How Static and Kinetic Meditation, with or without Guidance, Affect Autonomic Nervous System Activity in Novice Meditators

How Static and Kinetic Meditation, with or without Guidance, Affect Autonomic Nervous System Activity in Novice Meditators | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article How Static and Kinetic Meditation, with or without Guidance, Affect Autonomic Nervous System Activity in Novice Meditators Jinwoo Han, Teri Kim This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6389936/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract This study explored the autonomic nervous system responses and perceived experiences of novice meditators during kinetic and static meditation. Thirty-five participants completed both meditation types in randomized order. Each 20-minute session included 10 minutes of guided and 10 minutes of unguided meditation. Heart rate variability (HRV) was recorded using the Polar H10 and EliteHRV apps. A visual analog scale (VAS) assessed depth and focus, peace and calm, and drowsiness. Results indicated that depth and focus were significantly higher in kinetic than in static meditation and were also higher when guidance was provided. Static meditation induced greater drowsiness than did kinetic meditation, particularly in the unguided condition. All meditation conditions increased the heart rate (HR) compared to rest, with guided meditation showing a significantly higher heart rate than unguided meditation. The mean RR intervals were shorter under all meditation conditions than at rest. RMSSD and lnRMSSD were significantly lower during guided and unguided static meditation and guided kinetic meditation than at rest. Both guided static and kinetic meditation reduced high frequency (HF) power and increased the PNN50. Increased sympathetic nervous system activity during guided meditation suggests a higher cognitive effort among novice meditators, leading to heightened physiological arousal. These findings highlight how movement and guidance influence autonomic responses and meditation experiences, thereby contributing to the scientific foundation of meditation-based interventions. Biological sciences/Physiology Biological sciences/Psychology Health sciences/Biomarkers Health sciences/Health care static meditation kinetic meditation heart rate variability autonomic nervous system sympathetic nervous system Figures Figure 1 1 Introduction The global meditation app market has grown substantially, especially since the COVID-19 pandemic, which has increased awareness of mental health challenges. In 2019, the market value for meditation apps was USD 270.39 million, with projections estimating it to reach USD 4.21 billion by 2027 [1]. Despite this rapid expansion, many meditation apps suffer from a lack of evidence-based content, low-quality offerings, and a limited understanding of their mechanisms. For instance, among the 700 meditation apps on the iTunes Store, only 23 provide genuine meditation training, and only one is supported by empirical evidence [2]. This lack of scientific validation exposes users to potentially ineffective interventions [3]. The meditation techniques of these apps focus on static seated meditation, with few incorporating kinetic forms of meditation that involve physical movement. An analysis of 16 popular iPhone meditation apps revealed that all featured static guided meditation, and none included kinetic approaches [4]. This gap in meditation content may arise from a limited understanding of the different forms of meditation. Many developers create apps based on assumptions of or imitating successful ones, with effectiveness testing often occurring after development, which can lead to a “digital placebo” effect [3,4]. Additionally, the overall quality of meditation apps is suboptimal, with an average Mobile Application Rating Scale (MARS) score of 3.2 out of 5.0 for 700 meditation apps [2]. These factors highlight the critical need for a rigorous investigation into the mechanisms and effectiveness of various meditation forms. The increasing popularity of meditation has driven extensive scientific research across fields, such as psychology, medicine, and neuroscience. Publications on meditation grew from fewer than 100 in 2006 to 2,808 in 2020, with an average annual growth rate of 23.5% between 2010 and 2020 [5]. These studies focused primarily on the physical and psychological benefits of meditation-based interventions. Meditation techniques are broadly categorized into static and kinetic forms. Static meditation includes seated practices such as mindfulness, mantra meditation, and body scans, whereas kinetic meditation includes movement-based practices such as Hatha yoga, walking meditation, dance, qigong, and tai chi. Hybrid approaches such as Mindfulness-Based Stress Reduction (MBSR), combine static and kinetic elements [6]. Despite meditation’s documented benefits, challenges such as publication bias and negative user experiences are often overlooked. A meta-analysis of 39 studies on meditation revealed a tendency to report only positive results [7]. In practice, individuals encounter obstacles such as drowsiness, discomfort, boredom, and negative emotions during static meditation [8]. For example, maintaining focus during a 30-minute body scan without falling asleep is difficult, particularly for beginners, children, and those with physical limitations [9]. These challenges make static meditation unsustainable. Research suggests that kinetic meditation offers enhanced benefits over static meditation. A meta-analysis comparing various meditation types found that while static meditation interventions produce medium effect sizes (Cohen’s d = 0.4–0.5), kinetic forms like yoga have a larger effect size (Cohen’s d = 0.77) for improving psychological well-being [10]. Programs such as MBSR, which incorporate yoga, have demonstrated greater efficacy in promoting psychological well-being than do static practices alone [7,11]. These findings highlight kinetic elements’ potential for enhancing meditation's positive effects, despite limited research on kinetic meditation. Matko and Sedlmeier (2019) who identified 309 meditation techniques, categorizing them into seven clusters, including meditation with movement, pointed out the lack of research on movement-based meditation techniques and highlighted the need for studies on their specificities and working mechanisms, as well as comparisons with other basic meditation techniques [12]. Heart rate variability (HRV), a physiological marker of health, has garnered attention because of technological advances in its measurement. HRV reflects the time variability between heartbeats and is linked to vagus nerve activity, a key component of the parasympathetic nervous system (PNS). Higher HRV indicates better autonomic regulation and stress recovery, whereas lower HRV is associated with chronic stress and mental health disorders [13]. Meditation practices, particularly mindfulness and focused breathing, improve HRV and provide an objective measure of physiological benefits [14,15]. However, the effects of static and kinetic meditation on HRV and autonomic nervous system (ANS) regulation have rarely been directly compared. Studies on attention-focused static meditation have shown changes in HRV metrics, such as increased SDNN, RMSSD, and HF power, along with decreased LF power and LF/HF ratio, suggesting enhanced parasympathetic activity [16–18]. A meta-analysis of 17 RCTs on Tai Chi and Yoga also found similar trends, including decreased LF power and increased HF power [18]. However, these studies, based on long-term interventions (8–16 weeks), did not address changes occurring within meditation sessions. Hunt et al. (2018) further explored these distinctions by dismantling MBSR components, revealing that yoga-based interventions involving movement were associated with higher resting HRV and more adaptive vagal responses to stress [6]. This suggests that movement-based meditation promotes better stress adaptation through flexible parasympathetic responses [14]. In contrast, mindfulness without movement resulted in more stable HRV, indicating reduced stress rather than dynamic autonomic adaptation [20]. These findings underscore the need for further research on how static and kinetic meditation affect autonomic functions differently and their therapeutic implications. Despite these insights, research on kinetic meditation remains scarce compared to that on static forms. Little is known about how these practices differentially affect ANS regulation. Given the distinct physiological responses observed, a direct comparison between static and kinetic meditation is essential to better understand their unique mechanisms and therapeutic potential. This study aimed to examine the impact of kinetic meditation on ANS regulation by comparing it with that of static meditation. By providing empirical evidence of the physiological differences between these meditation practices, this study provides valuable insights into the scientific foundation for meditation-based interventions. 2 Results 2.1 VAS 2.1.1 Depth and Focus The analysis was conducted using a two-way RM-ANOVA with a 2 (meditation type: static vs. kinetic) × 2 (guidance: guided vs. unguided) design. A significant main effect of meditation type was observed, F(1, 34) = 6.209, p = .018, partial η² = .154, indicating that participants experienced greater depth and focus during kinetic meditation (mean = 6.366, standard error = .236) than during static meditation (mean = 5.790, standard error = .269). A significant main effect of guidance was also found, F(1, 34) = 4.875, p = .034, partial η² = .125, with participants reporting higher depth and focus during audio-guided meditation (mean = 6.370, standard error = .220) than during unguided meditation (mean = 5.786, standard error = .297). To further examine the differences across the four conditions, a one-way RM-ANOVA was conducted. The results showed a significant effect of condition on depth and focus ratings, F(3, 102) = 4.478, p = .005, partial η² = .116. Post hoc comparisons indicated that guided kinetic meditation showed significantly higher depth and focus scores than in unguided static meditation (Table 2). 2.1.2 Peace and Calm For the peace and calm ratings, neither the one-way nor two-way RM-ANOVA revealed any significant differences across conditions. 2.1.3 Drowsiness The two-way RM-ANOVA revealed a significant main effect of meditation type on drowsiness, F(1, 34) = 14.742, p = .001, partial η² = .288. articipants reported greater drowsiness during static meditation (mean = 3.890, standard error = .439) than during kinetic meditation (mean = 2.256, standard error = .381). The one-way RM-ANOVA conducted on drowsiness ratings showed a significant effect of condition, F(3, 102) = 7.170, p = .000, partial η² = .174. Pairwise comparisons revealed that drowsiness during unguided static meditation was significantly higher than during both guided kinetic meditation (p = .020) and unguided kinetic meditation (p = .001) (Table 2). 2.2 HRV Differences in HR and HRV metrics across the resting state, guided static, unguided static, guided kinetic, and unguided kinetic meditation conditions are shown in Figure 1. 2.2.1 Heart Rate Analysis The min HR during guided static meditation was significantly higher than that during the resting state (F(4, 128) = 3.031, p = .020, partial η² = .087), while the max HR was significantly higher in all meditation conditions than in the resting state (F(4, 128) = 9.394, p = .000, partial η² = .227). We also observed significant differences in average HR, (F(4, 128) = 15.431, p = .000, partial η² = .325), where average HR during all meditation conditions was higher than that during the resting state. Additionally, the guided meditation conditions (both static and kinetic) showed a higher average HR than do their respective unguided meditation conditions. 