Robotic-resisted Exercise for Health Promotion in Younger Adults
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Abstract Introduction Physical inactivity and sedentary behavior both increase the risk of chronic disease and mortality. Regular participation in physical activity and reducing sedentary behavior play important roles in maintaining physical health and disease prevention. The purpose of this study was to investigate the effect of a wearable hip exoskeleton, Bot Fit, on muscle strength, muscle effort, and the kinematics of the pelvis during walking in younger adults. Methods We designed three parallel experimental conditions and randomly assigned participants to one of three groups: those assigned to exercise using an interval program of Bot Fit (interval group), those who used a power program of Bot Fit (power group), and a control group who exercised without Bot Fit. A total of 45 young adults participated in 18 exercise-intervention sessions over six weeks, and all participants were assessed at two time points: before and after the 18 exercise sessions. Each assessment evaluated muscle strength, muscle effort, and the kinematics of the pelvis during walking. In addition, the number of steps, distance, energy expenditure, and heart rate for 30 min during the exercise sessions were recorded. Results A significant increase in the maximum voluntary contraction (MVC) of the right biceps femoris (BF) was evident in the interval group while significant changes in the MVC of the bilateral BF were seen in the power group showed after Bot Fit exercise. A significant decrease of muscle effort in right BF in the interval group and right lumbar erector spinae and bilateral BF in the power group were also observed. In addition, the symmetry index of pelvic tilt significantly improved in the interval group, and greater exercise volume and intensity in both the interval and power groups compared with the control group were confirmed as measured by the number of steps, distance, energy expenditure, and heart rate. Conclusion Results of this study indicate a beneficial effect of the Bot Fit on muscle strength, walking efficiency, and pelvic movement symmetry in younger adults. Personalized exercise programs using different exercise protocol with the Bot Fit may therefore improve the physical health and gait symmetry of younger adults.
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Regular participation in physical activity and reducing sedentary behavior play important roles in maintaining physical health and disease prevention. The purpose of this study was to investigate the effect of a wearable hip exoskeleton, Bot Fit, on muscle strength, muscle effort, and the kinematics of the pelvis during walking in younger adults. Methods We designed three parallel experimental conditions and randomly assigned participants to one of three groups: those assigned to exercise using an interval program of Bot Fit (interval group), those who used a power program of Bot Fit (power group), and a control group who exercised without Bot Fit. A total of 45 young adults participated in 18 exercise-intervention sessions over six weeks, and all participants were assessed at two time points: before and after the 18 exercise sessions. Each assessment evaluated muscle strength, muscle effort, and the kinematics of the pelvis during walking. In addition, the number of steps, distance, energy expenditure, and heart rate for 30 min during the exercise sessions were recorded. Results A significant increase in the maximum voluntary contraction (MVC) of the right biceps femoris (BF) was evident in the interval group while significant changes in the MVC of the bilateral BF were seen in the power group showed after Bot Fit exercise. A significant decrease of muscle effort in right BF in the interval group and right lumbar erector spinae and bilateral BF in the power group were also observed. In addition, the symmetry index of pelvic tilt significantly improved in the interval group, and greater exercise volume and intensity in both the interval and power groups compared with the control group were confirmed as measured by the number of steps, distance, energy expenditure, and heart rate. Conclusion Results of this study indicate a beneficial effect of the Bot Fit on muscle strength, walking efficiency, and pelvic movement symmetry in younger adults. Personalized exercise programs using different exercise protocol with the Bot Fit may therefore improve the physical health and gait symmetry of younger adults. aerobic exercise muscle-strengthening exercise hip exoskeleton muscle strength pelvic symmetry Figures Figure 1 Figure 2 Figure 3 Figure 4 Introduction Low levels of physical activity and sedentary behavior (time spent sitting, as distinct from lack of physical activity) both increase the risk of chronic disease and mortality ( 1 ). Worldwide, one of five adults are physically inactive, and sedentary lifestyles are spreading in popularity ( 2 ). Recent updates to physical activity guidelines highlight the importance of reducing sedentary time ( 3 ). Regular participation in physical activity and reducing sedentary behavior play important roles in physical health and disease prevention ( 4 ). Current global recommendations state that adults aged 18–64 years should engage in at least 150 min of moderate-intensity aerobic physical activity, or at least 75 min of vigorous-intensity aerobic physical activity, or an equivalent combination of both a week, as well as muscle-strengthening activities involving major muscle groups two or more days a week ( 5 ). Although many health organizations, including the World Health Organization (WHO), emphasize the importance of physical activity, the number of individuals who currently do not meet the recommendations for physical activity continues to grow worldwide. Recent global estimates show that one in four (27.5%) adults ( 6 ) and more than three-quarters (81%) of adolescents ( 7 ) do not meet the aerobic exercise provisions of the 2010 Global Recommendations on Physical Activity for Health ( 8 ). Research suggests that regular aerobic exercise can prevent weight gain and improve physical fitness, cardiorespiratory health, executive functioning, and brain health, even in healthy populations ( 9 – 12 ). Additionally, strong clinical evidence and emerging epidemiological data show that muscle-strengthening exercise is independently associated with multiple health outcomes, including a reduced risk of all-cause mortality and the incidence of diabetes and enhanced cardiometabolic musculoskeletal and mental health ( 13 – 17 ). However, muscle-strengthening exercise have been overlooked in public health approaches to chronic-disease prevention despite numerous independent health benefits compared with the attention devoted to aerobic physical activity. Moreover, recent health surveillance data from several countries show that only 10–30% of adults meet guidelines for muscle-strengthening exercise, a far lower proportion than those meeting aerobic physical activity guidelines (approximately 50%) ( 18 , 19 ). Physical activity recommendations in public health campaigns have focused on promoting moderate-to-vigorous-intensity exercises since the 1970s. However, over the past decade, the value of muscle-strengthening exercise has been recognized, with the combination of muscle- strengthening exercise and aerobic physical activity being a recent addition to physical activity guidelines ( 20 ). Recent epidemiological studies suggest that, compared with engaging in either moderate-to-vigorous-intensity aerobic physical activity or muscle-strengthening exercise alone, a combination of both has more favorable effects on cardiometabolic biomarkers, lean muscle mass, and mental health ( 21 – 23 ). Moreover, concurrent exercise, an integrative exercise modality that combines aerobic physical activity with muscle-strengthening exercise, is a time-efficient strategy that fits into modern busy lifestyles and provide the benefits of both interventions ( 24 , 25 ). Resistance training during aerobic physical activity, such as walking with weights, is well recognized as a method of increasing metabolic cost while improving muscle strength, overground walking performance, and endurance in healthy as well as neurologically impaired individuals ( 26 – 29 ). A few studies have used weights attached to a subject’s waist and connected to a pulley system to examine the efficacy of resistance training while walking on a treadmill ( 27 , 28 , 30 ). Other studies have added weights to subject’s limb segments as they walk ( 31 ) or practice walking in water tanks ( 32 ). However, conventional training is often performed using additional loads such as resistance bands, weighted cuffs, or a backpack on the body, all of which tend to be bulky and less stable (i.e., large resistive forces are only possible with excessively large weights). Moreover, these methods typically vary the task intensity through progressive schemes, such as increasing band stiffness or adding higher weights over time ( 26 , 31 , 33 ). Wearable robotic systems, particularly those that provide resistance targeting specific muscle groups and functions, have emerged as potential tools to more effectively target the appropriate timing of the activity of specific muscle groups in a functional context ( 34 ). In this study, we used a wearable robotic hip exoskeleton, the Bot Fit, which can produce resistive torque during walking, to investigate the effects of Bot Fit exercise programs. In our previous studies, we demonstrated the effects of Bot Fit–resisted exercise in older adults and stroke patients ( 35 , 36 ). The purpose of this study was to investigate the effects of Bot Fit exercise on muscle strength, muscle effort, and kinematics of the pelvis during walking in younger adults. Methods Study design and participants This study used a single-blinded (evaluator), randomized, controlled, three-group, parallel design. The characteristics of the 45 participants are shown in Table 1 . Based on their histories and functional assessments, we excluded individuals with a history of neurological and musculoskeletal disorders that affect walking capacity, efficiency, and endurance. Eligible subjects were healthy and between 19 and 65 years of age without any history of central nervous system disease. Study procedures were approved by the ethics committee of the Sungkyunkwan University Institutional Review Board (approval number: 2023-03-005) and registered with ClinicalTrials.gov (NCT05862077). Written informed consent was obtained from all participants before they entered the study, and all methods were carried out in accordance with the approved study protocol. Table 1 Baseline characteristics of participants (N = 45) Characteristics Control Interval Power χ 2 /F P Age, years 38.47 (4.82) 36.07 (2.46) 37.40 (5.79) 1.035 0.364 Sex (male/female) 14/1 10/5 11/4 3.343 0.188 Height, cm 174.30 (6.94) 172.03 (8.80) 171.53 (9.10) 0.469 0.629 Weight, kg 77.41 (11.13) 70.99 (13.99) 76.53 (13.09) 1.111 0.339 Body mass index, kg/m 2 25.41 (2.76) 23.78 (3.12) 25.87 (2.94) 2.093 0.136 Data are expressed as mean (standard deviation). Exercise intervention All subjects in the interval and power groups performed community-mobility routines (walking in the Samsung Digital City, including level walking, slope and stair walking, and crossing the cross walk) for 30 mins with a Bot Fit while the control group did the same without a Bot Fit. The interval group exercised using the interval exercise program, which repeats rapid walking in resistance mode and slow walking in assistance mode with Bot Fit, and the power group exercised using the power exercise