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Abstract Background We hypothesized that postural instability observed in individuals with Parkinson's disease (PD) can be classified as distinct subtypes based on comprehensive analyses of various evaluated parameters obtained from time-series of center of pressure (CoP) data during quiet standing. The aim of this study was to characterize the postural control patterns in PD patients by performing an exploratory factor analysis and subsequent cluster analysis using CoP time-series data during quiet standing. Methods 127 PD patients, 47 aged 65 years or older healthy older adults, and 71 healthy young adults participated in this study. Subjects maintain quiet standing for 30 s on a force platform and 23 variables were calculated from the measured CoP time-series data. Exploratory factor analysis and cluster analysis with a Gaussian mixture model using factors were performed on each variable to classify subgroups based on differences in characteristics of postural instability in PD. Results The factor analysis identified five factors (magnitude of sway, medio-lateral frequency, anterio-posterior frequency, component of high frequency, and closed-loop control). Based on the five extracted factors, six distinct subtypes were identified, which can be considered as subtypes of distinct manifestations of postural disorders in PD patients. Factor loading scores for the clinical classifications (younger, older, and PD severity) overlapped, but the cluster classification scores were clearly separated. Conclusions The cluster categorization clearly identifies symptom-dependent differences in the characteristics of the CoP, suggesting that the detected clusters can be regarded as subtypes of distinct manifestations of postural disorders in patients with PD.

ObjectiveThe aim of this study was to cross-sectionally investigate how static balance changes throughout the aging process in older women aged from their early sixties to their late eighties.MethodsForty-six older women (aged 62–89 years) were requested to stand barefoot and quietly on a force platform for 30 s with their eyes either open or closed. During the trials, the position of the center of foot pressure (CoP) and the acceleration of the body’s center of mass (ACC) were measured. The root mean square (RMS) of the CoP and ACC values was calculated to evaluate the amplitude of postural sway and the level of regulatory activity, respectively. The mean power frequency of the ACC was also calculated to represent the temporal characteristics of regulatory activity.ResultsIn the anterior–posterior direction, there was no significant relationship between the RMS of CoP and the participants’ age, whereas the RMS of ACC significantly increased with increasing age. In the mediolateral direction, however, the RMS of CoP significantly increased with increasing age, whereas the RMS of ACC did not change with age. The mean power frequency of ACC did not exhibit any age-related change in either the anterior–posterior or the mediolateral direction.ConclusionThe results indicate that static balance in older women aged in their early sixties to their late eighties exhibits distinctly contrasting aging patterns between the anterior–posterior and mediolateral directions. To prevent falls in older women, it is necessary to elucidate the physiological mechanisms responsible for the increase in mediolateral sway that occurs throughout old age.

Exoskeleton devices can reduce metabolic cost, increase walking speed, and augment load-carrying capacity. However, little is known about the effects of powered assistance on the sensory information required to achieve these tasks. To learn how to use an assistive device, humans must integrate novel sensory information into their internal model. This process may be disrupted by challenges to the sensory systems used for posture. We investigated the exoskeleton-induced changes to balance performance and sensory integration during quiet standing. We asked 11 unimpaired adults to perform a virtual reality-based test of sensory integration in balance (VRSIB) on two days while wearing the exoskeleton either unpowered, using proportional myoelectric control, or with regular shoes. We measured postural biomechanics, muscle activity, equilibrium scores, postural control strategy, and sensory ratios. Results showed improvement in balance performance when wearing the exoskeleton on firm ground. The opposite occurred when standing on an unstable platform with eyes closed or when the visual information was non-veridical. The balance performance was equivalent when the exoskeleton was powered versus unpowered in all conditions except when both the support surface and the visual information were altered. We argue that in stable ground conditions, the passive stiffness of the device dominates the postural task. In contrast, when the ground becomes unstable the passive stiffness negatively affects balance performance. Furthermore, when the visual input to the user is non-veridical, exoskeleton assistance can magnify erroneous muscle inputs and negatively impact the user’s postural control.