2.2.2 HRV Time-domain Analysis RMSSD during guided static, unguided static, and guided kinetic meditation was significantly lower than during the resting state (F(4, 128) = 5.974, p = .000, partial η² = .157). lnRMSSD also demonstrated significant differences among conditions (F(4, 128) = 6.920, p = .000, partial η² = .178), with lnRMSSD during the resting state higher than in all other conditions. Additionally, lnRMSSD was significantly higher during unguided kinetic meditation than during guided kinetic meditation. The resting-state PNN50 was higher than was guided static and guided kinetic meditation (F(4, 84) = 5.412, p = .001, partial η² = .205). Mean RR intervals showed significant differences (F(4, 128) = 15.250, p = .000, partial η² = .323), with the resting state having longer mean RR intervals compared to all other conditions. However, no significant differences were observed in SDNN. 2.2.3 HRV Frequency-domain Analysis The LF/HF ratio was significantly higher during guided and unguided kinetic meditation conditions than during the resting state (F(4, 128) = 4.082, p = .004, partial η² = .113). HF power was significantly lower during guided static and guided kinetic meditation than during the resting state (F(4, 128) = 4.491, p = .002, partial η² = .123). However, the TF and LF powers did not differ significantly across the conditions. 3 Discussion This study investigated autonomic responses during kinetic and static meditation, along with the meditators' perceived experiences. VAS analysis revealed significant differences in participants’ self-reported depth and focus depending on the type of meditation and presence of guidance. Kinetic meditation led to higher levels of depth and focus than did static meditation, whereas audio-guided meditation induced greater depth and focus than did unguided meditation. These findings suggest that movement-based meditation and verbal guidance play crucial roles in enhancing meditators’ engagement. Given that the participants in this study were beginners with no prior systematic meditation training, it appears that physical movements and audio guidance helped reduce boredom and facilitated a deeper focus. For novice practitioners, seated meditation often induces drowsiness and physical discomfort, whereas movement-based practices such as walking meditation or Hatha yoga minimize distractions from drowsiness or bodily discomfort, making continued practice easier [9]. This claim was supported by the VAS drowsiness analysis in this study, which showed that static meditation induced significantly more drowsiness than kinetic meditation. This can be attributed to the minimal physical activity during static meditation, which may lead to greater fatigue or sleepiness. Notably, unguided static meditation resulted in the highest level of drowsiness, suggesting that the absence of verbal cues makes sustaining focus more challenging. This was further supported by the VAS depth and focus scores, where unguided static meditation received the lowest ratings, indicating that it may create an environment in which practitioners are more prone to falling into a drowsy state. Together, these findings suggest that kinetic meditation may be a more suitable approach for beginners than static meditation. However, no significant differences were observed in peace and calm measures across meditation types or guidance conditions, indicating that these factors may have less of an influence on tranquility. This suggests that all four meditation conditions promote a sense of peace and calm. Heart rate and HRV were analyzed across the resting state, guided static meditation, unguided static meditation, guided kinetic meditation, and unguided kinetic meditation to examine the differences in autonomic responses. Both max and average HR were higher in all meditation conditions than in the resting state. This suggests that cognitive engagement, such as sustained attention and physical movement during kinetic meditation, may provide neurophysiological stimulation, leading to an elevated heart rate relative to rest. Notably, the average HR was significantly higher during guided meditation than during unguided meditation, while the minimum HR was significantly higher during guided static meditation than in in the resting state. These findings suggest that processing verbal instructions, integrating them cognitively, and executing the corresponding tasks may contribute to increased sympathetic nervous system (SNS) activation. This interpretation is further supported by the mean RR interval, which was shorter in all meditation conditions than in the resting state. A shorter mean RR interval, meaning reduced the time between successive heartbeats, indicates a faster and more unstable heart rate during meditation. This is often associated with increased SNS activity and reduced PNS dominance, which reflects a state of heightened physiological arousal or stress. These results align with those of a previous study, which reported that heart rate increased during meditation compared with baseline, suggesting SNS activation during meditation [21]. Although meditation is often associated with relaxation, it can also function as a mental task that requires cognitive effort and has been linked to physiological arousal [22,23]. Mental states that impose high cognitive demands influence ANS activity [24]. The observed increase in heart rate and decrease in the HRV during meditation in this study may be attributed to the cognitive demands placed on participants, particularly because they were meditation novices. Prior research suggests that the physiological meditation effects vary depending on the type, level of cognitive effort required, and extent of prior training [24]. Furthermore, mental effort during meditation tends to decrease with increasing expertise over time [25]. Because this study did not include a comparison based on expertise, future research should examine the differences between novice and experienced meditators. The RMSSD and lnRMSSD were significantly lower in the guided static meditation, unguided static meditation, and guided kinetic meditation conditions than in in the resting state. This suggests an increase in SNS activation or a relative decrease in PNS activity during meditation. The required active engagement in meditation may have increased participants' mental effort, leading to heightened physiological arousal. In contrast, unguided kinetic meditation was the only condition in which RMSSD did not decrease relative to the resting state. Furthermore, lnRMSSD was higher for unguided kinetic meditation than for guided kinetic meditation. These findings may be attributed to a practice effect as unguided kinetic meditation was performed after the guided condition, potentially allowing participants to engage in meditation in a more familiar and relaxed state. Another possibility is that participants may have engaged in less physical movement in the unguided condition because of no instructional guidance. Alternatively, freedom from external demands in unguided kinetic meditation may facilitate greater parasympathetic activation [26]. However, to generalize this interpretation, this study did not collect data on participants' actual movement levels in the unguided condition to compare with guided kinetic meditation, making it difficult to generalize this interpretation. Therefore, future studies should examine the extent of physical activity under different conditions. Furthermore, both guided static meditation and kinetic meditation resulted in a significant decrease in HF power and an increase in PNN50 compared to the resting state. These results suggest a reduction in parasympathetic tone, which may occur due to stress, cognitive load, or sympathetic activation [27]. Given that participants reported greater focus during guided meditation based on the VAS results, the observed decrease in HF power along with an increase in PNN50 was more likely attributable to cognitive load than stress. This finding suggests that following guided instructions during meditation imposes cognitive demands that contribute to increased sympathetic activation. This study found that the LF/HF ratio in both guided and unguided kinetic meditation was significantly higher than that in the resting state. The LF/HF ratio is a key indicator used to assess the ANS balance. A high LF/HF ratio reflects increased sympathetic or suppressed PNS activation, which are associated with stress, tension, and the dominant action of the SNS during physical activity [28]. This suggests that kinetic meditation involving movement activates the SNS. In particular, the elevated LF/HF ratio observed during kinetic meditation may be related to withdrawal of cardiac vagal control. As parasympathetic regulation decreases, the SNS becomes relatively dominant, which may activate mechanisms that increase the heart rate and cardiac output [20]. This reduction in parasympathetic control could serve as a rapid physiological adaptation to meet the demands of the situation, particularly in response to physical activity [29,30]. This study has several limitations. First, the sample consisted of meditation novices, which may limit the generalizability of the findings to experienced meditators as autonomic responses could vary with expertise [25]. Future research should also examine long-term effects, including breath-rate variability (BRV), which can provide insight into short-term autonomic changes, whereas HRV is more indicative of long-term effects [31]. Additionally, because this study measured and compared the ANS responses during meditation, we were unable to identify immediate or lasting effects after meditation. Although the order of static and kinetic meditation was randomized, the sequence of guided meditation followed by unguided meditation may have influenced the results owing to potential sequence effects. Additionally, the study did not measure or control the actual levels of physical movement during unguided kinetic meditation, which may have influenced the results. Future studies should assess physical activity levels across different conditions to better understand their impact. In summary, this study explored participants’ autonomic responses and perceived experiences during kinetic meditation compared to static meditation with and without verbal guidance. The results indicated that depth and focus were higher in kinetic meditation than in static meditation and were higher with verbal guidance. Static meditation induced more drowsiness than kinetic meditation, with unguided static meditation causing the highest level of drowsiness. No significant difference presented in the sense of peace and calm reported by the meditators across conditions. Additionally, all meditation conditions resulted in an increased heart rate and HRV markers associated with SNS activity compared to the resting state. Specifically, an increase in SNS activity during guided meditation appears to be associated with greater cognitive effort among novice meditators, leading to heightened physiological arousal. Together, our findings provide empirical evidence that the inclusion of movement and guidance in meditation can differentially influence the ANS responses and shape how novice meditators perceive their meditation experiences. This study contributes to establishing a scientific foundation for mediation-based interventions. 4 Materials and Methods 4.1 Participants Thirty-five participants (male=15, age: 22.03±2.54) participated in the study. Participants were restricted to healthy adults in their 20s who could engage in light physical activity and had no restrictions on neurophysiological measurements. Additionally, participants had to have no systematic experience in meditation practice, physical disabilities, or mental health conditions. A within-participant experimental design was adopted to minimize individual differences related to personal meditation experience or skills. All participants completed both static and kinetic meditation sessions, with the order randomized and conducted at least 24 h apart to reduce potential carryover effects. Prior to participation, all participants provided written informed consent. This study was approved by the university’s Institutional Review Board (WKIRB-202310-HR-076), and all methods were carried out in accordance with relevant guidelines and regulations. 