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Background: The coronavirus disease 2019 (COVID-19) pandemic has restricted people’s activities and necessitated the discontinuation of cardiac rehabilitation (CR) programs for outpatients. In our hospital, CR for outpatients had to be discontinued for 3 months. We investigated the influence of this discontinuation of CR on physical activity, body composition, and dietary intake in cardiovascular outpatients. Method: Seventy-eight outpatients who restarted CR were investigated. We measured body composition, balance test, stage of locomotive syndrome, and food frequency questionnaire (FFQ) results at restart and 3 months later. We also investigated the results of examination that were obtained before discontinuation. Results: With regard to baseline characteristics, the percentage of male was 62.7% (n = 49), and average age and body mass index were 74.1 ± 8.5 years and 24.9 ± 7.0 kg/m2, respectively. Stage of locomotive syndrome and the results of FFQ did not change significantly. The one-leg standing time with eyes open test significantly worsened at restart (p < 0.001) and significantly improved 3 months later (p = 0.007). With regard to body composition, all limb muscle masses were decreased at restart and decreased even further 3 months later. Conclusions: Discontinuation of CR influenced standing balance and limb muscle mass. While the restart of CR may improve a patient’s balance, more time is required for additional daily physical activities. The recent pandemic-related interruption of CR should inspire the development of alternatives that could ensure the continuity of CR in a future crisis.

Virtual time-to-contact (VTC) is a promising approach for investigating postural balance control. However, current VTC calculation approaches are limited as they (1) cannot be used to evaluate directional components of balance, and (2) only assess a single, temporal aspect of balance control. This study introduces a new approach for VTC calculation, namely directional VTC, expanding VTC to assess temporal, spatial, and control aspects of balance. Three case studies were conducted across varying populations and conditions as a proof-of-concept of the presented method. The first study examined quiet stance on a firm surface in people with Parkinson’s disease (PD; n = 10) in comparison to their healthy peers (n = 10). The second and third studies assessed balance control of healthy individuals under challenging environments. Ten healthy individuals participated in standing tasks on compliant ground surfaces, while another ten on oscillatory ground surfaces, all simulated by a dual-axis robotic platform. Preliminary results not only provided a closer look at balance control with multiple aspects, including temporal, spatial, and control aspects, but also showed how different aspects of balance changed due to neurological diseases (Case Study I) or challenging standing grounds (Case Studies II and III). This study advances our understanding of posture biomechanics and its clinical applications.

Accurate estimation of the center of mass is necessary for evaluating balance control during quiet standing. However, no practical center of mass estimation method exists because of problems with estimation accuracy and theoretical validity in previous studies that used force platforms or inertial sensors. This study aimed to develop a method for estimating the center of mass displacement and velocity based on equations of motion describing the standing human body. This method uses a force platform under the feet and an inertial sensor on the head and is applicable when the support surface moves horizontally. We compared the center of mass estimation accuracy of the proposed method with those of other methods in previous studies using estimates from the optical motion capture system as the true value. The results indicate that the present method has high accuracy in quiet standing, ankle motion, hip motion, and support surface swaying in anteroposterior and mediolateral directions. The present method could help researchers and clinicians to develop more accurate and effective balance evaluation methods.

Purpose To elucidate the normative values of whole body sagittal alignment and balance of a healthy population in the standing position; and to clarify the relationship among the alignment, balance, health-related quality of life (HRQOL), and age. Methods Healthy Japanese adult volunteers [ n  = 126, mean age 39.4 years (20–69), M/F = 30/96] with no history of spinal disease were enrolled in a cross-sectional cohort study. The Oswestry Disability Index (ODI) questionnaire was administered and subjects were scanned from the center of the acoustic meati (CAM) to the feet while standing on a force plate to determine the gravity line (GL), and the distance between CAM and GL (CAM–GL) was measured in the sagittal plane. Standard X-ray parameters were measured from the head to the lower extremities. ODI was compared among age groups stratified by decade. Correlations were investigated by simple linear regression analysis. Ideal lumbar lordosis was investigated using the least squares method. Results The present study yielded normative values for whole standing sagittal alignment including head and lower extremities in a cohort of 126 healthy adult volunteers, comparable to previous reports and thus a formula for ideal lumbar lordosis was deduced: LL = 32.9 + 0.60 × PI − 0.23 × age. There was a tendency of positive correlation between McGregor slope, thoracic kyphosis, PT, and age. SVA, T1 pelvic angle, sacrofemoral angle, knee flexion angle, and ankle flexion angle, but not CAM–GL, increased with age, suggesting that the spinopelvic alignment changes with age, but standing whole body alignment is compensated for to preserve a horizontal gaze. ODI tended to increase from the 40s in the domain of pain intensity, personal care, traveling, and total score. ODI weakly, but significantly positively correlated with age and PI–LL. Conclusion Whole body standing alignment even in healthy subjects gradually deteriorates with age, but is compensated to preserve a horizontal gaze. HRQOL is also affected by aging and spinopelvic malalignment.