The quiet standing test is used to detect diseases of the postural control system. The descriptive statistics of the center of pressure (COP) of older people during the test tend to be larger than those of healthy young people, but they cannot indicate structural problems in postural control. COP trajectories can be mathematically modeled with structural parameters such as viscosity, stiffness, and stochastic terms; however, the classification accuracy of older and fall-experienced people using such parameters has not been sufficiently verified. In this study, six structural parameters of a mass–spring–damper (MSD) model were estimated using two datasets, in which a total of 212 subjects performed quiet standing tests under four conditions. The estimated parameters were used for classification with a random forest algorithm to examine the differences in classification accuracy compared to seven conventional descriptive statistics methods. For the classification of older subjects, the classification accuracy of the MSD parameter method was the highest in foam condition, with positive likelihood ratios approximately 8.0. For the classification of fall-experienced subjects, the positive likelihood ratio of the MSD parameter method was 5.0, which is better than conventional descriptive statistics. Various MSD parameters revealed that aging and changing the floor surface and visual conditions cause oscillations in the COP behavior. While the MSD parameters were confirmed to help classify older subjects more accurately than the conventional descriptive statistics, there was room for further improvement in the classification accuracy of fall-experienced subjects.

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.

Background: Theoretically, balance is affected by the height of center of mass (COM) during quiet standing. However, no one examined this in humans with variables derived from the center of pressure (COP). Objects: We have conducted balance experiment to measure COP data during quiet standing, in order to examine how the COP measures were affected by the height of COM, vision, floor conditions, and gender. Methods: Twenty individuals stood still with feet together and arms at sides for 30 seconds on a force plate. Trials were acquired with three COM heights: 1% increased or decreased, and not changed, with two vision conditions: eyes closed (EC) and eyes open (EO), and with two floor conditions: unstable (foam pad) and stable (force plate) floor. Outcome variables included the mean distance, root mean square distance, total excursion, mean velocity, and 95% confidence circle area. Results: All outcome variables were associated with the COM height (p < 0.0005), vision (p < 0.0005), and floor condition (p < 0.003). The mean velocity and 95% confidence circle area were 5.7% and 21.8% greater, respectively, in raised COM than in lowered COM (24.6 versus 23.2 mm/s; 1,013.4 versus 832.3 mm2). However, there were no interactions between the COM height and vision condition (p > 0.096), and between the COM height and floor condition (p > 0.183) for all outcome variables. Furthermore, there was no gender difference in all outcome variables (p > 0.186). Conclusion: Balance was affected by the change of COM height induced by a weight belt in human. However, the effect was not affected by vision or floor condition. Our results should inform the design of balance exercise program to improve the outcome of the balance training.

Abstract Background Gymnastics training enhances the development of postural control in children and adolescents. In competitive gymnastics, the training regimen is specific to the given gymnastic discipline and is usually followed from the early years of practicing. This study aimed to determine whether postural steadiness differed between young gymnasts practicing two distinct disciplines, and whether it was related to the duration of their training experience, age, and their anthropometric characteristics. Methods Thirty 10–13-year-old females ̶ ten artistic gymnasts, ten acrobatic gymnasts (training as “tops”), and ten non-athletes ̶ were examined during 60-s quiet standing trials on a force platform with the eyes open and closed. Their postural sway was represented by directional components of centre of foot pressure mean velocity. Mann-Whitney U, Wilcoxon and Spearman’s ρ tests were used for analyses. Results Anterior-posterior and medial-lateral centre of foot pressure mean velocities were not different between the artistic and acrobatic gymnasts (p > 0.05). In the artistic gymnasts, the duration of training experience, age, body height, body mass, and maturity offset were negatively correlated with the anterior-posterior centre of foot pressure mean velocity under eyes-open conditions. The acrobatic gymnasts’ body mass and BMI percentiles were negatively correlated with their anterior-posterior and medial-lateral centre of foot pressure mean velocities under both visual conditions (r ranged from − 0.64 to − 0.93; p 0.05). Conclusions The artistic gymnasts’ longer training experience, greater age, body height, body mass, and biological maturity were associated with better anterior-posterior postural steadiness when vision was available; the acrobatic gymnasts’ greater body mass and BMI percentiles were associated with better overall postural steadiness regardless of visual conditions. Relationships were observed between postural steadiness and discipline-specific training experience and anthropometric characteristics; however, causes and effects were not proven.