4.2 Measures 4.2.1 Visual Analog Scale (VAS) To compare the meditation experiences between static and kinetic meditation as well as between audio-guided and unguided conditions, participants were asked to respond to three VAS questions at the end of each meditation session. Each participant rated their feelings on a 0–10 cm line, with endpoints labeled “not at all” and “very much.” The three questions asked were: (1) the depth and focus of their meditation experience, (2) the level of inner peace and calm felt, and (3) the amount of drowsiness experienced. For analysis, the length of the mark from the left endpoint of the scale was measured using a ruler for analysis (Cline et al., 1992). 4.2.2 HRV The Polar H10 (Polar Unk, Finland) was connected via Bluetooth to the EliteHRV app (EliteHRV, Asheville, USA) installed on iPhone 14 (Apple, Inc., Cupertino, CA, USA). The Polar H10 is a wireless chest strap heart rate (HR) monitor that records HR data processed by the EliteHRV app to calculate HRV metrics. Previous research has validated the reliability of measuring HRV using the Polar H10 with the EliteHRV app, with a correlation coefficient (r) of 0.998 or higher compared to measurements using a stationary ECG device (Im and Woo, 2024). HRV was measured during a 5-min resting-state period. Separate measurements were taken during 10-min sessions of four types of meditation: audio-guided static meditation, unguided static meditation, audio-guided kinetic meditation, and unguided kinetic meditation. The Elite HRV app recorded the data, which were automatically saved to the data log after the recording was completed. The following HRV metrics were calculated and displayed: minimum HR, maximum HR, average HR, RMSSD, SDNN, lnRMSSD, PNN50, mean RR interval, total power (TF), LF/HF ratio, LF power, and HF power. These values were coded immediately and used for analysis. 4.3 Procedure The participants were instructed to abstain from caffeine, alcohol, and exercise for at least 12 h prior to each session. During the first visit, participants were provided with a detailed explanation of the study and signed an informed consent form. They then wore a Polar H10 chest strap and sat comfortably in a chair, while their baseline HRV was measured for 5 min. All sessions were conducted individually in a quiet, light-controlled environment to ensure minimal external distraction. After the baseline measurement, participants engaged in either static or kinetic meditation, in the order randomly determined by the researcher. If static meditation was conducted first, the participants sat in a chair and performed seated breathing meditation guided by prerecorded audio for 10 min. Immediately after completing the guided meditation, they responded to VAS. Subsequently, they remained seated and performed 10 min of unguided static meditation, after which they completed the same VAS assessments. On a separate day, participants returned to the laboratory for kinetic meditation. They first engaged in a 10-min session of guided kinetic meditation involving physical movements, following instructions from prerecorded audio. Immediately after the guided session, the participants completed the same VAS assessments. This was followed by a 10-min unguided kinetic meditation session, after which they again completed the VAS assessments, marking the end of the experiment. To minimize order effects, the sequence of static and kinetic meditation sessions was randomized across participants. However, for each meditation type, guided meditation was always conducted before unguided meditation. This approach ensured that participants who were naïve to meditation could familiarize themselves with basic meditation techniques during the guided sessions before independently attempting the unguided sessions. HRV data recording began at the start of each meditation session and ended immediately upon completion, capturing HRV metrics for the entire 10-minute period. The study protocol was retrospectively registered with the Clinical Research Information Service (CRIS) associated with the WHO International Clinical Trials Registry Platform (ICTRP) on 21/03/2025 (registration number: KCT0010333). 4.4 Meditation Protocol The static and kinetic meditation protocols were developed by four certified experts, including a meditation instructor, an exercise psychologist, and a yoga instructor. Both meditations were performed while seated on a chair for consistency and accessibility. Static meditation focused on breathing, whereas kinetic meditation incorporated basic seated yoga movements for beginners. Audio guides for both were recorded in Korean by the same instructor to ensure consistency in tone and delivery. The guided scripts were standardized to 430 words to maintain uniformity across sessions, tailored for participants with no prior meditation experience. 2.4.1 Static Meditation Before the static meditation, participants received the following guidelines: • Sit toward the front edge of the chair with feet shoulder-width apart and back straight. • Keep ears, shoulders, and hip joints aligned. • Relax shoulders, breathe deeply through the nose, and exhale slowly. • Observe the breath naturally without control. • Focus inwardly, minimizing attention to external sounds. • Acknowledge thoughts or emotions and gently return focus to breathing. Before unguided meditation, participants were instructed to follow the same breathing approach practiced during the guided session. 2.4.2 Kinetic Meditation The guidelines for kinetic meditation included: • Align ears, shoulders, and hips in a straight line. • Relax shoulders and breathe deeply, exhaling naturally. • Avoid breath-holding and move slowly, focusing on bodily sensations. • Acknowledge arising thoughts or emotions and refocus on breath and movement. Participants were familiarized with basic precautions before starting. Since movements were guided solely by audio, three poses (mountain, tree, warrior) were shown in pictures, and a researcher demonstrated them. These movements were beginner-friendly, emphasizing mindful alignment and breathing. The movements included in the guided kinetic meditation session are presented in Table 1. The kinetic meditation lasted 10 minutes, incorporating breathing and alignment during transitions. In the unguided session, participants could perform any seated movement, whether from the guided session or freely chosen, focusing on breath, sensations, and emotions. 4.5 Statistical analysis To examine the interaction effects of meditation type (static vs. kinetic) and guidance (guided vs. unguided), a two-way repeated-measures analysis of variance (RM-ANOVA) was conducted. Subsequently, to compare the differences in VAS scores across the four individual conditions (guided static meditation, unguided static meditation, guided kinetic meditation, and unguided kinetic meditation), a one-way RM-ANOVA was performed. To investigate differences in HRV measures (i.e., minimum HR, maximum HR, average HR, RMSSD, SDNN, lnRMSSD, PNN50, mean RR interval, TF, LF/HF ratio, LF power, and HF power) across conditions (i.e., resting-state, guided static meditation, unguided static meditation, guided kinetic meditation, and unguided kinetic meditation), a one-way RM-ANOVA was conducted, with the conditions as the independent variable and HRV metrics as the dependent variable. The effect size for all ANOVA results was calculated using an eta-squared value. Mauchly’s test of sphericity was conducted for all dependent variables, and when the assumption of sphericity was not met, the degrees of freedom for ANOVA were adjusted using the Greenhouse-Geisser correction. All statistical analyses were performed using SPSS version 29 with the significance level set at 0.05. Declarations Competing interests The authors declare no competing interests. Funding This work was supported by the Ministry of Education of the Republic of Korea and the National Research Foundation of Korea (NRF-2023S1A5A8077074) Author Contribution J.H. was responsible for conceptualization, methodology design, data analysis, software development, implementation of the experimental procedures, visualization, funding acquisition, and drafting the original manuscript. T.K. contributed to the conceptual framework, supervised the overall research process, curated the data, supported experimental implementation, and co-wrote the original manuscript. All authors reviewed and edited the manuscript and contributed to interpreting the results and finalizing the paper. Availability of data The datasets used and analyzed during the current study are available from the corresponding author upon reasonable request. References Polaris Market Research. Mindfulness Meditation Apps Market Share, Size, Trends, Industry Analysis Report, by Operating System (Android, iOS, Others); by Service Type (Paid-In App Purchases, Free); by Age Group (6–12 Years Old, 13–18 Years Old, and 19 Above); by Regions; Segment Forecast, 2020–2027 (2020). Mani, M., Kavanagh, D.J., Hides, L. & Stoyanov, S.R. Review and evaluation of mindfulness-based iPhone apps. JMIR mHealth uHealth 3 , e82 (2015). Torous, J. & Firth, J. The digital placebo effect: Mobile mental health meets clinical psychiatry. Lancet Psychiatry 3 , 100–102 (2016). Dauden Roquet, C. & Sas, C. Evaluating mindfulness meditation apps. In Extended Abstracts of the 2018 CHI Conference on Human Factors in Computing Systems , 1–6 (ACM, New York, NY, USA, 2018). Baminiwatta, A. & Solangaarachchi, I. Trends and developments in mindfulness research over 55 years: A bibliometric analysis of publications indexed in Web of Science. Mindfulness 12 , 2099–2116 (2021). Hunt, M., Al-Braiki, F., Dailey, S., Russell, R. & Simon, K. Mindfulness training, yoga, or both? Dismantling the active components of a mindfulness-based stress reduction intervention. Mindfulness 9 , 512–520 (2018). Eberth, J. & Sedlmeier, P. The effects of mindfulness meditation: A meta-analysis. Mindfulness 3 , 174–189 (2012). Sparby, T. What stands in the way becomes the way: Dual and non-dual approaches to meditation hindrances in Buddhist traditions and contemplative science. Religions 13 , 840 (2022). Kim, W. Differential effects of moving and unmoving meditation in meditation-based intervention programs. Korean J. Health Psychol. 18 , 643–667 (2013). Rose, S., Zell, E. & Strickhouser, J.E. The effect of meditation on health: A metasynthesis of randomized controlled trials. Mindfulness 11 , 507–516 (2020). Grossman, P., Niemann, L., Schmidt, S. & Walach, H. Mindfulness-based stress reduction and health benefits: A meta-analysis. J. Psychosom. Res. 57 , 35–43 (2004). Matko, K. & Sedlmeier, P. What is meditation? Proposing an empirically derived classification system. Front. Psychol. 10 , 2276 (2019). McCraty, R. & Shaffer, F. Heart rate variability: New perspectives on physiological mechanisms, assessment of self-regulatory capacity, and health risk. Glob. Adv. Health Med. 4 , 46–61 (2015). Christodoulou, G., Salami, N. & Black, D.S. The utility of heart rate variability in mindfulness research. Mindfulness 11 , 554–570 (2020). Krygier, J.R., Heathers, J.A., Shahrestani, S., Abbott, M., Gross, J.J. & Kemp, A.H. Mindfulness meditation, well-being, and heart rate variability: a preliminary investigation into the impact of intensive Vipassana meditation. Int. J. Psychophysiol. 89 , 305–313 (2013). Nesvold, A. et al. Increased heart rate variability during nondirective meditation. Eur. J. Prev. Cardiol. 19 , 773–780 (2012). Krygier, J.R., Heathers, J.A., Shahrestani, S., Abbott, M., Gross, J.J. & Kemp, A.H. Mindfulness meditation, well-being, and heart rate variability: a preliminary investigation into the impact of intensive Vipassana meditation. Int. J. Psychophysiol. 