Background Effective balance rehabilitation requires training at an appropriate level of exercise intensity given an individual’s needs and abilities. Typically balance intensity is assessed through in-clinic visual observation by physical therapists (PTs), which limits the ability to monitor and progress intensity during home-based components of training programs. The goal of this study was to train and evaluate machine learning models for estimating physical therapists’ perceived balance exercise intensity using data from full-body wearable sensors to support the development of home-based training exercise dosage monitoring. Methods Balance exercise participants ( n  = 47) participated in a single-day balance training session where they were filmed performing static standing exercises at various levels of intensity. Kinematic data from 13 full-body wearable inertial measurement units (IMUs) and self-ratings of balance intensity were also collected. An additional cohort of PT participants ( n  = 42) was recruited to watch the videos of the balance exercise participants and provide ratings of balance intensity. The mean PT rating for each video was used as a ground truth (GT) label of balance intensity. We trained and evaluated Convolutional Neural Networks (CNN)-based models to predict balance intensity based on performance as captured through the IMUs. Model performance was evaluated by calculating the root-mean-square error (RMSE) of predications. A sensitivity analysis was also performed to assess the effect of the number of IMUs used on model performance. Results Models trained on orientation derived from all 13 IMUs achieved good predictive performance as indicated by a RMSE of 0.66 [0.62, 0.69], which was within the threshold defined by typical inter-rater variabilities between PTs (RMSE of 0.74 [0.72, 0.76]). Sensitivity analysis indicated that model performance stabilized at four sensors with the best performance corresponding to sensors placed on both thighs and the lower and upper back. Conclusions Findings from this study indicated that balance intensity assessment can be achieved through wearable sensors and a CNN model, which could support the supervision and effectiveness of home-based balance rehabilitation.

Age-related hearing loss is a risk factor for mobility problems and falls, possibly due to poor access to spatial sounds or the higher allocation of attention required to listen, thereby reducing cognitive resources to support mobility. Introducing stabilizing spatial sounds or reducing cognitive load through hearing aids could possibly improve balance performance; however, evidence is mixed. Few studies have evaluated the effects of hearing aids and spatial sounds on balance during realistic, multisensory, dual-tasking conditions. This study used virtual reality to simulate a listening-while-balancing task in 22 older adults with normal hearing and 22 hearing aid users, tested with their aids on versus off. Participants performed a competing digits listening task (two, four digits) and a standing postural task, alone and in combination (dual task) under different visual, postural, and acoustical loads. Listening accuracy and postural outcomes (centre of pressure mean velocity, anterior–posterior standard deviation, medial–lateral standard deviation) were collected. With respect to listening accuracy, as expected, normal hearing adults had higher listening accuracy than those with hearing loss (aided better than unaided) and both groups performed better with eyes closed (vs. open) and under lower postural loads (firm vs. compliant). With respect to postural performance, hearing aids did not remarkably improve balance overall, with no effects on dual-task costs to posture. Other factors related to the complexity of the conditions (i.e., listening, visual, postural demands) differently influenced dual-task costs to posture in individuals with and without hearing loss. Overall, these results contribute to our understanding of how age-related hearing loss and hearing aids affect balance-related outcomes under realistic, complex, multisensory, multitasking conditions.

BackgroundIdentification of simple screening tools for detecting lower skeletal muscle mass may be beneficial for planning effective interventions in the elderly.AimsWe aimed to (1) establish a threshold for one-leg standing balance test (OLST) time for low muscle mass, and (2) test the ability of that threshold to assess muscular impairments in a poor balance group.MethodsEyes-open OLST (maximum duration 30 s) was performed with right and left legs in 291 women (age 71 ± 6 years). OLST time was calculated as the sum of the OLST time of right and left legs. Fat-free mass (FFM), skeletal muscle mass (SMM), fat mass, biceps brachii and vastus lateralis sizes; handgrip strength (HGS), elbow flexion maximum torque (MVCEF) and knee extension maximum torque (MVCKE) were measured. Muscle quality was calculated as MVCKE/FFM and physical activity was assessed by questionnaire. Low muscle mass was defined as SMMrelative of 22.1%, a previously established threshold for pre-sarcopenia.ResultsThe OLST threshold time to detect low muscle mass was 55 s (sensitivity: 0.63; specificity: 0.60). The poor balance group (OLST < 55 s) had higher fat mass (3.0%, p < 0.001), larger VL thickness (5.1%, p = 0.016), and lower HGS (− 10.2%, p < 0.001), MVCEF (− 8.2%, p = 0.003), MVCKE (− 9.5%, p = 0.012), MVCKE/FFM (− 11.0%, p = 0.004) and physical activity (− 8.0%, p = 0.024) compared to the normal balance group. While after adjusting age, the differences exist for HGS, fat mass and VL thickness only.DiscussionAn OLST threshold of 55 s calculated as the summed score from both legs discriminated pre-sarcopenic characteristics among active, community-dwelling older women with limited potential (sensitivity 0.63, specificity 0.60).ConclusionOLST, which can be performed easily in community settings without the need for more complex muscle mass measurement, may help identify women at risk of developing sarcopenia.