program, which repeats rapid walking in resistance mode and rapid walking in assistance mode with Bot Fit. Wearable hip-assist robot, Bot Fit The Bot Fit, which was developed at Samsung Electronics Co., Ltd. (Suwon, Republic of Korea), is a wearable hip-type robot designed to promote health in younger adults. The device is fastened around the wearer’s waist and thighs to assist or resist hip-joint flexion and extension. Torque assistance and resistance are transmitted to the user’s thighs through an exoskeletal frame (Fig. 1 ). Users can operate the device and change the exercise program settings using an application on a mobile phone and smart watch. Assessment tools and data collection Participants were evaluated at two time points: before (pre) and after (post) 18 exercise-intervention sessions. Each assessment evaluated muscle strength, muscle effort, and the kinematics of the pelvis during walking. In addition, the number of steps, distance, energy expenditure, and heart rate (HR) for each 30-min exercise session were recorded. To measure surface electromyography (sEMG) signals (Noraxon USA Inc., Scottsdale, AZ, USA), bipolar surface electrodes (Ag/AgCl) were positioned on the right rectus abdominis (RA) and lumbar erector spinae (LES) and the bilateral rectus femoris (RF) and biceps femoris (BF) of subjects following guidance by the Surface ElectroMyoGraphy for Non-Invasive Assessment of Muscles (SENIAM) project for reliable sensor placement ( 37 ). In addition, footswitches (Model 500 DTS FootSwitch; Noraxon USA Inc.) were placed on the bilateral toe and heel to record the timing of the stance and swing gait phases while walking. Before placing sEMG sensors, subjects’ skin was shaved, abraded, and cleaned with alcohol to reduce surface impedance. We defined muscle effort as the percentage of maximum voluntary contraction (% MVC) averaged across all participants. The MVC test is a normalizing method proposed by the SENIAM project and kinesiology guidelines and is the most widely used normalization method ( 38 ). To normalize the sEMG signal amplitude, three 5-s maximal muscle contraction measurement trials were performed with each muscle to determine each participant’s MVC. To reduce movement artifacts, a sampling frequency of 1,000 Hz was used, and raw sEMG signals were bandpass filtered between 10 and 350 Hz and full-wave rectified with Noraxon software (MyoResearch XP Master Edition). The root mean squared values of the signals were calculated using a sliding 100-ms window. The data were passed through a sixth-order Butterworth low-pass filter with a 6-Hz cutoff to create a linear envelope and normalized to the MVC data obtained prior to the tasks. The average normalized sEMG activity was processed within the selected phases of the gait cycle using MATLAB software (MathWorks, Inc., Natick, MA, USA) ( 39 ). Individual gait cycles were determined using footswitch data, with each stride considered the period between successive heel strikes by the same leg. The sEMG patterns for each stride were time-normalized and expressed as a percentage of the total gait cycle (0–99%). The three-dimensional kinematics of the pelvis (anterior-posterior tilt, up-down obliquity, and intra-extra rotation) and pelvic symmetry index (SI) were measured using a wireless G-Walk wearable sensor (BTS Bioengineering S.p.A., Milan, Itay), which consists of a triaxial accelerometer, a magnetic sensor, and a triaxial gyroscope. The G-Walk sensor was placed on the subject’s waist using a semi-elastic belt covering the L4-L5 intervertebral space to acquire the acceleration values for the three anatomical axes (antero-posterior, medio-lateral and vertebral). Subjects were asked to walk 10 m in one direction and then turn around and walk 10 m back at a self-selected speed, as naturally as possible. The collected data, transmitted to a personal computer via Bluetooth and processed with dedicated BTS G-Walk software, allowed us to obtain a set of gait parameters from which the kinematics of the pelvis (degree of tilt, obliquity, and rotation) and SI (%) could be analyzed. SI quantifies the similarity of the profiles of the right and left curves. If the two curves overlap perfectly, the index score is 100, meaning that the two curves have the same value frame by frame. The pelvis position in three planes comprises the pelvic tilt in the sagittal plain, pelvic obliquity in the coronal plane, and pelvic rotation in the transverse plane. For pelvic tilt, SI values higher than 40 can be considered normal. For the pelvic obliquity and rotation angles, a normal SI value is 80–100 (according to guidelines supplied by the manufacturer, BTS Bioengineering S.p.A., Milan, Italy). The BTS G-Walk device uses a mathematical correlation function applied to the two curves: symmetric index = (corr + 1) × 100/2, where corr is the Pearson correlation coefficient between the mean left and right normalized anteroposterior acceleration signals (according to the manufacturer’s guidelines). The number of steps, distance, energy expenditure, and average HR during 30 min of exercise were measured using a Samsung Galaxy Active 2 smart watch linked to a mobile phone Bot Fit application. Statistical analyses Statistical analyses were performed using SPSS version 22.0 (IBM, Armonk, NY, USA), with a significance level of 0.05. Descriptive statistics are expressed as means and standard deviation. After examining the distribution of the data for normality, we chose parametric tests for MVC and pelvic movement and non-parametric tests for muscle effort (% MVC). One-way analysis of variance (ANOVA) for continuous variables and chi-square tests for categorical variables were used to compare participants’ baseline characteristics. To compare the outcome measures before and after exercise in each group, paired t-tests and Wilcoxon signed-rank tests were used. One-way ANOVA and Kruskal–Wallis tests were used to determine statistically significant differences among groups. In addition, repeated-measures ANOVA was used to examine the main effects of exercise over time, including groups and time points. Post hoc tests were used to identify differences among the group means, and the significance levels of the tests were adjusted using Bonferroni corrections. Results Effects of Bot Fit exercise on muscle strength and muscle effort Table 2 and Fig. 2 present the specific values for MVC (µV) and muscle effort (% MVC) at the respective pre– and post–time points. Significant improvements in the MVC of the left BF were seen in the interval group while the power group showed significant changes in the MVC of the bilateral BF after Bot Fit exercise ( P < 0.05). However, no significant changes were evident in the control group. Muscle effort during the total gait cycle (100%) decreased significantly in the right BF in the interval group and in the right LES and bilateral BF in the power group ( P < 0.05) after Bot Fit exercise. In contrast, the control group showed no significant muscle effort decreases. Significant group × time interactions were also found in muscle effort in the right LES and bilateral BF, and the interval and power groups experienced greater changes compared with the control group ( P < 0.05). Table 2 Effects of Bot Fit exercise on muscle strength (N = 45) MVC, µV Control Interval Power Between-group Pre Post Pre Post Pre Post F P Rt. RA 153.40 (82.69) 149.47 (76.70) 134.01 (63.46) 136.37 (75.17) 118.49 (46.03) 128.37 (53.81) 0.326 0.724 Rt. LES 190.11 (111.68) 184.69 (123.74) 161.51 (80.59) 161.62 (76.25) 151.45 (76.69) 164.23 (73.79) 0.364 0.697 Rt. RF 214.05 (79.65) 216.85 (75.37) 168.62 (57.10) 176.39 (70.18) 217.10 (80.57) 232.36 (87.35) 0.176 0.840 Lt. RF 197.05 (78.26) 198.64 (63.98) 191.64 (63.65) 199.08 (91.27) 204.77 (78.67) 217.25 (94.99) 0.108 0.898 Rt. BF 240.96 (112.56) 251.35 (124.90) 205.09 (79.35) 245.28 (126.31) 209.25 (99.41) 250.44 (102.92) * 0.776 0.468 Lt. BF 223.40 (94.62) 242.97 (114.18) 195.47 (91.37) 236.00 (96.07) * 183.29 (75.20) 225.50 (87.63) * 0.728 0.490 Data are expressed as mean (standard deviation). * Significant change compared with Pre ( P < 0.05). MVC: maximum voluntary contraction, RA: rectus abdominis, LES: lumbar extensor spinae, RF: rectus femoris, BF: biceps femoris. Effects of Bot Fit exercise on kinematics of the pelvis Specific values for pelvic SI and kinematics of the pelvis are presented in Table 3 and Fig. 3 . The SI of pelvic tilt tended to increase in post– compared to pre–time points in the interval and power groups (by 23.80% and 23.04%, respectively), but the increase was statistically significant different only in the interval group ( P < 0.05). Table 3 Effects of Bot Fit exercise on kinematics of the pelvis (N = 45) Control Interval Power Between-group Pre Post Pre Post Pre Post F P Tilt 60.77 (17.17) 54.53 (20.23) 53.73 (28.68) 71.89 (21.07) * 60.19 (27.56) 74.06 (15.48) 2.659 0.082 Obliquity 97.41 (1.80) 98.02 (0.83) 98.37 (0.96) 98.46 (1.05) 98.39 (0.79) 98.63 (0.98) 0.364 0.697 Rotation 98.41 (1.09) 98.65 (0.88) 98.52 (0.59) 98.49 (0.93) 96.57 (6.85) 98.66 (0.79) 1.235 0.301 Data are expressed as mean (standard deviation). * Significant change compared with Pre ( P < 0.05). Number of steps, distance, energy expenditure, and heart rate during exercise Table 4 presents values for the number of steps, distance, energy expenditure, and average HR during exercise in each group. The number of steps and distance were significantly higher in the power group than in the control and interval groups ( P < 0.05). Energy expenditure was significantly higher in the power group than in the interval and control groups, and the interval group power expenditure was also significantly higher than that of the control group ( P < 0.05): by 24.30% in interval group and 44.38% in the power group compared with the control group. The maximum heart rate (HR max ) averages predicted by the [207 − 0.7 × age] Eq. (40) were 180.1 in the control group, 181.8 in the interval group, and 180.8 in the power group. The ranges in moderate exercise intensity (64–76% of HR max ) were from 115.3 to 136.9 in control group, 116.3 to 138.1 in the interval group, and 115.7 to 137.4 in the power group. The average HR during exercise was significantly higher in the power group than in the interval and control groups, and it was also significantly higher in the interval group than in the control group ( P < 0.05): by 8.99% in the interval and 12.07% in power group compared with the control group. In addition, the average HRs in interval group (117.99 ± 13.20) and power group (121.33 ± 11.33) were in the range of moderate exercise intensity, but the average HR in the control group (108.26 ± 10.31) was not in the range of moderate exercise intensity. Discussion This study investigated the effects of robotic-resisted exercise with a novel wearable hip exoskeleton, Bot Fit, on muscle strength, muscle effort, and the kinematics of the pelvis during walking in younger adults. The results of this study suggest that walking using a Bot Fit exercise programs offers several key advantages over exercise without a Bot Fit in terms of muscle strength, muscle effort, and pelvic symmetry during walking in younger adults. The interval group experienced a significant increase in the MVC of the right BF and the power group showed significant changes in the MVC of the bilateral BF after Bot Fit exercise. Significant decreases in muscle effort in the right BF in the interval group and the right LES and bilateral BF in the power group were observed. In addition, the SI of pelvic tilt improved significantly in the interval group, and greater exercise volume and intensity in interval and power groups were confirmed through the number of