89 , 305–313 (2013). Arredondo, M. et al. A mindfulness training program based on brief practices (M-PBI) to reduce stress in the workplace: A randomised controlled pilot study. Int. J. Occup. Environ. Health 23 , 40–51 (2017). Zou, L. et al. Effects of Mind–Body Exercises (Tai Chi/Yoga) on Heart Rate Variability Parameters and Perceived Stress: A Systematic Review with Meta-Analysis of Randomized Controlled Trials. J. Clin. Med. 7 , 404 (2018). Laborde, S., Mosley, E. & Mertgen, A. Vagal Tank Theory: The Three Rs of Cardiac Vagal Control Functioning – Resting, Reactivity, and Recovery. Front. Neurosci. 12 , 458 (2018). Lutz, A., Greischar, L.L., Perlman, D.M. & Davidson, R.J. BOLD signal in insula is differentially related to cardiac function during compassion meditation in experts vs. novices. Neuroimage 47 , 1038–1046 (2009). Hansen, A.L., Johnsen, B.H. & Thayer, J.F. Vagal influence on working memory and attention. Int. J. Psychophysiol. 48 , 263–274 (2003). Luft, C.D.B., Takase, E. & Darby, D. Heart rate variability and cognitive function: Effects of physical effort. Biol. Psychol. 82 , 164–168 (2009). Lumma, A.L., Kok, B.E. & Singer, T. Is meditation always relaxing? Investigating heart rate, heart rate variability, experienced effort and likeability during training of three types of meditation. Int. J. Psychophysiol. 97 , 38–45 (2015). Tang, Y.-Y., Rothbart, M.K. & Posner, M.I. Neural correlates of establishing, maintaining, and switching brain states. Trends Cogn. Sci. 16 , 330–337 (2012). Mizuno, K. et al. Mental fatigue caused by prolonged cognitive load associated with sympathetic hyperactivity. Behav. Brain Funct. 7 , 17 (2011). Shaffer, F. & Ginsberg, J.P. An overview of heart rate variability metrics and norms. Front. Public Health 5 , 258 (2017). Billman, G.E. The LF/HF ratio does not accurately measure cardiac sympatho-vagal balance. Front. Physiol. 4 , 26 (2013). Fu, Q. & Levine, B.D. Exercise and the autonomic nervous system. Handb. Clin. Neurol. 117 , 147–160 (2013). Fisher, J.P. Autonomic control of the heart during exercise in humans: role of skeletal muscle afferents. Exp. Physiol. 99 , 300–305 (2014). Soni, R. & Muniyandi, M. Breath rate variability: A novel measure to study the meditation effects. Int. J. Yoga 12 , 45–54 (2019). Cline, M.E., Herman, J., Shaw, E.R. & Morton, R.D. Standardization of the visual analogue scale. Nurs. Res. 41 , 378–380 (1992). Im, C. & Woo, M. Evaluation of the suitability of digital devices for measuring heart rate variability: A comparative analysis with ECG. J. Sport Leis. Stud. 98 , 325–336 (2024). Tables Table 1. Movements included in the kinetic meditation Movement Time Mountain Pose spread and raise the arms up, parallel above the head, then lower them back to the sides. Slowly repeat for 1 min Gently open and close the fists. Slowly repeat for 30 sec Rotate the wrists clockwise and counterclockwise. Slowly repeat for 30 sec Alternately straighten one leg at a time and lift the foot off the ground. Slowly repeat for 1 min Tree Pose Lift one foot and place it on the opposite thigh, bringing the hands together in front of the chest. Hold for 30 sec Extend the arms straight, relax the shoulders, and hold the pose. Hold for 20 sec Switch legs and repeat the same pose. Hold for 30 + 20 sec Warrior Pose Stretch the left leg out to the side, keeping the hands on the hips. Hold for 20 sec Extend the arms out to the sides and gaze beyond the right hand. Hold for 30 sec Switch sides and repeat the same pose. Hold for 20 + 30sec Table 2. Mean and standard deviation of VAS scores reported across four conditions VAS Static Meditation Kinetic Meditation Guided Unguided Guided Unguided Depth and focus 6.01±1.70 5.57±1.85 6.73±1.39 6.00±2.07 Peace and calm 6.61±1.71 5.99±1.79 6.53±1.58 6.19±2.00 Drowsiness 3.66±3.01 4.12±3.12 2.31±2.46 2.21±2.36 Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted 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. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. 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-6389936","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":458795224,"identity":"15c04087-e476-4da7-b5c6-86b681cf5b79","order_by":0,"name":"Jinwoo Han","email":"","orcid":"","institution":"Daegu Catholic University","correspondingAuthor":false,"prefix":"","firstName":"Jinwoo","middleName":"","lastName":"Han","suffix":""},{"id":458795225,"identity":"21381f09-d970-40ff-8732-495c930f5f29","order_by":1,"name":"Teri Kim","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA40lEQVRIiWNgGAWjYJCCgw0GDHIMB8DsBBDBjFc5D1SLMWlaGBsYGBIbiNZiz9778OCMgm3pfcd7D7/82pbGwN9+gNkAry08xw0ObjC4nTvzzLk0a9m2HAaJMwnMCXi1SKQxHHwA1LLhRo6ZsWRbBQPDDQbmA3i1yD8Da0k3gGmRJ6hFgo0B5LAEoBbjhx+BDjMAasHvsDNAh80wuG0488wZM2aGc2k8hmcSm/F6n739GPPHnj+35fmO9xh//FGWLCd3/PBhCXxakAGbNA84okDxRCRg/viDaLWjYBSMglEwkgAAoWxPgHhGXswAAAAASUVORK5CYII=","orcid":"","institution":"Dongguk University-WISE","correspondingAuthor":true,"prefix":"","firstName":"Teri","middleName":"","lastName":"Kim","suffix":""}],"badges":[],"createdAt":"2025-04-07 04:08:14","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6389936/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6389936/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":83283433,"identity":"5a8853a9-9dc5-46e5-bbc8-440abecd05cc","added_by":"auto","created_at":"2025-05-22 10:49:59","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":168104,"visible":true,"origin":"","legend":"\u003cp\u003eDifferences in HR and HRV metrics across resting state, guide-static, unguided static, guided kinetic, and unguided kinetic meditation conditions\u003c/p\u003e","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-6389936/v1/5bd4319c70a7e7b9ae9493b2.png"},{"id":86659704,"identity":"e94df12a-3a9a-447f-af42-2d405683fa60","added_by":"auto","created_at":"2025-07-14 10:32:17","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":782375,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6389936/v1/bee0abb9-2da5-4ea2-be12-4a65b9d20f5e.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"How Static and Kinetic Meditation, with or without Guidance, Affect Autonomic Nervous System Activity in Novice Meditators","fulltext":[{"header":"1 Introduction","content":"\u003cp\u003eThe global meditation app market has grown substantially, especially since the COVID-19 pandemic, which has increased awareness of mental health challenges. In 2019, the market value for meditation apps was USD 270.39\u0026nbsp;million, with projections estimating it to reach USD 4.21\u0026nbsp;billion by 2027 [1]. Despite this rapid expansion, many meditation apps suffer from a lack of evidence-based content, low-quality offerings, and a limited understanding of their mechanisms. For instance, among the 700 meditation apps on the iTunes Store, only 23 provide genuine meditation training, and only one is supported by empirical evidence [2]. This lack of scientific validation exposes users to potentially ineffective interventions [3].\u003c/p\u003e \u003cp\u003eThe meditation techniques of these apps focus on static seated meditation, with few incorporating kinetic forms of meditation that involve physical movement. An analysis of 16 popular iPhone meditation apps revealed that all featured static guided meditation, and none included kinetic approaches [4]. This gap in meditation content may arise from a limited understanding of the different forms of meditation. Many developers create apps based on assumptions of or imitating successful ones, with effectiveness testing often occurring after development, which can lead to a \u0026ldquo;digital placebo\u0026rdquo; effect [3,4]. Additionally, the overall quality of meditation apps is suboptimal, with an average Mobile Application Rating Scale (MARS) score of 3.2 out of 5.0 for 700 meditation apps [2]. These factors highlight the critical need for a rigorous investigation into the mechanisms and effectiveness of various meditation forms.\u003c/p\u003e \u003cp\u003eThe increasing popularity of meditation has driven extensive scientific research across fields, such as psychology, medicine, and neuroscience. Publications on meditation grew from fewer than 100 in 2006 to 2,808 in 2020, with an average annual growth rate of 23.5% between 2010 and 2020 [5]. These studies focused primarily on the physical and psychological benefits of meditation-based interventions. Meditation techniques are broadly categorized into static and kinetic forms. Static meditation includes seated practices such as mindfulness, mantra meditation, and body scans, whereas kinetic meditation includes movement-based practices such as Hatha yoga, walking meditation, dance, qigong, and tai chi. Hybrid approaches such as Mindfulness-Based Stress Reduction (MBSR), combine static and kinetic elements [6].\u003c/p\u003e \u003cp\u003eDespite meditation\u0026rsquo;s documented benefits, challenges such as publication bias and negative user experiences are often overlooked. A meta-analysis of 39 studies on meditation revealed a tendency to report only positive results [7]. In practice, individuals encounter obstacles such as drowsiness, discomfort, boredom, and negative emotions during static meditation [8]. For example, maintaining focus during a 30-minute body scan without falling asleep is difficult, particularly for beginners, children, and those with physical limitations [9]. These challenges make static meditation unsustainable.\u003c/p\u003e \u003cp\u003eResearch suggests that kinetic meditation offers enhanced benefits over static meditation. A meta-analysis comparing various meditation types found that while static meditation interventions produce medium effect sizes (Cohen\u0026rsquo;s d\u0026thinsp;=\u0026thinsp;0.4\u0026ndash;0.5), kinetic forms like yoga have a larger effect size (Cohen\u0026rsquo;s d\u0026thinsp;=\u0026thinsp;0.77) for improving psychological well-being [10]. Programs such as MBSR, which incorporate yoga, have demonstrated greater efficacy in promoting psychological well-being than do static practices alone [7,11]. These findings highlight kinetic elements\u0026rsquo; potential for enhancing meditation's positive effects, despite limited research on kinetic meditation. Matko and Sedlmeier (2019) who identified 309 meditation techniques, categorizing them into seven clusters, including meditation with movement, pointed out the lack of research on movement-based meditation techniques and highlighted the need for studies on their specificities and working mechanisms, as well as comparisons with other basic meditation techniques [12].\u003c/p\u003e \u003cp\u003eHeart rate variability (HRV), a physiological marker of health, has garnered attention because of technological advances in its measurement. HRV reflects the time variability between heartbeats and is linked to vagus nerve activity, a key component of the parasympathetic nervous system (PNS). Higher HRV indicates better autonomic regulation and stress recovery, whereas lower HRV is associated with chronic stress and mental health disorders [13]. Meditation practices, particularly mindfulness and focused breathing, improve HRV and provide an objective measure of physiological benefits [14,15]. However, the effects of static and kinetic meditation on HRV and autonomic nervous system (ANS) regulation have rarely been directly compared.\u003c/p\u003e \u003cp\u003eStudies on attention-focused static meditation have shown changes in HRV metrics, such as increased SDNN, RMSSD, and HF power, along with decreased LF power and LF/HF ratio, suggesting enhanced parasympathetic activity [16\u0026ndash;18]. A meta-analysis of 17 RCTs on Tai Chi and Yoga also found similar trends, including decreased LF power and increased HF power [18]. However, these studies, based on long-term interventions (8\u0026ndash;16 weeks), did not address changes occurring within meditation sessions. Hunt et al. (2018) further explored these distinctions by dismantling MBSR components, revealing that yoga-based interventions involving movement were associated with higher resting HRV and more adaptive vagal responses to stress [6]. This suggests that movement-based meditation promotes better stress adaptation through flexible parasympathetic responses [14]. In contrast, mindfulness without movement resulted in more stable HRV, indicating reduced stress rather than dynamic autonomic adaptation [20]. These findings underscore the need for further research on how static and kinetic meditation affect autonomic functions differently and their therapeutic implications.