscle damage or stress response, as evidenced by stable enzyme levels across all groups. In contrast to other studies, such as those analyzing the effects of nutritional interventions on HRV (e.g., energy drinks leading to changes primarily in high-frequency indices), our approach using TMS combined with PES showcases a broader regulatory impact on both high and low-frequency components of HRV. This suggests a more comprehensive modulation of the autonomic nervous system, potentially offering a more effective means of enhancing athletic recovery and performance.\u003c/p\u003e \u003cp\u003eIn contrast to other studies, such as those analyzing the effects of nutritional interventions on HRV, our approach using TMS combined with PES showcases a broader regulatory impact on both high and low-frequency components of HRV (Lopresti, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; \u0026ldquo;Nutrition and Athletic Performance,\u0026rdquo; 2016; Zahar et al., \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). This suggests a more comprehensive modulation of the autonomic nervous system, potentially offering a more effective means of enhancing athletic recovery and performance.\u003c/p\u003e \u003cp\u003eFurthermore, our study's group-by-time interactions, as detailed in the subsequent analysis, reveal significant differences in HRV parameters such as LF and HF, not just at a single post-exercise point but across multiple recovery phases. This progressive monitoring highlights the dynamic changes in autonomic nervous system activity and provides a more detailed understanding of how these interventions influence recovery over time.\u003c/p\u003e \u003cp\u003eIn conclusion, our research underscores the importance of considering combined electromagnetic stimulation therapies in sports medicine and rehabilitation. By demonstrating no adverse effects and highlighting significant enhancements in autonomic regulation, this study not only reaffirms the safety of these interventions but also their potential efficacy in improving physiological recovery and athletic performance. Future research should continue to explore these interactions, ideally incorporating a broader demographic and varied athletic disciplines to fully ascertain the generalizability and scope of these findings.\u003c/p\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003eStudy Limitations and future research lines\u003c/h2\u003e \u003cp\u003eWhile our findings contribute valuable insights into the effects of combined electromagnetic stimulation on autonomic nervous system regulation and recovery processes, several limitations must be acknowledged. First, the generalizability of our results may be restricted. The study focused on active, young male athletes, which raises questions about the applicability of our findings to less active populations or women. Future research should, therefore, aim to explore the effects of combined treatment modalities across a more diverse demographic to enhance the universality of the findings.\u003c/p\u003e \u003cp\u003eFurthermore, the biomarkers used in our study primarily included creatine kinase and lactate levels. While these are indicative of muscle stress and recovery, expanding future analyses to include a broader range of biomarkers could provide deeper insights into the physiological impacts of the treatments. Studies could investigate how these interventions influence other recovery-related parameters, such as inflammatory markers and additional metabolic enzymes, which may further elucidate the mechanisms driving the DOMS recovery process (Kyriakidou et al., \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2021\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eAdditionally, the potential interactions between electromagnetic stimulation treatments and long-term medication use or recovery processes in patients with chronic conditions, such as cancer, warrant exploration. Understanding these interactions could significantly expand the scope of practice for these treatments, potentially offering new therapeutic avenues for managing symptoms and enhancing recovery in clinical populations (He et al., \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2022\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eLastly, incorporating psychological assessments into future studies could provide a more comprehensive understanding of the recovery process. Parameters such as central fatigue and recovery sensation are critical yet often overlooked aspects of post-exercise recovery. Including psychological questionnaires and subjective measures of wellness and fatigue could reveal important insights into the mental and emotional dimensions of recovery, which are integral to holistic treatment approaches.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003ePractical applications and keypoints\u003c/h2\u003e \u003cp\u003eEnhanced Recovery Protocols: The study demonstrates the potential of combined transcranial and peripheral electromagnetic stimulation to facilitate recovery in athletes. This can be incorporated into sports medicine practices to reduce downtime and improve recovery rates after intense physical activities.\u003c/p\u003e \u003cp\u003eNon-Invasive Treatment Options: The safety and efficacy of the non-invasive treatment modalities presented in the study suggest that they can be used as alternatives to more invasive recovery methods. This is particularly relevant for athletes who are sensitive to traditional medical treatments or who prefer less invasive recovery techniques.