steps, distance, energy expenditure, and HR. The benefits of regular aerobic moderate-to-vigorous physical activity are well established and embraced by the Physical Activity Guidelines for Americans and the WHO 2020 Global Recommendations on Physical Activity for Health ( 41 , 42 ). The evidence that activities such as brisk walking, cycling, sports, and planned exercise reduce the risk of cardiovascular disease, stroke, type 2 diabetes, some cancers, and all-cause mortality has accumulated since the 1950s ( 41 ). Although recommendations for aerobic physical activity date back to at least the 1970s and have strengthened and been refined over time, recommendations for adults to engage in muscle-strengthening activities being initially included in the 2008 Physical Activity Guidelines for Americans ( 43 ). Unlike the decades of epidemiological research on aerobic moderate-to-vigorous physical activity, comparable research on muscle-strengthening exercise is limited. However, the role of muscular strength in the prevention of chronic disease in adults has been increasingly recognized ( 44 ), and the inclusion of resistance training in exercise programs that promote adult health has been endorsed by several organizations ( 45 ). In this study, the interval and power groups simultaneously performed aerobic physical activity (walking) and muscle-strengthening exercise with Bot Fit, while the control group performed only walking without a Bot Fit. The MVC of the right BF in the interval group and the MVC of the bilateral BF in the power group increased significantly after Bot Fit-resisted exercise, but there was no change in MVC after exercise in the control group. In addition, significant decreases in muscle effort in the right BF in the interval group and the right LES and bilateral BF in the power group were observed, but there was no change in muscle effort after exercise in the control group. These results imply that the resistance imposed by a Bot Fit, which generates hip-joint flexion and extension-resistive torque during walking, affected the MVC of the hip extension muscle, enhancing muscle strength and decreased effort of BF. Resistance exercise has been shown to rapidly increase muscular strength and is essential for improving sports performance, injury prevention and rehabilitation, and improving health in all populations ( 46 , 47 ). It is well established that resistance training leads to changes in the nervous system, which plays an important role in the development of strength ( 48 , 49 ). The increased MVC caused by resistance is expected to promote muscle strength in the BF by improving neural adaptations such as motor unit activation and synchronization, and by decreasing presynaptic inhibition ( 50 ). Our results indicate that Bot Fit–assisted exercise can increase muscle strength and help individuals walk more efficiently by reducing the required muscle effort. Control of pelvis alignment is necessary for efficient movement and walking, and if it is not properly controlled during walking, the speed, stability, and efficiency of the walk decreases ( 51 – 53 ). Asymmetries of the pelvis can be associated with the development of non-specific chronic low back pain, caused by incorrect mechanical load on the body which increases the stress on the soft tissues in the lumbar section ( 54 , 55 ). The increased use of sitting positions in daily life and sedentary behavior among young adults can induce a tendency to increase the asymmetric load exerted on the spine and disrupt pelvic symmetry ( 56 , 57 ). In this study, as a result of measuring the change in kinematics of the pelvis after exercise-intervention, the SI of pelvic tilt increased in the interval and power groups (by 23.80% and by 23.04%, respectively) after Bot Fit exercise, but the SI of pelvic tilt decreased in the control group (by 10.27%). The increase in the SI of pelvic tilt in the two groups that exercised using a Bot Fit can be attributed to the strengthened abdominal and hip muscles involved in pelvic tilt due to resistance exercise using a Bot Fit. In addition, a Bot Fit can stimulate and train a wearer’s muscles by providing controllable resistive force and torque at the hip joint. As these sensory inputs provide continuous feedback to correct movement and improve proprioception, and may have influenced pelvic symmetry during walking. The most commonly used metric of exercise intensity is HR, which is easy to monitor and stable during exercise ( 58 ). It is generally accepted that the relationship between HR/workload and oxygen consumption (and therefore caloric expenditure) is linear, and HR therefore accurately reflects workload and exercise intensity. As such, it is often used to prescribe exercise and track changes in training status of athletes ( 59 , 60 ). In this study, the exercise volume and intensity of each group were mesured using the number of steps, distance, energy expenditure, and HR. The number of steps and distance during exercise were significantly higher in the power group than in the interval and control groups, and the average HR and energy expenditure during exercise were significantly higher in the interval and power groups compared with the control group. A Bot Fit can provide extensive, repetitive, task-specific walking exercise that can increase exercise intensity, which in turn affects HR and energy expenditure during exercise. In addition, the Bot Fit exercise programs increase exercise volume by providing resistance and encouraging walking at a speed above a certain level. Use of the Bot Fit during exercise can enhance the physiologic effects of exercise compared with the same exercise performed without a Bot Fit. This study has limitations related to inadequate control of everyday activity levels of the participants beyond the exercise-intervention session. During the long-term intervention period, other factors that may have affected the study outcome, such as an individual’s overall amount of physical activity, were not controlled or monitored. All participants were allowed to perform their usual daily activities and complete the study without drop-outs during the study period. Second, the statistical power of this study was low because of the small number of participants, and our results cannot be generalized to the entire young population. Nevertheless, this study demonstrates that use of a Bot Fit while walking can improve muscle strength and effort and symmetry of pelvic movement compared with the same exercise without a Bot Fit. Conclusions This study was a randomized controlled trial evaluating the effects of robotic-resisted exercise with the Bot Fit in younger adults. The results of this study confirm the beneficial effect of the Bot Fit on muscle strength, walking efficiency, and pelvic movement symmetry in younger adults. Personalized exercise programs using different exercise protocols with the Bot Fit can therefore improve physical health and gait symmetry in younger adults. Abbreviations sEMG Surface electromyography RA Rectus abdominis LES lumbar erector spinae RF Rectus femoris BF Biceps femoris MVC Maximum voluntary contraction SI Symmetry index HR Heart rate Declarations Ethics approval and consent to participate Study procedures were approved by the ethics committee of the Sungkyunkwan University Institutional Review Board (approval number: 2023-03-005), written informed consent was obtained from all participants before they entered the study, and all methods were carried out in accordance with the approved study protocol. Trial registration: ClinicalTrials.gov, NCT05862077. Registered 22 March 2022, https://register.clinicaltrials.gov/prs/app/action/SelectProtocol?sid=S000D386&selectaction=Edit&uid=U00025OA&ts=2&cx=6itjjg Consent for publication All participants consented to data publication. Availability of data and material The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request. Competing interests The authors declare that they have no competing interests. Funding This study was supported by Samsung Electronics (S-2023-0600-000-1) Authors’ contributions All authors contributed substantially to the development of this manuscript. SHL, HJL and YHK designed the experiment; SHL, EMK, UJK, DWK and DKL recruited participants and recorded data; SHL, EMK and JUK analyzed and interpreted the results. SHL and HJL created the first draft of the manuscript. YHK and HJL improved results and contributed with improvements in literature review. All authors read and approved the final manuscript. Acknowledgments We thank all participants for volunteering to participate in this study Authors’ information Department of Physical and Rehabilitation Medicine, Sungkyunkwan University School of Medicine, Suwon, 16419, Republic of Korea Su-Hyun Lee, Eunmi Kim, Yun-Hee Kim Center for Neuroscience Imaging Research, Institute for Basic Science, Suwon, 16419, Republic of Korea Jinuk Kim Robot Business Team, Samsung Electronics, Suwon, 16677, Republic of Korea Donwoo Kim, Dokwan Lee, Hwang-Jae Lee Haeundae Sharing and Happiness Hospital, Pusan, 612702, Republic of Korea Yun-Hee Kim References Bouchard C, Blair SN, Katzmarzyk PT, editors. Less sitting, more physical activity, or higher fitness? Mayo Clinic Proceedings; 2015: Elsevier. Dumith SC, Hallal PC, Reis RS, Kohl HW III. Worldwide prevalence of physical inactivity and its association with human development index in 76 countries. Prev Med. 2011;53(1–2):24–8. 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A pooled analysis of data on 11 population cohorts with all-cause, cancer, and cardiovascular mortality endpoints. Am J Epidemiol. 2018;187(5):1102–12. Tarasenko YN, Linder DF, Miller EA. Muscle-strengthening and aerobic activities and mortality among 3 + year cancer survivors in the US. Cancer Causes Control. 2018;29:475–84. Lemes ÍR, Ferreira PH, Linares SN, Machado AF, Pastre CM, Netto J. Resistance training reduces systolic blood pressure in metabolic syndrome: a systematic review and meta-analysis of randomised controlled trials. Br J Sports Med. 2016. Schoenfeld BJ, Ogborn D, Krieger JW. Effects of resistance training frequency on measures of muscle hypertrophy: a systematic review and meta-analysis. Sports Med. 2016;46(11):1689–97. Martyn-St James M, Carroll S. Effects of different impact exercise modalities on bone mineral density in premenopausal women: a meta-analysis. J Bone Miner Metab. 2010;28:251–67. Bennie JA, Shakespear-Druery J, De Cocker K. 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Differential effects of aerobic exercise, resistance training and combined exercise modalities on cholesterol and the lipid profile: review, synthesis and recommendations. Sports Med. 2014;44:211–21. Valenzuela PL, Ruilope LM, Santos-Lozano A, Wilhelm M, Kränkel N, Fiuza-Luces C, et al. Exercise benefits in cardiovascular diseases: from mechanisms to clinical implementation. Eur Heart J. 2023;44(21):1874–89. Whelton SP, Chin A, Xin X, He J. Effect of aerobic exercise on blood pressure: a meta-analysis of randomized, controlled trials. Ann Intern Med. 2002;136(7):493–503. Yang Y-R, Wang R-Y, Lin K-H, Chu M-Y, Chan R-C. Task-oriented progressive resistance strength training improves muscle strength and functional performance in individuals with stroke. Clin Rehabil. 2006;20(10):860–70. Lewek MD, Raiti C, Doty A. The presence of a paretic propulsion reserve during gait in individuals following stroke. Neurorehabilit Neural Repair. 2018;32(12):1011–9. Chang Y-H, Kram R. Metabolic cost of generating horizontal forces during human running. J Appl Physiol. 1999;86(5):1657–62. Gama GL, Savin DN, Keenan T, Waller SM, Whitall J. Comparing the effects of adapting to a weight on one leg during treadmill and overground walking: A pilot study. Gait Posture. 