\u003c/p\u003e \u003cp\u003eDespite these insights, research on kinetic meditation remains scarce compared to that on static forms. Little is known about how these practices differentially affect ANS regulation. Given the distinct physiological responses observed, a direct comparison between static and kinetic meditation is essential to better understand their unique mechanisms and therapeutic potential. This study aimed to examine the impact of kinetic meditation on ANS regulation by comparing it with that of static meditation. By providing empirical evidence of the physiological differences between these meditation practices, this study provides valuable insights into the scientific foundation for meditation-based interventions.\u003c/p\u003e"},{"header":"2 Results","content":"\u003ch2\u003e2.1\u0026nbsp; \u0026nbsp; \u0026nbsp;VAS\u003c/h2\u003e\n\u003ch3\u003e2.1.1\u0026nbsp;\u0026nbsp;Depth and Focus\u003c/h3\u003e\n\u003cp\u003eThe analysis was conducted using a\u0026nbsp;two-way RM-ANOVA\u0026nbsp;with a 2 (meditation type: static vs. kinetic) \u0026times; 2 (guidance: guided vs. unguided) design. A\u0026nbsp;significant main effect of meditation type\u0026nbsp;was observed,\u0026nbsp;F(1, 34) = 6.209, p = .018, partial \u0026eta;\u0026sup2; = .154, indicating that participants experienced greater depth and focus during\u0026nbsp;kinetic meditation (mean = 6.366, standard error = .236) than during\u0026nbsp;static meditation\u0026nbsp;(mean = 5.790, standard error = .269). A\u0026nbsp;significant main effect of guidance\u0026nbsp;was also found,\u0026nbsp;F(1, 34) = 4.875, p = .034, partial \u0026eta;\u0026sup2; = .125, with participants reporting higher depth and focus during\u0026nbsp;audio-guided meditation\u0026nbsp;(mean = 6.370, standard error = .220) than during\u0026nbsp;unguided meditation\u0026nbsp;(mean = 5.786, standard error = .297).\u003c/p\u003e\n\u003cp\u003eTo further examine the differences across the four conditions, a\u0026nbsp;one-way RM-ANOVA\u0026nbsp;was conducted. The results showed a significant effect of condition on depth and focus ratings,\u0026nbsp;F(3, 102) = 4.478, p = .005, partial \u0026eta;\u0026sup2; = .116. Post hoc comparisons indicated that\u0026nbsp;guided kinetic meditation\u0026nbsp;showed significantly higher depth and focus scores than in unguided static meditation (Table 2).\u003c/p\u003e\n\u003ch3\u003e2.1.2\u0026nbsp;\u0026nbsp;Peace and Calm\u003c/h3\u003e\n\u003cp\u003eFor the peace and calm ratings, neither the\u0026nbsp;one-way nor two-way RM-ANOVA\u0026nbsp;revealed any significant differences across conditions.\u003c/p\u003e\n\u003ch3\u003e2.1.3\u0026nbsp;\u0026nbsp;Drowsiness\u003c/h3\u003e\n\u003cp\u003eThe\u0026nbsp;two-way RM-ANOVA\u0026nbsp;revealed a\u0026nbsp;significant main effect of meditation type\u0026nbsp;on drowsiness,\u0026nbsp;F(1, 34) = 14.742, p = .001, partial \u0026eta;\u0026sup2; = .288. articipants reported greater drowsiness during\u0026nbsp;static meditation\u0026nbsp;(mean = 3.890, standard error = .439) than during\u0026nbsp;kinetic meditation\u0026nbsp;(mean = 2.256, standard error = .381).\u003c/p\u003e\n\u003cp\u003eThe\u0026nbsp;one-way RM-ANOVA\u0026nbsp;conducted on drowsiness ratings showed a\u0026nbsp;significant effect of condition,\u0026nbsp;F(3, 102) = 7.170, p = .000, partial \u0026eta;\u0026sup2; = .174. Pairwise comparisons revealed that\u0026nbsp;drowsiness during unguided static meditation\u0026nbsp;was significantly higher than during both\u0026nbsp;guided kinetic meditation\u0026nbsp;(p = .020) and\u0026nbsp;unguided kinetic meditation\u0026nbsp;(p = .001) (Table 2).\u003c/p\u003e\n\u003ch2\u003e2.2\u0026nbsp; \u0026nbsp; \u0026nbsp;HRV\u003c/h2\u003e\n\u003cp\u003eDifferences in HR and HRV metrics across the resting state, guided static, unguided static, guided kinetic, and unguided kinetic meditation conditions are shown in Figure 1.\u003c/p\u003e\n\u003ch3\u003e2.2.1\u0026nbsp;\u0026nbsp;Heart Rate Analysis\u003c/h3\u003e\n\u003cp\u003eThe min HR during guided static meditation was significantly higher than that during the resting state (F(4, 128) = 3.031, p = .020, partial \u0026eta;\u0026sup2; = .087), while the max HR was significantly higher in all meditation conditions than in the resting state (F(4, 128) = 9.394, p = .000, partial \u0026eta;\u0026sup2; = .227). We also observed significant differences in average HR, (F(4, 128) = 15.431, p = .000, partial \u0026eta;\u0026sup2; = .325), where average HR during all meditation conditions was higher than that during the resting state. Additionally, the guided meditation conditions (both static and kinetic) showed a higher average HR than do their respective unguided meditation conditions.\u003c/p\u003e\n\u003ch3\u003e2.2.2\u0026nbsp;\u0026nbsp;HRV Time-domain Analysis\u003c/h3\u003e\n\u003cp\u003eRMSSD during guided static, unguided static, and guided kinetic meditation was significantly lower than during the resting state (F(4, 128) = 5.974, p = .000, partial \u0026eta;\u0026sup2; = .157). lnRMSSD also demonstrated significant differences among conditions (F(4, 128) = 6.920, p = .000, partial \u0026eta;\u0026sup2; = .178), with lnRMSSD during the resting state higher than in all other conditions. Additionally, lnRMSSD was significantly higher during unguided kinetic meditation than during guided kinetic meditation. The resting-state PNN50 was higher than was guided static and guided kinetic meditation (F(4, 84) = 5.412, p = .001, partial \u0026eta;\u0026sup2; = .205). Mean RR intervals showed significant differences (F(4, 128) = 15.250, p = .000, partial \u0026eta;\u0026sup2; = .323), with the resting state having longer mean RR intervals compared to all other conditions. However, no significant differences were observed in SDNN.\u003c/p\u003e\n\u003ch3\u003e2.2.3\u0026nbsp;\u0026nbsp;HRV Frequency-domain Analysis\u003c/h3\u003e\n\u003cp\u003eThe LF/HF ratio was significantly higher during guided and unguided kinetic meditation conditions than during the resting state (F(4, 128) = 4.082, p = .004, partial \u0026eta;\u0026sup2; = .113). HF power was significantly lower during guided static and guided kinetic meditation than during the resting state (F(4, 128) = 4.491, p = .002, partial \u0026eta;\u0026sup2; = .123). However, the TF and LF powers did not differ significantly across the conditions.\u003c/p\u003e"},{"header":"3 Discussion","content":"\u003cp\u003eThis study investigated autonomic responses during kinetic and static meditation, along with the meditators' perceived experiences. VAS analysis revealed significant differences in participants\u0026rsquo; self-reported depth and focus depending on the type of meditation and presence of guidance. Kinetic meditation led to higher levels of depth and focus than did static meditation, whereas audio-guided meditation induced greater depth and focus than did unguided meditation. These findings suggest that movement-based meditation and verbal guidance play crucial roles in enhancing meditators\u0026rsquo; engagement. Given that the participants in this study were beginners with no prior systematic meditation training, it appears that physical movements and audio guidance helped reduce boredom and facilitated a deeper focus. For novice practitioners, seated meditation often induces drowsiness and physical discomfort, whereas movement-based practices such as walking meditation or Hatha yoga minimize distractions from drowsiness or bodily discomfort, making continued practice easier [9]. This claim was supported by the VAS drowsiness analysis in this study, which showed that static meditation induced significantly more drowsiness than kinetic meditation. This can be attributed to the minimal physical activity during static meditation, which may lead to greater fatigue or sleepiness.\u003c/p\u003e \u003cp\u003e Notably, unguided static meditation resulted in the highest level of drowsiness, suggesting that the absence of verbal cues makes sustaining focus more challenging. This was further supported by the VAS depth and focus scores, where unguided static meditation received the lowest ratings, indicating that it may create an environment in which practitioners are more prone to falling into a drowsy state. Together, these findings suggest that kinetic meditation may be a more suitable approach for beginners than static meditation. However, no significant differences were observed in peace and calm measures across meditation types or guidance conditions, indicating that these factors may have less of an influence on tranquility. This suggests that all four meditation conditions promote a sense of peace and calm.\u003c/p\u003e \u003cp\u003eHeart rate and HRV were analyzed across the resting state, guided static meditation, unguided static meditation, guided kinetic meditation, and unguided kinetic meditation to examine the differences in autonomic responses. Both max and average HR were higher in all meditation conditions than in the resting state. This suggests that cognitive engagement, such as sustained attention and physical movement during kinetic meditation, may provide neurophysiological stimulation, leading to an elevated heart rate relative to rest. Notably, the average HR was significantly higher during guided meditation than during unguided meditation, while the minimum HR was significantly higher during guided static meditation than in in the resting state. These findings suggest that processing verbal instructions, integrating them cognitively, and executing the corresponding tasks may contribute to increased sympathetic nervous system (SNS) activation. This interpretation is further supported by the mean RR interval, which was shorter in all meditation conditions than in the resting state. A shorter mean RR interval, meaning reduced the time between successive heartbeats, indicates a faster and more unstable heart rate during meditation. This is often associated with increased SNS activity and reduced PNS dominance, which reflects a state of heightened physiological arousal or stress. These results align with those of a previous study, which reported that heart rate increased during meditation compared with baseline, suggesting SNS activation during meditation [21]. Although meditation is often associated with relaxation, it can also function as a mental task that requires cognitive effort and has been linked to physiological arousal [22,23]. Mental states that impose high cognitive demands influence ANS activity [24].\u003c/p\u003e \u003cp\u003eThe observed increase in heart rate and decrease in the HRV during meditation in this study may be attributed to the cognitive demands placed on participants, particularly because they were meditation novices. Prior research suggests that the physiological meditation effects vary depending on the type, level of cognitive effort required, and extent of prior training [24]. Furthermore, mental effort during meditation tends to decrease with increasing expertise over time [25]. Because this study did not include a comparison based on expertise, future research should examine the differences between novice and experienced meditators.