\u003c/p\u003e \u003cp\u003eAutonomic Nervous System Regulation: The findings emphasize the role of autonomic nervous system regulation in athletic performance and recovery. Training programs and rehabilitation protocols can be designed to target this system, potentially enhancing overall athletic performance and well-being.\u003c/p\u003e \u003cp\u003eHolistic Approach to Athlete Health: The study supports a holistic approach to athlete health, where both physical and neurological aspects are considered. This could lead to more comprehensive health management strategies in sports organizations and teams.\u003c/p\u003e \u003cp\u003eTailored Therapeutic Strategies: Given the differential effects observed across various groups in the study, sports medicine professionals can tailor electromagnetic stimulation protocols based on individual athlete needs and responses, optimizing performance outcomes.\u003c/p\u003e \u003cp\u003eResearch and Development: The findings encourage further research and development in electromagnetic stimulation technologies. This could lead to more refined devices and treatment protocols specifically optimized for different sports and activities.\u003c/p\u003e \u003c/div\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThe results from this clinical trial highlight the potential and safety of combined transcranial and peripheral electromagnetic stimulation as a therapeutic modality. This innovative approach illuminates the recovery processes within the Autonomic Nervous System, facilitating a deeper and more comprehensive understanding of both the mechanisms and recovery associated with Delayed Onset Muscle Soreness (DOMS). Crucially, the findings demonstrate that the natural physiological processes of DOMS recovery were not adversely affected by the treatments administered. This observation suggests that this non-invasive approach could represent a novel strategy in the management and enhancement of athletic performance and rehabilitation. By preserving the body's inherent recovery dynamics while effectively aiding in the recovery process, combined electromagnetic stimulation may offer a valuable tool in sports medicine, potentially setting a new standard for athlete care and performance optimization.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003cstrong\u003e:\u0026nbsp;\u003c/strong\u003eThe study was approved by the\u0026nbsp;Research Ethics Committee of the Clinical Hospital San Carlos (reference number: C.I. 23/048-E).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003cstrong\u003e:\u0026nbsp;\u003c/strong\u003eWe have the consent for publication. We register our study in the Australian New Zealand Clinical Trials Registry (reference number:\u0026nbsp;ACTRN12623000677606).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003cstrong\u003e:\u0026nbsp;\u003c/strong\u003eWe have the availability of the data, and the materials are available at the request of the publisher.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflicts of interest:\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003eThe authors declared no potential conflicts of interest\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003ewith respect to the research, authorship, and/or publication of this article.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding:\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003eThe authors received no financial support for the research, authorship, and/or publication of this article.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003cstrong\u003e:\u003c/strong\u003e We would like to thank to the students at the European University of Madrid for participating in the study and to the University itself. And MR Inc. (Republic of Korea) for provide us the devices MagRex magnetic stimulator.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor contributions\u003c/strong\u003e\u003cstrong\u003e:\u003c/strong\u003e ASS and HK carried out the design and idea of the project, HK, JFTA and DDB wrote the introduction to the manuscript, AGF, MGA and MBA wrote the methodology and statistics part, DDB, MPSF and HK wrote the Discussion and conclusions part, GGPS, VJCS and AGF prepared figures 1 \u0026amp; 2. All authors reviewed the manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eContribution to the field:\u003c/strong\u003e This work represents an advance in finding the appropriate therapeutic strategies to improve the symptoms of DOMS and thus be able to anticipate athletes to their training without risk of injury, and with the certainty of adding stimuli to the muscles to be able to provoke physiological adaptations derived from eccentric exercise. Therefore, based on the new theory of DOMS caused by axonopathy, paired-associative electromagnetic stimulation peripheral and transcranial treatment could improve muscle pain and sports performance in athletes.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eBarker, A. T. (1991). An Introduction to the Basic Principles of Magnetic Nerve Stimulation. \u003cem\u003eJournal of Clinical Neurophysiology\u003c/em\u003e, \u003cem\u003e8\u003c/em\u003e(1), 26\u0026ndash;37. https://doi.org/10.1097/00004691-199101000-00005\u003c/li\u003e\n\u003cli\u003eBeltr\u0026aacute;, P., Ruiz‐del‐Portal, I., Ortega, F. J., Valdesuso, R., Delicado‐Miralles, M., \u0026amp; Velasco, E. (2022). 