2018;59:35–9. Mun K-R, Yeo BBS, Guo Z, Chung SC, Yu H. Resistance training using a novel robotic walker for over-ground gait rehabilitation: a preliminary study on healthy subjects. Med Biol Eng Comput. 2017;55:1873–81. Moreland JD, Goldsmith CH, Huijbregts MP, Anderson RE, Prentice DM, Brunton KB, et al. Progressive resistance strengthening exercises after stroke: a single-blind randomized controlled trial. Arch Phys Med Rehabil. 2003;84(10):1433–40. Chu KS, Eng JJ, Dawson AS, Harris JE, Ozkaplan A, Gylfadóttir S. A randomized controlled trial of water-based exercise for cardiovascular fitness in individuals with chronic stroke. Arch Phys Med Rehabil. 2004;85(6):870. Grøntved A, Pan A, Mekary RA, Stampfer M, Willett WC, Manson JE, et al. Muscle-strengthening and conditioning activities and risk of type 2 diabetes: a prospective study in two cohorts of US women. PLoS Med. 2014;11(1):e1001587. Harshe K, Williams JR, Hocking TD, Lerner ZF. Predicting Neuromuscular Engagement to Improve Gait Training with a Robotic Ankle Exoskeleton. IEEE Robotics and Automation Letters; 2023. Lee H-J, Lee S-H, Seo K, Lee M, Chang WH, Choi B-O, et al. Training for walking efficiency with a wearable hip-assist robot in patients with stroke: a pilot randomized controlled trial. Stroke. 2019;50(12):3545–52. Lee S-H, Kim J, Lim B, Lee H-J, Kim Y-H. Exercise with a wearable hip-assist robot improved physical function and walking efficiency in older adults. Sci Rep. 2023;13(1):7269. Hermens HJ, Freriks B, Disselhorst-Klug C, Rau G. Development of recommendations for SEMG sensors and sensor placement procedures. J Electromyogr Kinesiol. 2000;10(5):361–74. Sousa AS, Tavares JMR. Surface electromyographic amplitude normalization methods: a review. Electromyography: new developments, procedures and applications. 2012. Schmitz A, Silder A, Heiderscheit B, Mahoney J, Thelen DG. Differences in lower-extremity muscular activation during walking between healthy older and young adults. J Electromyogr Kinesiol. 2009;19(6):1085–91. Gellish RL, Goslin BR, Olson RE, McDONALD A, Russi GD, Moudgil VK. Longitudinal modeling of the relationship between age and maximal heart rate. Med Sci Sports Exerc. 2007;39(5):822–9. Piercy KL, Troiano RP, Ballard RM, Carlson SA, Fulton JE, Galuska DA, et al. The physical activity guidelines for Americans. JAMA. 2018;320(19):2020–8. Bull FC, Al-Ansari SS, Biddle S, Borodulin K, Buman MP, Cardon G, et al. World Health Organization 2020 guidelines on physical activity and sedentary behaviour. Br J Sports Med. 2020;54(24):1451–62. Giovannucci EL, Rezende LF, Lee DH. Muscle-strengthening activities and risk of cardiovascular disease, type 2 diabetes, cancer and mortality: A review of prospective cohort studies. J Intern Med. 2021;290(4):789–805. Ruiz JR, Sui X, Lobelo F, Morrow JR, Jackson AW, Sjöström M et al. Association between muscular strength and mortality in men: prospective cohort study. BMJ. 2008;337. Steene-Johannessen J, Anderssen SA, Kolle E, Andersen LB. Low muscle fitness is associated with metabolic risk in youth. Med Sci Sports Exerc. 2009;41(7):1361–7. Fragala MS, Cadore EL, Dorgo S, Izquierdo M, Kraemer WJ, Peterson MD et al. Resistance training for older adults: position statement from the national strength and conditioning association. J Strength Conditioning Res. 2019;33(8). Maestroni L, Read P, Bishop C, Papadopoulos K, Suchomel TJ, Comfort P, et al. The benefits of strength training on musculoskeletal system health: practical applications for interdisciplinary care. Sports Med. 2020;50(8):1431–50. Enoka RM. Neural adaptations with chronic physical activity. J Biomech. 1997;30(5):447–55. Enoka RM. Neural strategies in the control of muscle force. Muscle Nerve: Official J Am Association Electrodiagn Med. 1997;20(S5):66–9. Frontera WR, Hughes VA, Krivickas LS, Kim SK, Foldvari M, Roubenoff R. Strength training in older women: early and late changes in whole muscle and single cells. Muscle Nerve. 2003;28(5):601–8. Gurney B. Leg length discrepancy. Gait Posture. 2002;15(2):195–206. Staszkiewicz R, Chwała W, Forczek W, Laska J. Three-dimensional analysis of the pelvic and hip mobility during gait on a treadmill and on the ground. Acta Bioeng Biomech. 2012;1:12. Dickstein R, Abulaffio N. Postural sway of the affected and nonaffected pelvis and leg in stance of hemiparetic patients. Arch Phys Med Rehabil. 2000;81(3):364–7. Applebaum A, Nessim A, Cho W. Overview and spinal implications of leg length discrepancy: narrative review. Clin Orthop Surg. 2021;13(2):127. Azizan NA, Basaruddin KS, Salleh AF, Sulaiman AR, Safar MJA, Rusli WMR. Leg length discrepancy: dynamic balance response during gait. Journal of healthcare engineering. 2018;2018. Biały M, Kłaptocz P, Gnat R. Functional asymmetry of the spine in standing and sitting positions. Acta Gymnica. 2010;40(1):53–60. Gao Y. Sit-stand workstations: effects on occupational sitting time, potential health benefits, and acute postural physiology. Studies in sport. Phys Educ health. 2017(260). Achten J, Jeukendrup AE. Heart rate monitoring: applications and limitations. Sports Med. 2003;33:517–38. Sinclair MR. Heart rate as a marker of training status. 2006. Halson SL. Monitoring training load to understand fatigue in athletes. Sports Med. 2014;44(Suppl 2):139–47. Cite Share Download PDF Status: Published Journal Publication published 14 Oct, 2024 Read the published version in Sports Medicine-Open → Version 1 posted Editorial decision: Major Revision 14 Jul, 2024 Reviewers agreed at journal 09 Mar, 2024 Reviewers invited by journal 05 Mar, 2024 Editor assigned by journal 03 Mar, 2024 First submitted to journal 27 Feb, 2024 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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-3998966","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":276459500,"identity":"add3a40a-4632-4110-8c5c-2e3e072267c9","order_by":0,"name":"Su-Hyun Lee","email":"","orcid":"","institution":"Sungkyunkwan University School of Medicine","correspondingAuthor":false,"prefix":"","firstName":"Su-Hyun","middleName":"","lastName":"Lee","suffix":""},{"id":276459501,"identity":"ce524f94-5c71-4c67-98ec-8f0f498abe0b","order_by":1,"name":"Eunmi Kim","email":"","orcid":"","institution":"Sungkyunkwan University School of Medicine","correspondingAuthor":false,"prefix":"","firstName":"Eunmi","middleName":"","lastName":"Kim","suffix":""},{"id":276459502,"identity":"ed48ac0c-8744-4534-b858-063f310dd66a","order_by":2,"name":"Jinuk Kim","email":"","orcid":"","institution":"Institute for Basic Science","correspondingAuthor":false,"prefix":"","firstName":"Jinuk","middleName":"","lastName":"Kim","suffix":""},{"id":276459503,"identity":"724b7bc5-9610-4e39-97c5-f1e95a3bfbe6","order_by":3,"name":"Dongwoo Kim","email":"","orcid":"","institution":"Samsung Electronics","correspondingAuthor":false,"prefix":"","firstName":"Dongwoo","middleName":"","lastName":"Kim","suffix":""},{"id":276459504,"identity":"17d53503-196d-41c3-a975-d27ba86c71fe","order_by":4,"name":"Dokwan Lee","email":"","orcid":"","institution":"Samsung Electronics","correspondingAuthor":false,"prefix":"","firstName":"Dokwan","middleName":"","lastName":"Lee","suffix":""},{"id":276459505,"identity":"c684ec18-8ba4-46a1-8c1a-6bd8491c5892","order_by":5,"name":"Hwang-Jae Lee","email":"","orcid":"","institution":"Samsung Electronics","correspondingAuthor":false,"prefix":"","firstName":"Hwang-Jae","middleName":"","lastName":"Lee","suffix":""},{"id":276459506,"identity":"fea62f2e-fb13-449d-8f9e-25883ffe36d9","order_by":6,"name":"Yun-Hee Kim","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAq0lEQVRIiWNgGAWjYHACZoYEBhsGCR4Qm414LWmkamFgOEyCFoMbuYcNHuact5fsOWPA8KHsMDFa8pITErfdTpzN22PAOOMcUVpyjA8AtSTI8fMYMPO2Ea/lnD1Yy19itQAddoAR5DBmRmK0SJ55Y2yQuC05cWbPsYKDPefSCWvhO55jLPlzm529xJnkjQ9+lFkT1qJwAIlzAIciVCDfQJSyUTAKRsEoGNEAAMcNOwFxxjmWAAAAAElFTkSuQmCC","orcid":"https://orcid.org/0000-0001-6101-8851","institution":"Sungkyunkwan University School of Medicine","correspondingAuthor":true,"prefix":"","firstName":"Yun-Hee","middleName":"","lastName":"Kim","suffix":""}],"badges":[],"createdAt":"2024-02-29 08:01:07","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-3998966/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-3998966/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1186/s40798-024-00773-x","type":"published","date":"2024-10-14T15:58:05+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":52191115,"identity":"9d91cb48-1afe-4c86-b68e-b23a90856ca5","added_by":"auto","created_at":"2024-03-07 19:27:48","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":3762853,"visible":true,"origin":"","legend":"\u003cp\u003e(A) Experimental protocol (B) Wearable hip exoskeleton, Bot Fit.\u003c/p\u003e","description":"","filename":"Figure1.png","url":"https://assets-eu.researchsquare.com/files/rs-3998966/v1/971ba5f0a30c833c9309ca4d.png"},{"id":52193378,"identity":"a6801d78-4fd0-4168-a18b-a6922f29208f","added_by":"auto","created_at":"2024-03-07 19:35:48","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":2837152,"visible":true,"origin":"","legend":"\u003cp\u003eEffects of Bot Fit on muscle effort (% MVC).\u003c/p\u003e","description":"","filename":"Figure2.png","url":"https://assets-eu.researchsquare.com/files/rs-3998966/v1/ac093d1846847ce2c8e61fe5.png"},{"id":52191116,"identity":"35f72a4f-d6ee-4f62-afc4-648ba6f240f8","added_by":"auto","created_at":"2024-03-07 19:27:48","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":581132,"visible":true,"origin":"","legend":"\u003cp\u003eKinematics of pelvis during walking.\u003c/p\u003e","description":"","filename":"Figure3.png","url":"https://assets-eu.researchsquare.com/files/rs-3998966/v1/930f3961fa782083aec3476b.png"},{"id":52191113,"identity":"9d595c86-6612-46aa-8e3f-466a43dd15eb","added_by":"auto","created_at":"2024-03-07 19:27:48","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":105438,"visible":true,"origin":"","legend":"\u003cp\u003eNumber of steps, distance, energy expenditure, and heart rate during exercise.