\u003c/p\u003e \u003cp\u003eThe RMSSD and lnRMSSD were significantly lower in the guided static meditation, unguided static meditation, and guided kinetic meditation conditions than in in the resting state. This suggests an increase in SNS activation or a relative decrease in PNS activity during meditation. The required active engagement in meditation may have increased participants' mental effort, leading to heightened physiological arousal. In contrast, unguided kinetic meditation was the only condition in which RMSSD did not decrease relative to the resting state. Furthermore, lnRMSSD was higher for unguided kinetic meditation than for guided kinetic meditation. These findings may be attributed to a practice effect as unguided kinetic meditation was performed after the guided condition, potentially allowing participants to engage in meditation in a more familiar and relaxed state. Another possibility is that participants may have engaged in less physical movement in the unguided condition because of no instructional guidance. Alternatively, freedom from external demands in unguided kinetic meditation may facilitate greater parasympathetic activation [26]. However, to generalize this interpretation, this study did not collect data on participants' actual movement levels in the unguided condition to compare with guided kinetic meditation, making it difficult to generalize this interpretation. Therefore, future studies should examine the extent of physical activity under different conditions.\u003c/p\u003e \u003cp\u003eFurthermore, both guided static meditation and kinetic meditation resulted in a significant decrease in HF power and an increase in PNN50 compared to the resting state. These results suggest a reduction in parasympathetic tone, which may occur due to stress, cognitive load, or sympathetic activation [27]. Given that participants reported greater focus during guided meditation based on the VAS results, the observed decrease in HF power along with an increase in PNN50 was more likely attributable to cognitive load than stress. This finding suggests that following guided instructions during meditation imposes cognitive demands that contribute to increased sympathetic activation.\u003c/p\u003e \u003cp\u003eThis study found that the LF/HF ratio in both guided and unguided kinetic meditation was significantly higher than that in the resting state. The LF/HF ratio is a key indicator used to assess the ANS balance. A high LF/HF ratio reflects increased sympathetic or suppressed PNS activation, which are associated with stress, tension, and the dominant action of the SNS during physical activity [28]. This suggests that kinetic meditation involving movement activates the SNS.\u003c/p\u003e \u003cp\u003eIn particular, the elevated LF/HF ratio observed during kinetic meditation may be related to withdrawal of cardiac vagal control. As parasympathetic regulation decreases, the SNS becomes relatively dominant, which may activate mechanisms that increase the heart rate and cardiac output [20]. This reduction in parasympathetic control could serve as a rapid physiological adaptation to meet the demands of the situation, particularly in response to physical activity [29,30].\u003c/p\u003e \u003cp\u003eThis study has several limitations. First, the sample consisted of meditation novices, which may limit the generalizability of the findings to experienced meditators as autonomic responses could vary with expertise [25]. Future research should also examine long-term effects, including breath-rate variability (BRV), which can provide insight into short-term autonomic changes, whereas HRV is more indicative of long-term effects [31]. Additionally, because this study measured and compared the ANS responses during meditation, we were unable to identify immediate or lasting effects after meditation. Although the order of static and kinetic meditation was randomized, the sequence of guided meditation followed by unguided meditation may have influenced the results owing to potential sequence effects. Additionally, the study did not measure or control the actual levels of physical movement during unguided kinetic meditation, which may have influenced the results. Future studies should assess physical activity levels across different conditions to better understand their impact.\u003c/p\u003e \u003cp\u003e In summary, this study explored participants\u0026rsquo; autonomic responses and perceived experiences during kinetic meditation compared to static meditation with and without verbal guidance. The results indicated that depth and focus were higher in kinetic meditation than in static meditation and were higher with verbal guidance. Static meditation induced more drowsiness than kinetic meditation, with unguided static meditation causing the highest level of drowsiness. No significant difference presented in the sense of peace and calm reported by the meditators across conditions. Additionally, all meditation conditions resulted in an increased heart rate and HRV markers associated with SNS activity compared to the resting state. Specifically, an increase in SNS activity during guided meditation appears to be associated with greater cognitive effort among novice meditators, leading to heightened physiological arousal. Together, our findings provide empirical evidence that the inclusion of movement and guidance in meditation can differentially influence the ANS responses and shape how novice meditators perceive their meditation experiences. This study contributes to establishing a scientific foundation for mediation-based interventions.\u003c/p\u003e"},{"header":"4 Materials and Methods","content":"\u003ch2\u003e4.1\u0026nbsp; \u0026nbsp; \u0026nbsp;Participants\u003c/h2\u003e\n\u003cp\u003eThirty-five participants (male=15, age: 22.03\u0026plusmn;2.54) participated in the study. Participants were restricted to healthy adults in their 20s who could engage in light physical activity and had no restrictions on neurophysiological measurements. Additionally, participants had to have no systematic experience in meditation practice, physical disabilities, or mental health conditions. A within-participant experimental design was adopted to minimize individual differences related to personal meditation experience or skills. All participants completed both static and kinetic meditation sessions, with the order randomized and conducted at least 24 h apart to reduce potential carryover effects. Prior to participation, all participants provided written informed consent. This study was approved by the university\u0026rsquo;s Institutional Review Board (WKIRB-202310-HR-076), and all methods were carried out in accordance with relevant guidelines and regulations.\u003c/p\u003e\n\u003ch2\u003e4.2\u0026nbsp; \u0026nbsp; \u0026nbsp;Measures\u003c/h2\u003e\n\u003ch3\u003e4.2.1\u0026nbsp;\u0026nbsp;Visual Analog Scale (VAS)\u003c/h3\u003e\n\u003cp\u003eTo compare the meditation experiences between static and kinetic meditation as well as between audio-guided and unguided conditions, participants were asked to respond to three VAS questions at the end of each meditation session. Each participant rated their feelings on a 0\u0026ndash;10 cm line, with endpoints labeled \u0026ldquo;not at all\u0026rdquo; and \u0026ldquo;very much.\u0026rdquo; The three questions asked were: (1) the depth and focus of their meditation experience, (2) the level of inner peace and calm felt, and (3) the amount of drowsiness experienced. For analysis, the length of the mark from the left endpoint of the scale was measured using a ruler for analysis (Cline et al., 1992).\u003c/p\u003e\n\u003ch3\u003e4.2.2 HRV\u003c/h3\u003e\n\u003cp\u003eThe Polar H10 (Polar Unk, Finland) was connected via Bluetooth to the EliteHRV app (EliteHRV, Asheville, USA) installed on iPhone 14 (Apple, Inc., Cupertino, CA, USA). The Polar H10 is a wireless chest strap heart rate (HR) monitor that records HR data processed by the EliteHRV app to calculate HRV metrics. Previous research has validated the reliability of measuring HRV using the Polar H10 with the EliteHRV app, with a correlation coefficient (r) of 0.998 or higher compared to measurements using a stationary ECG device (Im and Woo, 2024). HRV was measured during a 5-min resting-state period. Separate measurements were taken during 10-min sessions of four types of meditation: audio-guided static meditation, unguided static meditation, audio-guided kinetic meditation, and unguided kinetic meditation. The Elite HRV app recorded the data, which were automatically saved to the data log after the recording was completed.\u0026nbsp;The following HRV metrics were calculated and displayed: minimum HR, maximum HR, average HR, RMSSD, SDNN, lnRMSSD, PNN50, mean RR interval, total power (TF), LF/HF ratio, LF power, and HF power. These values were coded immediately and used for analysis.\u003c/p\u003e\n\u003ch2\u003e4.3\u0026nbsp; \u0026nbsp; \u0026nbsp;Procedure\u003c/h2\u003e\n\u003cp\u003eThe participants were instructed to abstain from caffeine, alcohol, and exercise for at least 12 h prior to each session. During the first visit, participants were provided with a detailed explanation of the study and signed an informed consent form. They then wore a Polar H10 chest strap and sat comfortably in a chair, while their baseline HRV was measured for 5 min. All sessions were conducted individually in a quiet, light-controlled environment to ensure minimal external distraction.\u003c/p\u003e\n\u003cp\u003eAfter the baseline measurement, participants engaged in either static or kinetic meditation, in the order randomly determined by the researcher. If static meditation was conducted first, the participants sat in a chair and performed seated breathing meditation guided by prerecorded audio for 10 min. Immediately after completing the guided meditation, they responded to VAS. Subsequently, they remained seated and performed 10 min of unguided static meditation, after which they completed the same VAS assessments.\u003c/p\u003e\n\u003cp\u003eOn a separate day, participants returned to the laboratory for kinetic meditation. They first engaged in a 10-min session of guided kinetic meditation involving physical movements, following instructions from prerecorded audio. Immediately after the guided session, the participants completed the same VAS assessments. This was followed by a 10-min unguided kinetic meditation session, after which they again completed the VAS assessments, marking the end of the experiment.\u003c/p\u003e\n\u003cp\u003eTo minimize order effects, the sequence of static and kinetic meditation sessions was randomized across participants. However, for each meditation type, guided meditation was always conducted before unguided meditation. This approach ensured that participants who were na\u0026iuml;ve to meditation could familiarize themselves with basic meditation techniques during the guided sessions before independently attempting the unguided sessions.\u003c/p\u003e\n\u003cp\u003eHRV data recording began at the start of each meditation session and ended immediately upon completion, capturing HRV metrics for the entire 10-minute period.\u003c/p\u003e\n\u003cp\u003eThe study protocol was retrospectively registered with the Clinical Research Information Service (CRIS) associated with the WHO International Clinical Trials Registry Platform (ICTRP) on 21/03/2025 (registration number: KCT0010333).\u0026nbsp;\u003c/p\u003e\n\u003ch2\u003e4.4\u0026nbsp; \u0026nbsp; \u0026nbsp;Meditation Protocol\u003c/h2\u003e\n\u003cp\u003eThe static and kinetic meditation protocols were developed by four certified experts, including a meditation instructor, an exercise psychologist, and a yoga instructor. Both meditations were performed while seated on a chair for consistency and accessibility. Static meditation focused on breathing, whereas kinetic meditation incorporated basic seated yoga movements for beginners. Audio guides for both were recorded in Korean by the same instructor to ensure consistency in tone and delivery. The guided scripts were standardized to 430 words to maintain uniformity across sessions, tailored for participants with no prior meditation experience.\u003c/p\u003e\n\u003ch3\u003e2.4.1 Static Meditation\u0026nbsp;\u003c/h3\u003e\n\u003cp\u003eBefore the static meditation, participants received the following guidelines:\u003c/p\u003e\n\u003cp\u003e\u0026bull; Sit toward the front edge of the chair with feet shoulder-width apart and back straight.