A force plate is one of the most popular tools for postural stability assessment. It decomposes the ground reaction force (GRF) applied to the human body into multiple force components to determine the center of pressure (COP), which is the point at which the GRF is applied. Many COP measures have been proposed to characterize postural stability. Despite postural stability being closely related to GRF components, the interactions between them have rarely been studied. By studying the correlation structure of these GRF components, we developed a set of features to assess postural stability. We determined the correlation matrix of these GRF components and subsequently solved the corresponding eigenvalue problem; we used the resulting eigenvalues to characterize postural stability. The effectiveness of the proposed features was demonstrated by using them to differentiate between individuals in two age groups: 18–24 and 65–73 years. Statistical test results showed that the correlation matrix eigenvalues of the two age groups differed significantly. The classification results demonstrated that most of the correlation matrix eigenvalues were more sensitive to age variations than one of the most reliable and accurate conventional COP features. Furthermore, by reducing the force sensing requirement from three-dimensional to one-dimensional by considering only the vertical GRF components, a simplified version of the proposed approach can be obtained, which could reduce the cost of the force plate system substantially.

Elderly and disabled people frequently experience falls that may require early assessment and training. The quiet standing test provides descriptive statistics such as the center of pressure (COP) sway data, which can be used to analyze the decline in balance ability. Generally, higher descriptive statistics indicate lower balance ability. Stochastic models can model COP trajectories, and such equation parameters were previously used to assess the balance of patients. However, the model equation is a hypothesis and should be verified. In this study, we evaluated whether stochastic models can predict the descriptive statistics of observed COP trajectories. We estimated the model parameters by fitting postural sway data from 49 individuals in four linear stochastic models, and the prediction accuracy was verified by comparing the observed descriptive statistics with the predicted COP trajectories. We observed that the prediction accuracy of the models with stiffness was much higher than those with viscosity only, and the models with the center of mass (COM) had higher prediction accuracy than COP-only models. Therefore, we identified that coefficients from Langevin-based models contained descriptive statistics about a subject’s COP trajectory, which suggested that these coefficients can be used to effectively assess balance issues.

The purpose of this study was to examine the effects of occasional and habitual wearing of high-heeled shoes on static balance in young women. Groups of habitual high-heel wearers and non-wearers (n = 7 in both groups) were asked to stand quietly on a force platform without shoes (WS condition) or with high heels (heel area 1 cm2, heel height 7 cm) (HH condition). During the trials, the center-of-pressure (CoP) position in the anterior-posterior direction was measured, and its root mean square (as a measure of postural sway magnitude, CoPRMS) and mean velocity (as a measure of regulatory activity, CoPMV) were calculated. To further examine the effect of high-heel wearing on the temporal aspects of slow and fast processes in static balance, the CoP sway was decomposed into low- (below 0.5 Hz) and high- (above 0.5 Hz) frequency components, and then spectral analysis was performed. Results showed that the CoPRMS was not significantly different between the groups or between the shoe conditions, indicating that wearing high heels with a heel height of 7 cm did not increase the magnitude of postural sway, irrespective of high-heel experience. The CoPMV was significantly larger in the HH condition than in the WS condition, whereas it was not significantly different between the groups. This result indicates that wearing high heels increased the amount of regulatory activity in both habitual wearers and non-wearers. The spectral analysis further showed that habitual high-heel wearers showed significantly decreased rate of regulatory activity than non-wearers, both while standing with and without high heels. These results suggest that use-dependent changes in static balance control are evident in both high-heeled and without shoes conditions.