\u003c/p\u003e","description":"","filename":"Figure4.png","url":"https://assets-eu.researchsquare.com/files/rs-3998966/v1/a75d3d965b89d1d9d778d2e6.png"},{"id":67149088,"identity":"25bfa78f-7def-4b0f-b0a5-80f595c3a4ad","added_by":"auto","created_at":"2024-10-21 16:11:48","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":6513070,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-3998966/v1/06de2b16-a2b6-4c94-b03e-67557cf741df.pdf"}],"financialInterests":"","formattedTitle":"Robotic-resisted Exercise for Health Promotion in Younger Adults","fulltext":[{"header":"Introduction","content":"\u003cp\u003eLow levels of physical activity and sedentary behavior (time spent sitting, as distinct from lack of physical activity) both increase the risk of chronic disease and mortality (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e). Worldwide, one of five adults are physically inactive, and sedentary lifestyles are spreading in popularity (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e). Recent updates to physical activity guidelines highlight the importance of reducing sedentary time (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e). Regular participation in physical activity and reducing sedentary behavior play important roles in physical health and disease prevention (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e). Current global recommendations state that adults aged 18\u0026ndash;64 years should engage in at least 150 min of moderate-intensity aerobic physical activity, or at least 75 min of vigorous-intensity aerobic physical activity, or an equivalent combination of both a week, as well as muscle-strengthening activities involving major muscle groups two or more days a week (\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e). Although many health organizations, including the World Health Organization (WHO), emphasize the importance of physical activity, the number of individuals who currently do not meet the recommendations for physical activity continues to grow worldwide. Recent global estimates show that one in four (27.5%) adults (\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e) and more than three-quarters (81%) of adolescents (\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e) do not meet the aerobic exercise provisions of the 2010 Global Recommendations on Physical Activity for Health (\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eResearch suggests that regular aerobic exercise can prevent weight gain and improve physical fitness, cardiorespiratory health, executive functioning, and brain health, even in healthy populations (\u003cspan additionalcitationids=\"CR10 CR11\" citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e). Additionally, strong clinical evidence and emerging epidemiological data show that muscle-strengthening exercise is independently associated with multiple health outcomes, including a reduced risk of all-cause mortality and the incidence of diabetes and enhanced cardiometabolic musculoskeletal and mental health (\u003cspan additionalcitationids=\"CR14 CR15 CR16\" citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e). However, muscle-strengthening exercise have been overlooked in public health approaches to chronic-disease prevention despite numerous independent health benefits compared with the attention devoted to aerobic physical activity. Moreover, recent health surveillance data from several countries show that only 10\u0026ndash;30% of adults meet guidelines for muscle-strengthening exercise, a far lower proportion than those meeting aerobic physical activity guidelines (approximately 50%) (\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e).\u003c/p\u003e \u003cp\u003ePhysical activity recommendations in public health campaigns have focused on promoting moderate-to-vigorous-intensity exercises since the 1970s. However, over the past decade, the value of muscle-strengthening exercise has been recognized, with the combination of muscle- strengthening exercise and aerobic physical activity being a recent addition to physical activity guidelines (\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e). Recent epidemiological studies suggest that, compared with engaging in either moderate-to-vigorous-intensity aerobic physical activity or muscle-strengthening exercise alone, a combination of both has more favorable effects on cardiometabolic biomarkers, lean muscle mass, and mental health (\u003cspan additionalcitationids=\"CR22\" citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e). Moreover, concurrent exercise, an integrative exercise modality that combines aerobic physical activity with muscle-strengthening exercise, is a time-efficient strategy that fits into modern busy lifestyles and provide the benefits of both interventions (\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eResistance training during aerobic physical activity, such as walking with weights, is well recognized as a method of increasing metabolic cost while improving muscle strength, overground walking performance, and endurance in healthy as well as neurologically impaired individuals (\u003cspan additionalcitationids=\"CR27 CR28\" citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e). A few studies have used weights attached to a subject\u0026rsquo;s waist and connected to a pulley system to examine the efficacy of resistance training while walking on a treadmill (\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e, \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e, \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e). Other studies have added weights to subject\u0026rsquo;s limb segments as they walk (\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e) or practice walking in water tanks (\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e). However, conventional training is often performed using additional loads such as resistance bands, weighted cuffs, or a backpack on the body, all of which tend to be bulky and less stable (i.e., large resistive forces are only possible with excessively large weights). Moreover, these methods typically vary the task intensity through progressive schemes, such as increasing band stiffness or adding higher weights over time (\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e, \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e, \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eWearable robotic systems, particularly those that provide resistance targeting specific muscle groups and functions, have emerged as potential tools to more effectively target the appropriate timing of the activity of specific muscle groups in a functional context (\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e). In this study, we used a wearable robotic hip exoskeleton, the Bot Fit, which can produce resistive torque during walking, to investigate the effects of Bot Fit exercise programs. In our previous studies, we demonstrated the effects of Bot Fit\u0026ndash;resisted exercise in older adults and stroke patients (\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e, \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e). The purpose of this study was to investigate the effects of Bot Fit exercise on muscle strength, muscle effort, and kinematics of the pelvis during walking in younger adults.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eStudy design and participants\u003c/h2\u003e \u003cp\u003eThis study used a single-blinded (evaluator), randomized, controlled, three-group, parallel design. The characteristics of the 45 participants are shown in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. Based on their histories and functional assessments, we excluded individuals with a history of neurological and musculoskeletal disorders that affect walking capacity, efficiency, and endurance. Eligible subjects were healthy and between 19 and 65 years of age without any history of central nervous system disease. Study procedures were approved by the ethics committee of the Sungkyunkwan University Institutional Review Board (approval number: 2023-03-005) and registered with ClinicalTrials.gov (NCT05862077). Written informed consent was obtained from all participants before they entered the study, and all methods were carried out in accordance with the approved study protocol.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eBaseline characteristics of participants (N\u0026thinsp;=\u0026thinsp;45)\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCharacteristics\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eControl\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eInterval\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003ePower\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eχ\u003csup\u003e2\u003c/sup\u003e/F\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eP\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge, years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e38.47 (4.82)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e36.07 (2.46)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e37.40 (5.79)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.035\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.364\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSex (male/female)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e14/1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10/5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e11/4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e3.343\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.188\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHeight, cm\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e174.30 (6.94)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e172.03 (8.80)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e171.53 (9.10)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.469\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.629\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWeight, kg\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e77.41 (11.13)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e70.99 (13.99)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e76.53 (13.09)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.111\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.339\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBody mass index, kg/m\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e25.41 (2.76)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e23.78 (3.12)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e25.87 (2.94)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e2.093\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.136\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"6\"\u003eData are expressed as mean (standard deviation).\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003eExercise intervention\u003c/h2\u003e \u003cp\u003eAll subjects in the interval and power groups performed community-mobility routines (walking in the Samsung Digital City, including level walking, slope and stair walking, and crossing the cross walk) for 30 mins with a Bot Fit while the control group did the same without a Bot Fit. The interval group exercised using the interval exercise program, which repeats rapid walking in resistance mode and slow walking in assistance mode with Bot Fit, and the power group exercised using the power exercise program, which repeats rapid walking in resistance mode and rapid walking in assistance mode with Bot Fit.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003eWearable hip-assist robot, Bot Fit\u003c/h2\u003e \u003cp\u003eThe Bot Fit, which was developed at Samsung Electronics Co., Ltd. (Suwon, Republic of Korea), is a wearable hip-type robot designed to promote health in younger adults. The device is fastened around the wearer\u0026rsquo;s waist and thighs to assist or resist hip-joint flexion and extension. Torque assistance and resistance are transmitted to the user\u0026rsquo;s thighs through an exoskeletal frame (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Users can operate the device and change the exercise program settings using an application on a mobile phone and smart watch.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003eAssessment tools and data collection\u003c/h2\u003e \u003cp\u003eParticipants were evaluated at two time points: before (pre) and after (post) 18 exercise-intervention sessions. Each assessment evaluated muscle strength, muscle effort, and the kinematics of the pelvis during walking. In addition, the number of steps, distance, energy expenditure, and heart rate (HR) for each 30-min exercise session were recorded.