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Neuromuscular Fatigue and Recovery after Heavy Resistance, Jump, and Sprint Training. \u003cem\u003eMedicine \u0026amp; Science in Sports \u0026amp; Exercise\u003c/em\u003e, \u003cem\u003e50\u003c/em\u003e(12). https://doi.org/10.1249/MSS.0000000000001733\u003c/li\u003e\n\u003cli\u003eTodd, G., Taylor, J. L., \u0026amp; Gandevia, S. C. (2003). Measurement of voluntary activation of fresh and fatigued human muscles using transcranial magnetic stimulation. \u003cem\u003eThe Journal of Physiology\u003c/em\u003e, \u003cem\u003e551\u003c/em\u003e(2), 661\u0026ndash;671. https://doi.org/10.1113/jphysiol.2003.044099\u003c/li\u003e\n\u003cli\u003eTornero Aguilera, J. F., Fernandez Elias, V., \u0026amp; Clemente-Su\u0026aacute;rez, V. J. (2021). Autonomic and cortical response of soldiers in different combat scenarios. \u003cem\u003eBMJ Military Health\u003c/em\u003e, \u003cem\u003e167\u003c/em\u003e(3), 172\u0026ndash;176. https://doi.org/10.1136/jramc-2019-001285\u003c/li\u003e\n\u003cli\u003eVernillo, G., Khassetarash, A., Millet, G. Y., \u0026amp; Temesi, J. (2021). Use of transcranial magnetic stimulation to assess relaxation rates in unfatigued and fatigued knee-extensor muscles. \u003cem\u003eExperimental Brain Research\u003c/em\u003e, \u003cem\u003e239\u003c/em\u003e(1), 205\u0026ndash;216. https://doi.org/10.1007/s00221-020-05921-9\u003c/li\u003e\n\u003cli\u003eZahar, S., De Longis, E., \u0026amp; Hudry, J. (2023). Revealing the Acute Effects of Dietary Components on Mood and Cognition: The Role of Autonomic Nervous System Responses. \u003cem\u003eBrain Sciences\u003c/em\u003e, \u003cem\u003e13\u003c/em\u003e(8), 1177. https://doi.org/10.3390/brainsci13081177\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":true,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"journal-of-translational-medicine","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"jtrm","sideBox":"Learn more about [Journal of Translational Medicine](http://translational-medicine.biomedcentral.com)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/jtrm/default.aspx","title":"Journal of Translational Medicine","twitterHandle":"@BioMedCentral","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Delayed Onset Muscle Soreness, transcranial electromagnetic stimulation, peripheral electromagnetic stimulation, athletes, recovery, heart rate variability","lastPublishedDoi":"10.21203/rs.3.rs-5225529/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-5225529/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eDelayed Onset Muscle Soreness (DOMS) has been extensively studied by scientists and sports teams over the last few decades. Eccentric exercises impact physiology and recovery, as shown in recent studies. This study investigates the effects of combined transcranial and peripheral electromagnetic stimulation on the autonomic nervous system in 48 young athletes. Participants were divided into four groups: Control (n\u0026thinsp;=\u0026thinsp;12), Peripheral (n\u0026thinsp;=\u0026thinsp;13), Transcranial (n\u0026thinsp;=\u0026thinsp;11), and Combined (n\u0026thinsp;=\u0026thinsp;12). The autonomic nervous system was assessed through Heart Rate Variability (HRV) monitoring before and after the eccentric session that induced DOMS and at 24h, 48h, and 72h post-session.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eThe Combined Group showed increased activation in various HRV parameters, including LF (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), HF (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), and the LF/HF power ratio (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). These results indicate that combined transcranial and peripheral electromagnetic stimulation enhances recovery in athletes after 72 hours.\u003c/p\u003e\u003ch2\u003eConclusions\u003c/h2\u003e \u003cp\u003ePaired-associative electromagnetic stimulation positively influences the autonomic nervous system response in young athletes, promoting recovery without disrupting the typical physiological recovery process in DOMS.\u003c/p\u003e","manuscriptTitle":"Influence of Combined Transcranial and Peripheral Electromagnetic Stimulation on the Autonomous Nerve System on Delayed Onset Muscle Soreness in Young Athletes. A Randomized Clinical Trial.","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-12-02 16:29:35","doi":"10.21203/rs.3.rs-5225529/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Major revision","date":"2024-12-21T02:10:19+00:00","index":"","fulltext":""},{"type":"reviewerAgreed","content":"","date":"2024-11-05T02:40:53+00:00","index":0,"fulltext":""},{"type":"reviewersInvited","content":"","date":"2024-11-04T12:03:29+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2024-10-23T15:08:08+00:00","index":"","fulltext":""},{"type":"submitted","content":"Journal of Translational Medicine","date":"2024-10-08T08:58:04+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"journal-of-translational-medicine","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"jtrm","sideBox":"Learn more about [Journal of Translational Medicine](http://translational-medicine.biomedcentral.com)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/jtrm/default.aspx","title":"Journal of Translational Medicine","twitterHandle":"@BioMedCentral","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"3a8dc78d-7dff-4492-8459-3ca213b6f645","owner":[],"postedDate":"December 2nd, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2025-03-17T16:02:06+00:00","versionOfRecord":{"articleIdentity":"rs-5225529","link":"https://doi.org/10.1186/s12967-025-06238-3","journal":{"identity":"journal-of-translational-medicine","isVorOnly":false,"title":"Journal of Translational Medicine"},"publishedOn":"2025-03-10 15:57:47","publishedOnDateReadable":"March 10th, 2025"},"versionCreatedAt":"2024-12-02 16:29:35","video":"","vorDoi":"10.1186/s12967-025-06238-3","vorDoiUrl":"https://doi.org/10.1186/s12967-025-06238-3","workflowStages":[]},"version":"v1","identity":"rs-5225529","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-5225529","identity":"rs-5225529","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}