Background: In this study, three detecting approaches have been proposed and evaluated for online detection of balance situations during quiet standing. The applied methods were based on electromyography of the gastrocnemius muscles adopting the hidden Markov models. Methods: The levels of postural stability during quiet standing were regarded as the hidden states of the Markov models while the zones in which the center of pressure lies within determines the level of stability. The Markov models were trained by using the well-known Baum-Welch algorithm. The performance of a single hidden Markov model, the multiple hidden Markov model, and the multiple hidden Markov model alongside an adaptive neuro-fuzzy inference system (ANFIS), were compared as three different detecting methods. Results: The obtained results show the better and more promising performance of the method designed based on a combination of the hidden Markov models and optimized neuro-fuzzy system. Conclusion: According to the results, using the combined detecting method yielded promising results.

Abstract Postural control is often quantified by recording the trajectory of the center of pressure (COP)—also called stabilogram—during human quiet standing. This quantification has many important applications, such as the early detection of balance degradation to prevent falls, a crucial task whose relevance increases with the aging of the population. Due to the complexity of the quantification process, the analyses of sway patterns have been performed empirically using a number of variables, such as ellipse confidence area or mean velocity. This study reviews and compares a wide range of state‐of‐the‐art variables that are used to assess the risk of fall in elderly from a stabilogram. When appropriate, we discuss the hypothesis and mathematical assumptions that underlie these variables, and we propose a reproducible method to compute each of them. Additionally, we provide a statistical description of their behavior on two datasets recorded in two elderly populations and with different protocols, to hint at typical values of these variables. First, the balance of 133 elderly individuals, including 32 fallers, was measured on a relatively inexpensive, portable force platform (Wii Balance Board, Nintendo) with a 25‐s open‐eyes protocol. Second, the recordings of 76 elderly individuals, from an open access database commonly used to test static balance analyses, were used to compute the values of the variables on 60‐s eyes‐open recordings with a research laboratory standard force platform.

Abstract Background Falling is the most common accident of daily living and the second most prevalent cause of accidental death in the world. The complex nature of risk factors associated with falling makes those at risk amongst the elderly population difficult to identify. Commonly used clinical tests have limitations when it comes to reliably detecting the risk of falling, but existing laboratory tests, such as force platform measurements, represent one method of overcoming this lack of a test. Despite their widespread use, however, Center of Pressure (COP) signal analysis techniques vary and there is currently no consensus on which features should be used diagnostically. Our objective is to identify, through a systematic review and meta-analysis, the COP characteristics of older adults (≥ 60 years old) during quiet bipedal stance which will allow fallers to be distinguished from non-fallers. Methods The systematic review will include both prospective and retrospective articles. Five databases will be searched: PubMed, Cochrane CENTRAL, EMBASE, and ScienceDirect. In addition, a search of gray literature will be performed using Google Scholar and ClinicalTrials.gov. Searches will be circumscribed to include only older adults (aged over 60 years) who underwent a bipedal quiet standing measure of their balance and for whom the number of falls was reported. Two authors will independently assess the risk of bias for each included article using a 26-item checklist. Funnel plots will be drawn to attest of possible publication biases for each COP parameters. The results will be synthesized descriptively and a meta-analysis will be undertaken. When trial methodological heterogeneity is too great for pooling of the data into a meta-analysis, evidence strength will be evaluated using best evidence analysis. Discussion Despite the numerous advantages of posturography, the diversity of studies exploring balance in older fallers has led to uncertainty regarding the method’s ability to reliably identify fall-prone older adults. It is expected that the findings from this systematic review will help clinicians use bipedal quiet standing measures as a diagnostic test and allow researchers to explore COP characteristics to create better models for fall prevention care. Systematic review registration PROSPERO CRD42018098671