\u003c/p\u003e \u003cp\u003eTo measure surface electromyography (sEMG) signals (Noraxon USA Inc., Scottsdale, AZ, USA), bipolar surface electrodes (Ag/AgCl) were positioned on the right rectus abdominis (RA) and lumbar erector spinae (LES) and the bilateral rectus femoris (RF) and biceps femoris (BF) of subjects following guidance by the Surface ElectroMyoGraphy for Non-Invasive Assessment of Muscles (SENIAM) project for reliable sensor placement (\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e). In addition, footswitches (Model 500 DTS FootSwitch; Noraxon USA Inc.) were placed on the bilateral toe and heel to record the timing of the stance and swing gait phases while walking. Before placing sEMG sensors, subjects\u0026rsquo; skin was shaved, abraded, and cleaned with alcohol to reduce surface impedance. We defined muscle effort as the percentage of maximum voluntary contraction (% MVC) averaged across all participants. The MVC test is a normalizing method proposed by the SENIAM project and kinesiology guidelines and is the most widely used normalization method (\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e). To normalize the sEMG signal amplitude, three 5-s maximal muscle contraction measurement trials were performed with each muscle to determine each participant\u0026rsquo;s MVC. To reduce movement artifacts, a sampling frequency of 1,000 Hz was used, and raw sEMG signals were bandpass filtered between 10 and 350 Hz and full-wave rectified with Noraxon software (MyoResearch XP Master Edition). The root mean squared values of the signals were calculated using a sliding 100-ms window. The data were passed through a sixth-order Butterworth low-pass filter with a 6-Hz cutoff to create a linear envelope and normalized to the MVC data obtained prior to the tasks. The average normalized sEMG activity was processed within the selected phases of the gait cycle using MATLAB software (MathWorks, Inc., Natick, MA, USA) (\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e). Individual gait cycles were determined using footswitch data, with each stride considered the period between successive heel strikes by the same leg. The sEMG patterns for each stride were time-normalized and expressed as a percentage of the total gait cycle (0\u0026ndash;99%).\u003c/p\u003e \u003cp\u003eThe three-dimensional kinematics of the pelvis (anterior-posterior tilt, up-down obliquity, and intra-extra rotation) and pelvic symmetry index (SI) were measured using a wireless G-Walk wearable sensor (BTS Bioengineering S.p.A., Milan, Itay), which consists of a triaxial accelerometer, a magnetic sensor, and a triaxial gyroscope. The G-Walk sensor was placed on the subject\u0026rsquo;s waist using a semi-elastic belt covering the L4-L5 intervertebral space to acquire the acceleration values for the three anatomical axes (antero-posterior, medio-lateral and vertebral). Subjects were asked to walk 10 m in one direction and then turn around and walk 10 m back at a self-selected speed, as naturally as possible. The collected data, transmitted to a personal computer via Bluetooth and processed with dedicated BTS G-Walk software, allowed us to obtain a set of gait parameters from which the kinematics of the pelvis (degree of tilt, obliquity, and rotation) and SI (%) could be analyzed. SI quantifies the similarity of the profiles of the right and left curves. If the two curves overlap perfectly, the index score is 100, meaning that the two curves have the same value frame by frame. The pelvis position in three planes comprises the pelvic tilt in the sagittal plain, pelvic obliquity in the coronal plane, and pelvic rotation in the transverse plane. For pelvic tilt, SI values higher than 40 can be considered normal. For the pelvic obliquity and rotation angles, a normal SI value is 80\u0026ndash;100 (according to guidelines supplied by the manufacturer, BTS Bioengineering S.p.A., Milan, Italy). The BTS G-Walk device uses a mathematical correlation function applied to the two curves: symmetric index = (corr\u0026thinsp;+\u0026thinsp;1) \u0026times; 100/2, where corr is the Pearson correlation coefficient between the mean left and right normalized anteroposterior acceleration signals (according to the manufacturer\u0026rsquo;s guidelines).\u003c/p\u003e \u003cp\u003eThe number of steps, distance, energy expenditure, and average HR during 30 min of exercise were measured using a Samsung Galaxy Active 2 smart watch linked to a mobile phone Bot Fit application.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003eStatistical analyses\u003c/h2\u003e \u003cp\u003eStatistical analyses were performed using SPSS version 22.0 (IBM, Armonk, NY, USA), with a significance level of 0.05. Descriptive statistics are expressed as means and standard deviation. After examining the distribution of the data for normality, we chose parametric tests for MVC and pelvic movement and non-parametric tests for muscle effort (% MVC). One-way analysis of variance (ANOVA) for continuous variables and chi-square tests for categorical variables were used to compare participants\u0026rsquo; baseline characteristics. To compare the outcome measures before and after exercise in each group, paired t-tests and Wilcoxon signed-rank tests were used. One-way ANOVA and Kruskal\u0026ndash;Wallis tests were used to determine statistically significant differences among groups. In addition, repeated-measures ANOVA was used to examine the main effects of exercise over time, including groups and time points. Post hoc tests were used to identify differences among the group means, and the significance levels of the tests were adjusted using Bonferroni corrections.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003eEffects of Bot Fit exercise on muscle strength and muscle effort\u003c/h2\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e and Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e present the specific values for MVC (\u0026micro;V) and muscle effort (% MVC) at the respective pre\u0026ndash; and post\u0026ndash;time points. Significant improvements in the MVC of the left BF were seen in the interval group while the power group showed significant changes in the MVC of the bilateral BF after Bot Fit exercise (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05). However, no significant changes were evident in the control group. Muscle effort during the total gait cycle (100%) decreased significantly in the right BF in the interval group and in the right LES and bilateral BF in the power group (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05) after Bot Fit exercise. In contrast, the control group showed no significant muscle effort decreases. Significant group \u0026times; time interactions were also found in muscle effort in the right LES and bilateral BF, and the interval and power groups experienced greater changes compared with the control group (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eEffects of Bot Fit exercise on muscle strength (N\u0026thinsp;=\u0026thinsp;45)\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"10\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eMVC, \u0026micro;V\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eControl\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003eInterval\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c8\" namest=\"c6\"\u003e \u003cp\u003ePower\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c10\" namest=\"c9\"\u003e \u003cp\u003eBetween-group\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePre\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003ePost\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003ePre\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003ePost\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003ePre\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003ePost\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e \u003cp\u003eF\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c10\"\u003e \u003cp\u003eP\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRt. RA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e153.40 (82.69)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e149.47 (76.70)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e134.01 (63.46)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e136.37 (75.17)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e118.49 (46.03)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e \u003cp\u003e128.37 (53.81)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.326\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.724\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRt. LES\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e190.11 (111.68)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e184.69 (123.74)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e161.51 (80.59)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e161.62 (76.25)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e151.45 (76.69)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e \u003cp\u003e164.23 (73.79)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.364\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.697\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRt. RF\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e214.05 (79.65)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e216.85 (75.37)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e168.62 (57.10)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e176.39 (70.18)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e217.10 (80.57)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e \u003cp\u003e232.36 (87.35)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.176\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.840\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLt. RF\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e197.05 (78.26)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e198.64 (63.98)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e191.64 (63.65)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e199.08 (91.27)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e204.77 (78.67)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e \u003cp\u003e217.25 (94.99)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.108\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.898\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRt. BF\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e240.96 (112.56)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e251.35 (124.90)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e205.09 (79.35)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e245.28 (126.31)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e209.25 (99.41)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e \u003cp\u003e250.44 (102.92)\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.776\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.468\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLt. BF\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e223.40 (94.62)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e242.97 (114.18)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e195.47 (91.37)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e236.00 (96.07)\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e183.29 (75.20)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e \u003cp\u003e225.50 (87.63)\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.728\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.490\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"10\"\u003eData are expressed as mean (standard deviation).\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"10\"\u003e\u003csup\u003e*\u003c/sup\u003eSignificant change compared with Pre (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05).\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"10\"\u003eMVC: maximum voluntary contraction, RA: rectus abdominis, LES: lumbar extensor spinae, RF: rectus femoris, BF: biceps femoris.