\u003cbr\u003e\u0026bull; Keep ears, shoulders, and hip joints aligned.\u003cbr\u003e\u0026bull; Relax shoulders, breathe deeply through the nose, and exhale slowly.\u003cbr\u003e\u0026bull; Observe the breath naturally without control.\u003cbr\u003e\u0026bull; Focus inwardly, minimizing attention to external sounds.\u003cbr\u003e\u0026bull; Acknowledge thoughts or emotions and gently return focus to breathing.\u003c/p\u003e\n\u003cp\u003eBefore unguided meditation, participants were instructed to follow the same breathing approach practiced during the guided session.\u003c/p\u003e\n\u003ch3\u003e2.4.2 Kinetic Meditation\u0026nbsp;\u003c/h3\u003e\n\u003cp\u003eThe guidelines for kinetic meditation included:\u003c/p\u003e\n\u003cp\u003e\u0026bull; Align ears, shoulders, and hips in a straight line.\u003cbr\u003e\u0026bull; Relax shoulders and breathe deeply, exhaling naturally.\u003cbr\u003e\u0026bull; Avoid breath-holding and move slowly, focusing on bodily sensations.\u003cbr\u003e\u0026bull; Acknowledge arising thoughts or emotions and refocus on breath and movement.\u003c/p\u003e\n\u003cp\u003eParticipants were familiarized with basic precautions before starting. Since movements were guided solely by audio, three poses (mountain, tree, warrior) were shown in pictures, and a researcher demonstrated them. These movements were beginner-friendly, emphasizing mindful alignment and breathing. The movements included in the guided kinetic meditation session are presented in Table 1.\u003c/p\u003e\n\u003cp\u003eThe kinetic meditation lasted 10 minutes, incorporating breathing and alignment during transitions. In the unguided session, participants could perform any seated movement, whether from the guided session or freely chosen, focusing on breath, sensations, and emotions.\u003c/p\u003e\n\u003ch2\u003e4.5\u0026nbsp; \u0026nbsp; \u0026nbsp;Statistical analysis\u003c/h2\u003e\n\u003cp\u003eTo examine the interaction effects of meditation type (static vs. kinetic) and guidance (guided vs. unguided), a two-way repeated-measures analysis of variance (RM-ANOVA) was conducted. Subsequently, to compare the differences in VAS scores across the four individual conditions (guided static meditation, unguided static meditation, guided kinetic meditation, and unguided kinetic meditation), a one-way RM-ANOVA was performed. To investigate differences in HRV measures (i.e., minimum HR, maximum HR, average HR, RMSSD, SDNN, lnRMSSD, PNN50, mean RR interval, TF, LF/HF ratio, LF power, and HF power) across conditions (i.e., resting-state, guided static meditation, unguided static meditation, guided kinetic meditation, and unguided kinetic meditation), a one-way RM-ANOVA was conducted, with the conditions as the independent variable and HRV metrics as the dependent variable. The effect size for all ANOVA results was calculated using an eta-squared value. Mauchly\u0026rsquo;s test of sphericity was conducted for all dependent variables, and when the assumption of sphericity was not met, the degrees of freedom for ANOVA were adjusted using the Greenhouse-Geisser correction. All statistical analyses were performed using SPSS version 29 with the significance level set at 0.05.\u003c/p\u003e"},{"header":"Declarations","content":" \u003ch2\u003eCompeting interests\u003c/h2\u003e \u003cp\u003eThe authors declare no competing interests.\u003c/p\u003e \u003ch2\u003eFunding\u003c/h2\u003e \u003cp\u003eThis work was supported by the Ministry of Education of the Republic of Korea and the National Research Foundation of Korea (NRF-2023S1A5A8077074)\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eJ.H. was responsible for conceptualization, methodology design, data analysis, software development, implementation of the experimental procedures, visualization, funding acquisition, and drafting the original manuscript. T.K. contributed to the conceptual framework, supervised the overall research process, curated the data, supported experimental implementation, and co-wrote the original manuscript. All authors reviewed and edited the manuscript and contributed to interpreting the results and finalizing the paper.\u003c/p\u003e\n\u003ch2\u003eAvailability of data\u003c/h2\u003e\n\u003cp\u003eThe datasets used and analyzed during the current study are available from the corresponding author upon reasonable request.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n \u003cli\u003e\u003cspan\u003ePolaris Market Research. \u003cem\u003eMindfulness Meditation Apps Market Share, Size, Trends, Industry Analysis Report, by Operating System (Android, iOS, Others); by Service Type (Paid-In App Purchases, Free); by Age Group (6\u0026ndash;12 Years Old, 13\u0026ndash;18 Years Old, and 19 Above); by Regions; Segment Forecast, 2020\u0026ndash;2027\u003c/em\u003e (2020).\u003c/span\u003e\u003c/li\u003e\n \u003cli\u003e\u003cspan\u003eMani, M., Kavanagh, D.J., Hides, L. \u0026amp; Stoyanov, S.R. Review and evaluation of mindfulness-based iPhone apps. \u003cem\u003eJMIR mHealth uHealth\u003c/em\u003e \u003cstrong\u003e3\u003c/strong\u003e, e82 (2015).\u003c/span\u003e\u003c/li\u003e\n \u003cli\u003e\u003cspan\u003eTorous, J. \u0026amp; Firth, J. The digital placebo effect: Mobile mental health meets clinical psychiatry. \u003cem\u003eLancet Psychiatry\u003c/em\u003e \u003cstrong\u003e3\u003c/strong\u003e, 100\u0026ndash;102 (2016).\u003c/span\u003e\u003c/li\u003e\n \u003cli\u003e\u003cspan\u003eDauden Roquet, C. \u0026amp; Sas, C. Evaluating mindfulness meditation apps. In \u003cem\u003eExtended Abstracts of the 2018 CHI Conference on Human Factors in Computing Systems\u003c/em\u003e, 1\u0026ndash;6 (ACM, New York, NY, USA, 2018).\u003c/span\u003e\u003c/li\u003e\n \u003cli\u003e\u003cspan\u003eBaminiwatta, A. \u0026amp; Solangaarachchi, I. Trends and developments in mindfulness research over 55 years: A bibliometric analysis of publications indexed in Web of Science. \u003cem\u003eMindfulness\u003c/em\u003e \u003cstrong\u003e12\u003c/strong\u003e, 2099\u0026ndash;2116 (2021).\u003c/span\u003e\u003c/li\u003e\n \u003cli\u003e\u003cspan\u003eHunt, M., Al-Braiki, F., Dailey, S., Russell, R. \u0026amp; Simon, K. Mindfulness training, yoga, or both? Dismantling the active components of a mindfulness-based stress reduction intervention. \u003cem\u003eMindfulness\u003c/em\u003e \u003cstrong\u003e9\u003c/strong\u003e, 512\u0026ndash;520 (2018).\u003c/span\u003e\u003c/li\u003e\n \u003cli\u003e\u003cspan\u003eEberth, J. \u0026amp; Sedlmeier, P. The effects of mindfulness meditation: A meta-analysis. \u003cem\u003eMindfulness\u003c/em\u003e \u003cstrong\u003e3\u003c/strong\u003e, 174\u0026ndash;189 (2012).\u003c/span\u003e\u003c/li\u003e\n \u003cli\u003e\u003cspan\u003eSparby, T. What stands in the way becomes the way: Dual and non-dual approaches to meditation hindrances in Buddhist traditions and contemplative science. \u003cem\u003eReligions\u003c/em\u003e \u003cstrong\u003e13\u003c/strong\u003e, 840 (2022).\u003c/span\u003e\u003c/li\u003e\n \u003cli\u003e\u003cspan\u003eKim, W. Differential effects of moving and unmoving meditation in meditation-based intervention programs. \u003cem\u003eKorean J. Health Psychol.\u003c/em\u003e \u003cstrong\u003e18\u003c/strong\u003e, 643\u0026ndash;667 (2013).\u003c/span\u003e\u003c/li\u003e\n \u003cli\u003e\u003cspan\u003eRose, S., Zell, E. \u0026amp; Strickhouser, J.E. The effect of meditation on health: A metasynthesis of randomized controlled trials. \u003cem\u003eMindfulness\u003c/em\u003e \u003cstrong\u003e11\u003c/strong\u003e, 507\u0026ndash;516 (2020).\u003c/span\u003e\u003c/li\u003e\n \u003cli\u003e\u003cspan\u003eGrossman, P., Niemann, L., Schmidt, S. \u0026amp; Walach, H. Mindfulness-based stress reduction and health benefits: A meta-analysis. \u003cem\u003eJ. Psychosom. Res.\u003c/em\u003e \u003cstrong\u003e57\u003c/strong\u003e, 35\u0026ndash;43 (2004).\u003c/span\u003e\u003c/li\u003e\n \u003cli\u003e\u003cspan\u003eMatko, K. \u0026amp; Sedlmeier, P. What is meditation? Proposing an empirically derived classification system. \u003cem\u003eFront. Psychol.\u003c/em\u003e \u003cstrong\u003e10\u003c/strong\u003e, 2276 (2019).\u003c/span\u003e\u003c/li\u003e\n \u003cli\u003e\u003cspan\u003eMcCraty, R. \u0026amp; Shaffer, F. Heart rate variability: New perspectives on physiological mechanisms, assessment of self-regulatory capacity, and health risk. \u003cem\u003eGlob. Adv. Health Med.\u003c/em\u003e \u003cstrong\u003e4\u003c/strong\u003e, 46\u0026ndash;61 (2015).\u003c/span\u003e\u003c/li\u003e\n \u003cli\u003e\u003cspan\u003eChristodoulou, G., Salami, N. \u0026amp; Black, D.S. The utility of heart rate variability in mindfulness research. \u003cem\u003eMindfulness\u003c/em\u003e \u003cstrong\u003e11\u003c/strong\u003e, 554\u0026ndash;570 (2020).\u003c/span\u003e\u003c/li\u003e\n \u003cli\u003e\u003cspan\u003eKrygier, J.R., Heathers, J.A., Shahrestani, S., Abbott, M., Gross, J.J. \u0026amp; Kemp, A.H. Mindfulness meditation, well-being, and heart rate variability: a preliminary investigation into the impact of intensive Vipassana meditation. \u003cem\u003eInt. J. Psychophysiol.\u003c/em\u003e \u003cstrong\u003e89\u003c/strong\u003e, 305\u0026ndash;313 (2013).\u003c/span\u003e\u003c/li\u003e\n \u003cli\u003e\u003cspan\u003eNesvold, A. \u003cem\u003eet al.\u003c/em\u003e Increased heart rate variability during nondirective meditation. \u003cem\u003eEur. J. Prev. Cardiol.\u003c/em\u003e \u003cstrong\u003e19\u003c/strong\u003e, 773\u0026ndash;780 (2012).\u003c/span\u003e\u003c/li\u003e\n \u003cli\u003e\u003cspan\u003eKrygier, J.R., Heathers, J.A., Shahrestani, S., Abbott, M., Gross, J.J. \u0026amp; Kemp, A.H. Mindfulness meditation, well-being, and heart rate variability: a preliminary investigation into the impact of intensive Vipassana meditation. \u003cem\u003eInt. J. Psychophysiol.\u003c/em\u003e \u003cstrong\u003e89\u003c/strong\u003e, 305\u0026ndash;313 (2013).\u003c/span\u003e\u003c/li\u003e\n \u003cli\u003e\u003cspan\u003eArredondo, M. \u003cem\u003eet al.\u003c/em\u003e A mindfulness training program based on brief practices (M-PBI) to reduce stress in the workplace: A randomised controlled pilot study. \u003cem\u003eInt. J. Occup. Environ. Health\u003c/em\u003e \u003cstrong\u003e23\u003c/strong\u003e, 40\u0026ndash;51 (2017).\u003c/span\u003e\u003c/li\u003e\n \u003cli\u003e\u003cspan\u003eZou, L. \u003cem\u003eet al.\u003c/em\u003e Effects of Mind\u0026ndash;Body Exercises (Tai Chi/Yoga) on Heart Rate Variability Parameters and Perceived Stress: A Systematic Review with Meta-Analysis of Randomized Controlled Trials. \u003cem\u003eJ. Clin. Med.\u003c/em\u003e \u003cstrong\u003e7\u003c/strong\u003e, 404 (2018).\u003c/span\u003e\u003c/li\u003e\n \u003cli\u003e\u003cspan\u003eLaborde, S., Mosley, E. \u0026amp; Mertgen, A. Vagal Tank Theory: The Three Rs of Cardiac Vagal Control Functioning \u0026ndash; Resting, Reactivity, and Recovery. \u003cem\u003eFront. Neurosci.\u003c/em\u003e \u003cstrong\u003e12\u003c/strong\u003e, 458 (2018).\u003c/span\u003e\u003c/li\u003e\n \u003cli\u003e\u003cspan\u003eLutz, A., Greischar, L.L., Perlman, D.M. \u0026amp; Davidson, R.J. BOLD signal in insula is differentially related to cardiac function during compassion meditation in experts vs. novices. \u003cem\u003eNeuroimage\u003c/em\u003e \u003cstrong\u003e47\u003c/strong\u003e, 1038\u0026ndash;1046 (2009).\u003c/span\u003e\u003c/li\u003e\n \u003cli\u003e\u003cspan\u003eHansen, A.L., Johnsen, B.H. \u0026amp; Thayer, J.F. Vagal influence on working memory and attention. \u003cem\u003eInt. J. Psychophysiol.\u003c/em\u003e \u003cstrong\u003e48\u003c/strong\u003e, 263\u0026ndash;274 (2003).\u003c/span\u003e\u003c/li\u003e\n \u003cli\u003e\u003cspan\u003eLuft, C.D.B., Takase, E. \u0026amp; Darby, D. Heart rate variability and cognitive function: Effects of physical effort. \u003cem\u003eBiol. Psychol.\u003c/em\u003e \u003cstrong\u003e82\u003c/strong\u003e, 164\u0026ndash;168 (2009).