Purpose: Predicting body Center of Mass (COM) acceleration is carried out with more accuracy based on the acceleration of three joints of lower limb compared to only accounting joints of hip and ankle. Given that trunk movement during quite standing is noticeable, calculating trunk acceleration in model might increase prediction accuracy of COM acceleration. Moreover, in previous research studies, dominant and nondominant limb was neglected as influencing variables in prediction accuracy. Therefore, this study aimed to investigate the accuracy of predicting COM acceleration based on the accelerations of lower limb joints and trunk, with emphasis on weight distribution on legs. Methods: The relevant kinematic data were collected using motion analysis systems. In this regard, visual 3D software was used to create a 14-segment model for each subject and estimate the positions of body COM. A force plate was used to assess the body weight distribution between legs. Calculation of the summation of joints angular accelerations was done using algebraic addition of time series data. Results: Prediction of COM acceleration, based on the individual acceleration of lower limb joints and trunk, revealed that just acceleration of hip joint in both dominant and nondominant lower limbs was an appropriate variable for predicting COM acceleration (R2adj =0.40). However, during prediction based on the summation of trunk and joints accelerations, its accuracy showed a significant increase (R2adj=0.90). Conclusion: The summation of angular accelerations of trunk and lower limb joints is the most accurate predictor of COM acceleration during quiet standing balance control. Simultaneous changes of lower limb joints and trunk accelerations control COM acceleration.

In this study, we investigated the fluctuation characteristics of micro vertical acceleration of center of mass (vCOMacc) in standing and examined the usefulness of vCOMacc as an aging marker for standing control abilities. Sixteen young and 18 older adults participated in this experiment. Data for vCOMacc were calculated as the vertical ground reaction force value divided by each participant’s body mass using a force plate. The COMacc frequency structure was determined using the continuous wavelet transform to analyze the relative frequency characteristics. For time domain analysis, we determined the root mean square (RMS) and maximum amplitude (MA) of the integrated power spectral density. We also analyzed the correlation between vCOMacc and lower limb muscle activity. The relative frequency band of vCOMacc was higher in older than young adults, and the time domain indicators were sufficient to distinguish the effects of aging. Regarding the relationship between vCOMacc during standing and muscle activity, a correlation was found with the soleus muscle in young adults, while it was moderately correlated with the gastrocnemius muscle in older adults. The cause of vCOM may be related to differences in muscle activity, and vCOMacc may be utilized to more easily assess the effects of aging in standing control.

The center of pressure (COP), which is defined as the point at which the resultant ground reaction force (GRF) is applied on a body, provides valuable information for postural stability assessment. This is because the fundamental goal of balance control is to regulate the center of mass (COM) of the human body by adaptively changing the position of the COP. By using Newtonian mechanics to develop two equations that relate the two-dimensional COP coordinates to the GRF components, one can easily determine the location of the COP using a force plate. An important property of these two equations is that for a given COP position, there exists an infinite number of GRF component combinations that can satisfy these two equations. However, the manner in which a postural control system deals with such redundancy is still unclear. To address this redundancy problem, we introduce four postural stability features by quantifying the coupling strengths between the COP coordinates and their GRF components. Experiments involving younger (18–24 years old) and older (65–73 years) participants were conducted. The efficacy of the proposed features was demonstrated by comparing the differences between variants of each feature for each age group (18–24 and 65–73 years). The results demonstrated that the coupling strengths between the anterior–posterior (AP) direction coordinate of the COP and its GRF components for the older group were significantly higher than those of the younger group. These experimental results suggest that (1) the balance control system of the older group is more constrained than that of the younger group in coordinating the GRF components and (2) the proposed features are more sensitive to age variations than one of the most reliable and accurate conventional COP features. The best testing classification accuracy achieved by the proposed features was 0.883, whereas the testing classification accuracy achieved by the most accurate conventional COP feature was 0.777. Finally, by investigating the interactions between the COP and its GRF components using the proposed features, we found that that the AP component of the GRF of younger people plays a more active role in balance control than that of the GRF of older people. Based on these findings, it is believed that the proposed features can be used as a set of stability measures to assess the effects on posture stability from various health-related conditions such as aging and fall risk.