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003eEffects of Bot Fit exercise on kinematics of the pelvis\u003c/h2\u003e \u003cp\u003eSpecific values for pelvic SI and kinematics of the pelvis are presented in Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e and Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e. The SI of pelvic tilt tended to increase in post\u0026ndash; compared to pre\u0026ndash;time points in the interval and power groups (by 23.80% and 23.04%, respectively), but the increase was statistically significant different only in the interval group (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eEffects of Bot Fit exercise on kinematics of the pelvis (N\u0026thinsp;=\u0026thinsp;45)\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"9\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eControl\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003eInterval\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003ePower\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e \u003cp\u003eBetween-group\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePre\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003ePost\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003ePre\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003ePost\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003ePre\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003ePost\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eF\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e \u003cp\u003eP\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTilt\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e60.77 (17.17)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e54.53 (20.23)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e53.73 (28.68)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e71.89 (21.07)\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e60.19 (27.56)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e74.06 (15.48)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e2.659\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.082\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eObliquity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e97.41 (1.80)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e98.02 (0.83)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e98.37 (0.96)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e98.46 (1.05)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e98.39 (0.79)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e98.63 (0.98)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.364\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.697\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRotation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e98.41 (1.09)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e98.65 (0.88)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e98.52 (0.59)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e98.49 (0.93)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e96.57 (6.85)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e98.66 (0.79)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.235\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.301\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"9\"\u003eData are expressed as mean (standard deviation).\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"9\"\u003e\u003csup\u003e*\u003c/sup\u003eSignificant change compared with Pre (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05).\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eNumber of steps, distance, energy expenditure, and heart rate during exercise\u003c/h2\u003e \u003cp\u003eTable\u0026nbsp;4 presents values for the number of steps, distance, energy expenditure, and average HR during exercise in each group. The number of steps and distance were significantly higher in the power group than in the control and interval groups (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05). Energy expenditure was significantly higher in the power group than in the interval and control groups, and the interval group power expenditure was also significantly higher than that of the control group (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05): by 24.30% in interval group and 44.38% in the power group compared with the control group. The maximum heart rate (HR\u003csub\u003emax\u003c/sub\u003e) averages predicted by the [207\u0026thinsp;\u0026minus;\u0026thinsp;0.7 \u0026times; age] Eq.\u0026nbsp;(40) were 180.1 in the control group, 181.8 in the interval group, and 180.8 in the power group. The ranges in moderate exercise intensity (64\u0026ndash;76% of HR\u003csub\u003emax\u003c/sub\u003e) were from 115.3 to 136.9 in control group, 116.3 to 138.1 in the interval group, and 115.7 to 137.4 in the power group. The average HR during exercise was significantly higher in the power group than in the interval and control groups, and it was also significantly higher in the interval group than in the control group (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05): by 8.99% in the interval and 12.07% in power group compared with the control group. In addition, the average HRs in interval group (117.99\u0026thinsp;\u0026plusmn;\u0026thinsp;13.20) and power group (121.33\u0026thinsp;\u0026plusmn;\u0026thinsp;11.33) were in the range of moderate exercise intensity, but the average HR in the control group (108.26\u0026thinsp;\u0026plusmn;\u0026thinsp;10.31) was not in the range of moderate exercise intensity.\u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eThis study investigated the effects of robotic-resisted exercise with a novel wearable hip exoskeleton, Bot Fit, on muscle strength, muscle effort, and the kinematics of the pelvis during walking in younger adults. The results of this study suggest that walking using a Bot Fit exercise programs offers several key advantages over exercise without a Bot Fit in terms of muscle strength, muscle effort, and pelvic symmetry during walking in younger adults. The interval group experienced a significant increase in the MVC of the right BF and the power group showed significant changes in the MVC of the bilateral BF after Bot Fit exercise. Significant decreases in muscle effort in the right BF in the interval group and the right LES and bilateral BF in the power group were observed. In addition, the SI of pelvic tilt improved significantly in the interval group, and greater exercise volume and intensity in interval and power groups were confirmed through the number of steps, distance, energy expenditure, and HR.\u003c/p\u003e \u003cp\u003eThe benefits of regular aerobic moderate-to-vigorous physical activity are well established and embraced by the Physical Activity Guidelines for Americans and the WHO 2020 Global Recommendations on Physical Activity for Health (\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e, \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e). The evidence that activities such as brisk walking, cycling, sports, and planned exercise reduce the risk of cardiovascular disease, stroke, type 2 diabetes, some cancers, and all-cause mortality has accumulated since the 1950s (\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e). Although recommendations for aerobic physical activity date back to at least the 1970s and have strengthened and been refined over time, recommendations for adults to engage in muscle-strengthening activities being initially included in the 2008 Physical Activity Guidelines for Americans (\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e). Unlike the decades of epidemiological research on aerobic moderate-to-vigorous physical activity, comparable research on muscle-strengthening exercise is limited. However, the role of muscular strength in the prevention of chronic disease in adults has been increasingly recognized (\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e), and the inclusion of resistance training in exercise programs that promote adult health has been endorsed by several organizations (\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e). In this study, the interval and power groups simultaneously performed aerobic physical activity (walking) and muscle-strengthening exercise with Bot Fit, while the control group performed only walking without a Bot Fit. The MVC of the right BF in the interval group and the MVC of the bilateral BF in the power group increased significantly after Bot Fit-resisted exercise, but there was no change in MVC after exercise in the control group. In addition, significant decreases in muscle effort in the right BF in the interval group and the right LES and bilateral BF in the power group were observed, but there was no change in muscle effort after exercise in the control group. These results imply that the resistance imposed by a Bot Fit, which generates hip-joint flexion and extension-resistive torque during walking, affected the MVC of the hip extension muscle, enhancing muscle strength and decreased effort of BF. Resistance exercise has been shown to rapidly increase muscular strength and is essential for improving sports performance, injury prevention and rehabilitation, and improving health in all populations (\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e, \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e). It is well established that resistance training leads to changes in the nervous system, which plays an important role in the development of strength (\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e, \u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e). The increased MVC caused by resistance is expected to promote muscle strength in the BF by improving neural adaptations such as motor unit activation and synchronization, and by decreasing presynaptic inhibition (\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e). Our results indicate that Bot Fit\u0026ndash;assisted exercise can increase muscle strength and help individuals walk more efficiently by reducing the required muscle effort.\u003c/p\u003e \u003cp\u003eControl of pelvis alignment is necessary for efficient movement and walking, and if it is not properly controlled during walking, the speed, stability, and efficiency of the walk decreases (\u003cspan additionalcitationids=\"CR52\" citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e). Asymmetries of the pelvis can be associated with the development of non-specific chronic low back pain, caused by incorrect mechanical load on the body which increases the stress on the soft tissues in the lumbar section (\u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e, \u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e). The increased use of sitting positions in daily life and sedentary behavior among young adults can induce a tendency to increase the asymmetric load exerted on the spine and disrupt pelvic symmetry (\u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e, \u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e). In this study, as a result of measuring the change in kinematics of the pelvis after exercise-intervention, the SI of pelvic tilt increased in the interval and power groups (by 23.80% and by 23.04%, respectively) after Bot Fit exercise, but the SI of pelvic tilt decreased in the control group (by 10.27%). The increase in the SI of pelvic tilt in the two groups that exercised using a Bot Fit can be attributed to the strengthened abdominal and hip muscles involved in pelvic tilt due to resistance exercise using a Bot Fit. In addition, a Bot Fit can stimulate and train a wearer\u0026rsquo;s muscles by providing controllable resistive force and torque at the hip joint. As these sensory inputs provide continuous feedback to correct movement and improve proprioception, and may have influenced pelvic symmetry during walking.