Whole-body vestibular-evoked balance responses decrease following ~ 55 min of normobaric hypoxia. It is unclear how longer durations of hypoxia affect the vestibular control of balance at the muscle and whole-body levels. This study examined how four hours of normobaric hypoxia influenced the vestibular control of balance. Fifteen participants (4 females; 11 males) stood on a force plate with vision occluded and head rotated rightward while subjected to three blocks of binaural, bipolar stochastic electrical vestibular stimulation (EVS; 0–25 Hz, root mean square amplitude = 1.1 mA) consisting of two, 90-s trials. The relationship between EVS and anteroposterior (AP) forces or medial gastrocnemius (MG) electromyography (EMG) was estimated in the time and frequency domains at baseline (BL; 0.21 fraction of inspired oxygen—FIO2) and following two (H2) and four (H4) hours of normobaric hypoxia (0.11 FIO2). The EVS-MG EMG short-latency peak and peak-to-peak amplitudes were smaller than BL at H2 and H4, but the medium-latency peak amplitude was only lower at H4. The EVS-AP force medium-latency peak amplitude was lower than BL at H4, but the short-latency peak and peak-to-amplitudes were unchanged. The EVS-MG EMG coherence and gain were reduced compared to BL at H2 and H4 across multiple frequencies ≥ 7 Hz, whereas EVS-AP force coherence was blunted at H4 (≤ 4 Hz), but gain was unaffected. Overall, the central nervous system’s response to vestibular-driven signals during quiet standing was decreased for up to four hours of normobaric hypoxia, and vestibular-evoked responses recorded within postural muscles may be more sensitive than the whole-body response.

In this scholarly investigation, the study focuses on scrutinizing the locomotion and control mechanisms governing a single-legged robot. The analysis encompasses the robot’s movement dynamics pertaining to two primary objectives: executing jumps and sustaining equilibrium throughout successive jump sequences. Diverse concepts of this robot model have been scrutinized, leading to the introduction of a distinctive semi-active model devised for maintaining the robot’s balance. The research involves an initial design for the robot model followed by the introduction of a multi-phase composite control system. As per the proposed model, the jumping action is facilitated through a four-link mechanism augmented by a spring, while balance preservation is achieved through the independent operation of two arms connected to the upper body. To address the successive jumps within the four-link mechanism, a multi-phase feedback controller is engineered. Additionally, a hybrid control strategy, incorporating the Deep Deterministic Policy Gradient algorithm (DDPG) along with a feedback controller, is proposed to sustain balance throughout the robot’s contact and flight phases. The research outcomes, acquired through a series of comprehensive tests conducted within the Simulink simulator environment, demonstrate the robot’s capacity to maintain balance over 80 consecutive jumps. The evaluations encompassed various simulated external disturbances, including 1- horizontal impacts on the upper body, 2- disparities in ground height, and 3- alterations in ground angle between consecutive steps. Notably, the findings showcase the robot’s adeptness in maintaining balance despite an impact with an amplitude of 25 N for a duration of 0.1 seconds, as well as its resilience in managing ground height disparities up to 3 cm and ground angle variations of up to 3°.

Standing balance deficits are prevalent after concussions and have also been reported after subconcussive head impacts. However, the mechanisms underlying such deficits are not fully understood. The objective of this review is to consolidate evidence linking head impact biomechanics to standing balance deficits. Mechanical energy transferred to the head during impacts may deform neural and sensory components involved in the control of standing balance. From our review of acute balance-related changes, concussions frequently resulted in increased magnitude but reduced complexity of postural sway, while subconcussive studies showed inconsistent outcomes. Although vestibular and visual symptoms are common, potential injury to these sensors and their neural pathways are often neglected in biomechanics analyses. While current evidence implies a link between tissue deformations in deep brain regions including the brainstem and common post-concussion balance-related deficits, this link has not been adequately investigated. Key limitations in current studies include inadequate balance sampling duration, varying test time points, and lack of head impact biomechanics measurements. Future investigations should also employ targeted quantitative methods to probe the sensorimotor and neural components underlying balance control. A deeper understanding of the specific injury mechanisms will inform diagnosis and management of balance deficits after concussions and subconcussive head impact exposure.