\u003c/span\u003e\u003c/li\u003e\n \u003cli\u003e\u003cspan\u003eLumma, A.L., Kok, B.E. \u0026amp; Singer, T. Is meditation always relaxing? Investigating heart rate, heart rate variability, experienced effort and likeability during training of three types of meditation. \u003cem\u003eInt. J. Psychophysiol.\u003c/em\u003e \u003cstrong\u003e97\u003c/strong\u003e, 38\u0026ndash;45 (2015).\u003c/span\u003e\u003c/li\u003e\n \u003cli\u003e\u003cspan\u003eTang, Y.-Y., Rothbart, M.K. \u0026amp; Posner, M.I. Neural correlates of establishing, maintaining, and switching brain states. \u003cem\u003eTrends Cogn. Sci.\u003c/em\u003e \u003cstrong\u003e16\u003c/strong\u003e, 330\u0026ndash;337 (2012).\u003c/span\u003e\u003c/li\u003e\n \u003cli\u003e\u003cspan\u003eMizuno, K. \u003cem\u003eet al.\u003c/em\u003e Mental fatigue caused by prolonged cognitive load associated with sympathetic hyperactivity. \u003cem\u003eBehav. Brain Funct.\u003c/em\u003e \u003cstrong\u003e7\u003c/strong\u003e, 17 (2011).\u003c/span\u003e\u003c/li\u003e\n \u003cli\u003e\u003cspan\u003eShaffer, F. \u0026amp; Ginsberg, J.P. An overview of heart rate variability metrics and norms. \u003cem\u003eFront. Public Health\u003c/em\u003e \u003cstrong\u003e5\u003c/strong\u003e, 258 (2017).\u003c/span\u003e\u003c/li\u003e\n \u003cli\u003e\u003cspan\u003eBillman, G.E. The LF/HF ratio does not accurately measure cardiac sympatho-vagal balance. \u003cem\u003eFront. Physiol.\u003c/em\u003e \u003cstrong\u003e4\u003c/strong\u003e, 26 (2013).\u003c/span\u003e\u003c/li\u003e\n \u003cli\u003e\u003cspan\u003eFu, Q. \u0026amp; Levine, B.D. Exercise and the autonomic nervous system. \u003cem\u003eHandb. Clin. Neurol.\u003c/em\u003e \u003cstrong\u003e117\u003c/strong\u003e, 147\u0026ndash;160 (2013).\u003c/span\u003e\u003c/li\u003e\n \u003cli\u003e\u003cspan\u003eFisher, J.P. Autonomic control of the heart during exercise in humans: role of skeletal muscle afferents. \u003cem\u003eExp. Physiol.\u003c/em\u003e \u003cstrong\u003e99\u003c/strong\u003e, 300\u0026ndash;305 (2014).\u003c/span\u003e\u003c/li\u003e\n \u003cli\u003e\u003cspan\u003eSoni, R. \u0026amp; Muniyandi, M. Breath rate variability: A novel measure to study the meditation effects. \u003cem\u003eInt. J. Yoga\u003c/em\u003e \u003cstrong\u003e12\u003c/strong\u003e, 45\u0026ndash;54 (2019).\u003c/span\u003e\u003c/li\u003e\n \u003cli\u003e\u003cspan\u003eCline, M.E., Herman, J., Shaw, E.R. \u0026amp; Morton, R.D. Standardization of the visual analogue scale. \u003cem\u003eNurs. Res.\u003c/em\u003e \u003cstrong\u003e41\u003c/strong\u003e, 378\u0026ndash;380 (1992).\u003c/span\u003e\u003c/li\u003e\n \u003cli\u003e\u003cspan\u003eIm, C. \u0026amp; Woo, M. Evaluation of the suitability of digital devices for measuring heart rate variability: A comparative analysis with ECG. \u003cem\u003eJ. Sport Leis. Stud.\u003c/em\u003e \u003cstrong\u003e98\u003c/strong\u003e, 325\u0026ndash;336 (2024).\u003c/span\u003e\u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Tables","content":"\u003cp\u003eTable 1. Movements included in the kinetic meditation\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"618\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 68.6591%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMovement\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 31.3409%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTime\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 68.6591%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMountain Pose\u003c/strong\u003e\u003c/p\u003e\n \u003cul\u003e\n \u003cli\u003espread and raise the arms up, parallel above the head, then lower them back to the sides.\u003c/li\u003e\n \u003c/ul\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 31.3409%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eSlowly repeat for 1 min\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 68.6591%;\"\u003e\n \u003cul type=\"disc\"\u003e\n \u003cli\u003eGently open and close the fists.\u003c/li\u003e\n \u003c/ul\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 31.3409%;\"\u003e\n \u003cp\u003eSlowly repeat for 30 sec\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 68.6591%;\"\u003e\n \u003cul type=\"disc\"\u003e\n \u003cli\u003eRotate the wrists clockwise and counterclockwise.\u003c/li\u003e\n \u003c/ul\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 31.3409%;\"\u003e\n \u003cp\u003eSlowly repeat for 30 sec\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 68.6591%;\"\u003e\n \u003cul type=\"disc\"\u003e\n \u003cli\u003eAlternately straighten one leg at a time and lift the foot off the ground.\u003c/li\u003e\n \u003c/ul\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 31.3409%;\"\u003e\n \u003cp\u003eSlowly repeat for 1 min\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 68.6591%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTree Pose\u003c/strong\u003e\u003c/p\u003e\n \u003cul type=\"disc\"\u003e\n \u003cli\u003eLift one foot and place it on the opposite thigh, bringing the hands together in front of the chest.\u003c/li\u003e\n \u003c/ul\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 31.3409%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eHold for 30 sec\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 68.6591%;\"\u003e\n \u003cul type=\"disc\"\u003e\n \u003cli\u003eExtend the arms straight, relax the shoulders, and hold the pose.\u003c/li\u003e\n \u003c/ul\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 31.3409%;\"\u003e\n \u003cp\u003eHold for 20 sec\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 68.6591%;\"\u003e\n \u003cul type=\"disc\"\u003e\n \u003cli\u003eSwitch legs and repeat the same pose.\u003c/li\u003e\n \u003c/ul\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 31.3409%;\"\u003e\n \u003cp\u003eHold for 30 + 20 sec\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 68.6591%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eWarrior Pose\u003c/strong\u003e\u003c/p\u003e\n \u003cul\u003e\n \u003cli\u003eStretch the left leg out to the side, keeping the hands on the hips.\u003c/li\u003e\n \u003c/ul\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 31.3409%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eHold for 20 sec\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 68.6591%;\"\u003e\n \u003cul type=\"disc\"\u003e\n \u003cli\u003eExtend the arms out to the sides and gaze beyond the right hand.\u003c/li\u003e\n \u003c/ul\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 31.3409%;\"\u003e\n \u003cp\u003eHold for 30 sec\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 68.6591%;\"\u003e\n \u003cul type=\"disc\"\u003e\n \u003cli\u003eSwitch sides and repeat the same pose.\u003c/li\u003e\n \u003c/ul\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 31.3409%;\"\u003e\n \u003cp\u003eHold for 20 + 30sec\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTable 2. Mean and standard deviation of VAS scores reported across four conditions\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"600\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 125px;\"\u003e\n \u003cp\u003eVAS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 238px;\"\u003e\n \u003cp\u003eStatic Meditation\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 238px;\"\u003e\n \u003cp\u003eKinetic Meditation\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 119px;\"\u003e\n \u003cp\u003eGuided\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 119px;\"\u003e\n \u003cp\u003eUnguided\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 119px;\"\u003e\n \u003cp\u003eGuided\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 119px;\"\u003e\n \u003cp\u003eUnguided\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 125px;\"\u003e\n \u003cp\u003eDepth and focus\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 119px;\"\u003e\n \u003cp\u003e6.01\u0026plusmn;1.70\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 119px;\"\u003e\n \u003cp\u003e5.57\u0026plusmn;1.85\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 119px;\"\u003e\n \u003cp\u003e6.73\u0026plusmn;1.39\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 119px;\"\u003e\n \u003cp\u003e6.00\u0026plusmn;2.07\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 125px;\"\u003e\n \u003cp\u003ePeace and calm\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 119px;\"\u003e\n \u003cp\u003e6.61\u0026plusmn;1.71\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 119px;\"\u003e\n \u003cp\u003e5.99\u0026plusmn;1.79\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 119px;\"\u003e\n \u003cp\u003e6.53\u0026plusmn;1.58\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 119px;\"\u003e\n \u003cp\u003e6.19\u0026plusmn;2.00\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 125px;\"\u003e\n \u003cp\u003eDrowsiness\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 119px;\"\u003e\n \u003cp\u003e3.66\u0026plusmn;3.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 119px;\"\u003e\n \u003cp\u003e4.12\u0026plusmn;3.12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 119px;\"\u003e\n \u003cp\u003e2.31\u0026plusmn;2.46\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 119px;\"\u003e\n \u003cp\u003e2.21\u0026plusmn;2.36\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"static meditation, kinetic meditation, heart rate variability, autonomic nervous system, sympathetic nervous system","lastPublishedDoi":"10.21203/rs.3.rs-6389936/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6389936/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eThis study explored the autonomic nervous system responses and perceived experiences of novice meditators during kinetic and static meditation. Thirty-five participants completed both meditation types in randomized order. Each 20-minute session included 10 minutes of guided and 10 minutes of unguided meditation. Heart rate variability (HRV) was recorded using the Polar H10 and EliteHRV apps. A visual analog scale (VAS) assessed depth and focus, peace and calm, and drowsiness. Results indicated that depth and focus were significantly higher in kinetic than in static meditation and were also higher when guidance was provided. Static meditation induced greater drowsiness than did kinetic meditation, particularly in the unguided condition. All meditation conditions increased the heart rate (HR) compared to rest, with guided meditation showing a significantly higher heart rate than unguided meditation. The mean RR intervals were shorter under all meditation conditions than at rest. RMSSD and lnRMSSD were significantly lower during guided and unguided static meditation and guided kinetic meditation than at rest. Both guided static and kinetic meditation reduced high frequency (HF) power and increased the PNN50. Increased sympathetic nervous system activity during guided meditation suggests a higher cognitive effort among novice meditators, leading to heightened physiological arousal. These findings highlight how movement and guidance influence autonomic responses and meditation experiences, thereby contributing to the scientific foundation of meditation-based interventions.\u003c/p\u003e","manuscriptTitle":"How Static and Kinetic Meditation, with or without Guidance, Affect Autonomic Nervous System Activity in Novice Meditators","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-05-22 10:49:55","doi":"10.21203/rs.3.rs-6389936/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"b708ccc7-f0c3-4c81-9b5a-b2be250dd725","owner":[],"postedDate":"May 22nd, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":48739166,"name":"Biological sciences/Physiology"},{"id":48739167,"name":"Biological sciences/Psychology"},{"id":48739168,"name":"Health sciences/Biomarkers"},{"id":48739169,"name":"Health sciences/Health care"}],"tags":[],"updatedAt":"2025-07-14T10:23:51+00:00","versionOfRecord":[],"versionCreatedAt":"2025-05-22 10:49:55","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-6389936","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6389936","identity":"rs-6389936","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}