\u003c/p\u003e \u003cp\u003eThe most commonly used metric of exercise intensity is HR, which is easy to monitor and stable during exercise (\u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e58\u003c/span\u003e). It is generally accepted that the relationship between HR/workload and oxygen consumption (and therefore caloric expenditure) is linear, and HR therefore accurately reflects workload and exercise intensity. As such, it is often used to prescribe exercise and track changes in training status of athletes (\u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e59\u003c/span\u003e, \u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e60\u003c/span\u003e). In this study, the exercise volume and intensity of each group were mesured using the number of steps, distance, energy expenditure, and HR. The number of steps and distance during exercise were significantly higher in the power group than in the interval and control groups, and the average HR and energy expenditure during exercise were significantly higher in the interval and power groups compared with the control group. A Bot Fit can provide extensive, repetitive, task-specific walking exercise that can increase exercise intensity, which in turn affects HR and energy expenditure during exercise. In addition, the Bot Fit exercise programs increase exercise volume by providing resistance and encouraging walking at a speed above a certain level. Use of the Bot Fit during exercise can enhance the physiologic effects of exercise compared with the same exercise performed without a Bot Fit.\u003c/p\u003e \u003cp\u003eThis study has limitations related to inadequate control of everyday activity levels of the participants beyond the exercise-intervention session. During the long-term intervention period, other factors that may have affected the study outcome, such as an individual\u0026rsquo;s overall amount of physical activity, were not controlled or monitored. All participants were allowed to perform their usual daily activities and complete the study without drop-outs during the study period. Second, the statistical power of this study was low because of the small number of participants, and our results cannot be generalized to the entire young population. Nevertheless, this study demonstrates that use of a Bot Fit while walking can improve muscle strength and effort and symmetry of pelvic movement compared with the same exercise without a Bot Fit.\u003c/p\u003e"},{"header":"Conclusions","content":"\u003cp\u003eThis study was a randomized controlled trial evaluating the effects of robotic-resisted exercise with the Bot Fit in younger adults. The results of this study confirm the beneficial effect of the Bot Fit on muscle strength, walking efficiency, and pelvic movement symmetry in younger adults. Personalized exercise programs using different exercise protocols with the Bot Fit can therefore improve physical health and gait symmetry in younger adults.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cdiv class=\"DefinitionList\"\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003esEMG\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eSurface electromyography\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eRA\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eRectus abdominis\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eLES\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003elumbar erector spinae\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eRF\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eRectus femoris\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eBF\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eBiceps femoris\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eMVC\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eMaximum voluntary contraction\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eSI\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eSymmetry index\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eHR\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eHeart rate\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003c/div\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eStudy procedures were approved by the ethics committee of the Sungkyunkwan University Institutional Review Board (approval number: 2023-03-005), written informed consent was obtained from all participants before they entered the study, and all methods were carried out in accordance with the approved study protocol.\u003c/p\u003e\n\u003cp\u003eTrial registration: ClinicalTrials.gov, NCT05862077. Registered 22 March 2022, https://register.clinicaltrials.gov/prs/app/action/SelectProtocol?sid=S000D386\u0026amp;selectaction=Edit\u0026amp;uid=U00025OA\u0026amp;ts=2\u0026amp;cx=6itjjg\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll participants consented to data publication.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and material\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was supported by Samsung Electronics (S-2023-0600-000-1)\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026rsquo; contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll authors contributed substantially to the development of this manuscript. SHL, HJL and YHK designed the experiment; SHL, EMK, UJK, DWK and DKL recruited participants and recorded data; SHL, EMK and JUK analyzed and interpreted the results. SHL and HJL created the first draft of the manuscript. YHK and HJL improved results and contributed with improvements in literature review. All authors read and approved the final manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgments\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe thank all participants for volunteering to participate in this study\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026rsquo; information\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eDepartment of Physical and Rehabilitation Medicine, Sungkyunkwan University School of Medicine, Suwon, 16419, Republic of Korea\u003c/p\u003e\n\u003cp\u003eSu-Hyun Lee, Eunmi Kim, Yun-Hee Kim\u003c/p\u003e\n\u003cp\u003eCenter for Neuroscience Imaging Research, Institute for Basic Science, Suwon, 16419, Republic of Korea\u003c/p\u003e\n\u003cp\u003eJinuk Kim\u003c/p\u003e\n\u003cp\u003eRobot Business Team, Samsung Electronics, Suwon, 16677, Republic of Korea\u003c/p\u003e\n\u003cp\u003eDonwoo Kim, Dokwan Lee, Hwang-Jae Lee\u003c/p\u003e\n\u003cp\u003eHaeundae Sharing and Happiness Hospital, Pusan, 612702, Republic of Korea\u003c/p\u003e\n\u003cp\u003eYun-Hee Kim\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eBouchard C, Blair SN, Katzmarzyk PT, editors. 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Sports Med. 2014;44(Suppl 2):139\u0026ndash;47.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":true,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"sports-medicine-open","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"smoa","sideBox":"Learn more about [Sports Medicine-Open](http://sportsmedicine-open.springeropen.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/smoa/default.aspx","title":"Sports Medicine-Open","twitterHandle":"@SpringerOpen","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"aerobic exercise, muscle-strengthening exercise, hip exoskeleton, muscle strength, pelvic symmetry","lastPublishedDoi":"10.21203/rs.3.rs-3998966/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-3998966/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eIntroduction\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003ePhysical inactivity and sedentary behavior both increase the risk of chronic disease and mortality. Regular participation in physical activity and reducing sedentary behavior play important roles in maintaining physical health and disease prevention. The purpose of this study was to investigate the effect of a wearable hip exoskeleton, Bot Fit, on muscle strength, muscle effort, and the kinematics of the pelvis during walking in younger adults.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe designed three parallel experimental conditions and randomly assigned participants to one of three groups: those assigned to exercise using an interval program of Bot Fit (interval group), those who used a power program of Bot Fit (power group), and a control group who exercised without Bot Fit. A total of 45 young adults participated in 18 exercise-intervention sessions over six weeks, and all participants were assessed at two time points: before and after the 18 exercise sessions. Each assessment evaluated muscle strength, muscle effort, and the kinematics of the pelvis during walking. In addition, the number of steps, distance, energy expenditure, and heart rate for 30 min during the exercise sessions were recorded.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA significant increase in the maximum voluntary contraction (MVC) of the right biceps femoris (BF) was evident in the interval group while significant changes in the MVC of the bilateral BF were seen in the power group showed after Bot Fit exercise. A significant decrease of muscle effort in right BF in the interval group and right lumbar erector spinae and bilateral BF in the power group were also observed. In addition, the symmetry index of pelvic tilt significantly improved in the interval group, and greater exercise volume and intensity in both the interval and power groups compared with the control group were confirmed as measured by the number of steps, distance, energy expenditure, and heart rate.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusion\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eResults of this study indicate a beneficial effect of the Bot Fit on muscle strength, walking efficiency, and pelvic movement symmetry in younger adults. Personalized exercise programs using different exercise protocol with the Bot Fit may therefore improve the physical health and gait symmetry of younger adults.\u003c/p\u003e","manuscriptTitle":"Robotic-resisted Exercise for Health Promotion in Younger Adults","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-03-07 19:27:43","doi":"10.21203/rs.3.rs-3998966/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Major Revision","date":"2024-07-14T09:18:05+00:00","index":"","fulltext":""},{"type":"reviewerAgreed","content":"","date":"2024-03-09T12:04:09+00:00","index":0,"fulltext":""},{"type":"reviewersInvited","content":"","date":"2024-03-05T09:33:51+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2024-03-04T01:49:03+00:00","index":"","fulltext":""},{"type":"submitted","content":"Sports Medicine-Open","date":"2024-02-28T00:35:40+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"sports-medicine-open","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"smoa","sideBox":"Learn more about [Sports Medicine-Open](http://sportsmedicine-open.springeropen.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/smoa/default.aspx","title":"Sports Medicine-Open","twitterHandle":"@SpringerOpen","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"17564685-2e4c-4498-a2b0-1fa4ab7b6ac9","owner":[],"postedDate":"March 7th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2024-10-21T16:04:54+00:00","versionOfRecord":{"articleIdentity":"rs-3998966","link":"https://doi.org/10.1186/s40798-024-00773-x","journal":{"identity":"sports-medicine-open","isVorOnly":false,"title":"Sports Medicine-Open"},"publishedOn":"2024-10-14 15:58:05","publishedOnDateReadable":"October 14th, 2024"},"versionCreatedAt":"2024-03-07 19:27:43","video":"","vorDoi":"10.1186/s40798-024-00773-x","vorDoiUrl":"https://doi.org/10.1186/s40798-024-00773-x","workflowStages":[]},"version":"v1","identity":"rs-3998966","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-3998966","identity":"rs-3998966","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}
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