Standing balance relies on the integration of multiple sensory inputs to generate the motor commands required to stand. Mechanical and sensory perturbations elicit compensatory postural responses that are interpreted as a window into the sensorimotor processing involved in balance control. Popular methods involve imposed external perturbations that disrupt the control of quiet stance. Although these approaches provide critical information on how the balance system responds to external disturbances, the control mechanisms involved in correcting for these errors may differ from those responsible for the regulation of quiet standing. Alternative approaches use manipulations of the balance control loop to alter the relationship between sensory and motor cues. Coupled with imposed perturbations, these manipulations of the balance control loop provide unique opportunities to reveal how sensory and motor signals are integrated to control the upright body. In this review, we first explore imposed perturbation approaches that have been used to investigate the neural control of standing balance. We emphasize imposed perturbations that only elicit balance responses when the disturbing stimuli are relevant to the balance task. Next, we highlight manipulations of the balance control loop that, when carefully implemented, replicate and/or alter the sensorimotor dynamics of quiet standing. We further describe how manipulations of the balance control loop can be used in combination with imposed perturbations to characterize mechanistic principles underlying the control of standing balance. We propose that recent developments in the use of robotics and sensory manipulations will continue to enable new possibilities for simulating and/or altering the sensorimotor control of standing beyond compensatory responses to imposed external perturbations.

The purpose of the study was to analyze the parameters of the autocorrelation function when assessing time series ground reaction force (GRF) signals during quiet standing. GRF in the three directions were recorded on two Kistler force plates during three 15-s trials in a sample of 82 (31 females and 51 males) participants. Autocorrelation was performed on the GRF data and four parameters characterizing the function were computed. Comparisons of the right- and left-foot parameter means showed significant differences in mediolateral GRF for the time of the function's decay to 0, magnitude of the derivative output, and mean decay velocity to the extremum. Significant correlations were observed among all parameters – weak correlations between the time of the function's decay to 0 and the time to the first extremum and strong correlations between the derivative output and mean decay velocity to the extremum. The analyzed autocorrelation function parameters can serve as a precise measure of the motor control process during quiet standing. The strong correlations observed between the four parameters indicate that they evaluate similar properties of the central nervous system as a regulator of balance maintenance.

Even though frequency analysis of body sway is widely applied in clinical studies, the lack of standardized procedures concerning power spectrum estimation may provide unreliable descriptors. Stabilometric tests were applied to 35 subjects (20-51 years, 54-95 kg, 1.6-1.9 m) and the power spectral density function was estimated for the anterior-posterior center of pressure time series. The median frequency was compared between power spectra estimated according to signal partitioning, sampling rate, test duration, and detrending methods. The median frequency reliability for different test durations was assessed using the intraclass correlation coefficient. When increasing number of segments, shortening test duration or applying linear detrending, the median frequency values increased significantly up to 137%. Even the shortest test duration provided reliable estimates as observed with the intraclass coefficient (0.74-0.89 confidence interval for a single 20-s test). Clinical assessment of balance may benefit from a standardized protocol for center of pressure spectral analysis that provides an adequate relationship between resolution and variance. An algorithm to estimate center of pressure power density spectrum is also proposed.

The ability to stand quietly is disturbed by degradation of cerebellar systems. Given the complexity of sensorimotor integration invoked to maintain upright posture, the integrity of supratentorial brain structures may also contribute to quiet standing and consequently be vulnerable to interference from cognitive challenges. As cerebellar system disruption is a common concomitant of alcoholism, we examined 46 alcoholics and 43 controls with a force platform to derive physiological indices of quiet standing during cognitive (solving simple, mental arithmetic problems) and visual (eyes closed) challenges. Also tested were relations between tremor velocity and regional gray matter and white matter tissue quality measured with the diffusion tensor imaging (DTI) metric of mean diffusivity (MD), indexing disorganized microstructure. Spectral analysis of sway revealed greater tremor in alcoholic men than alcoholic women or controls. Cognitive dual-tasking elicited excessive tremor in two frequency bands, each related to DTI signs of degradation in separate brain systems: tremor velocity at a low power (2-5 Hz/0-2 Hz) correlated with higher MD in the cerebellar hemispheres and superior cingulate bundles, whereas tremor velocity at a higher power (5-7 Hz) correlated with higher MD in the motor cortex and internal capsule. These brain sites may represent tremorgenic networks that when disturbed by disease and exacerbated by cognitive dual-tasking contribute to postural instability, putting affected individuals at heightened risk for falling.