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Context: Chronic ankle instability (CAI) is associated with a less flexible and adaptable sensorimotor system. Thus, individuals with CAI may present an inadequate sensory reweighting system, inhibiting their ability to place more emphasis (upweight) on reliable sensory feedback to control posture. However, how individuals with CAI reweight sensory feedback to maintain postural control in bilateral and unilateral stances has not been established., Objectives: To examine (1) group differences in how the sensory reweighting system changes to control posture in a simple double-limb stance and a more complex single-limb stance (uninjured limb and injured limb) under increased environmental constraints manipulating somatosensory and visual information for individuals with and without CAI and (2) the effect of environmental and task constraints on postural control., Design: Case-control study., Setting: Laboratory., Patients or Other Participants: A total of 21 individuals with CAI (age = 26.4 ± 5.7 years, height = 171.2 ± 9.8 cm, mass = 76.6 ± 15.17 kg) and 21 individuals without CAI (control group; age = 25.8 ± 5.7 years, height = 169.5 ± 9.5 cm, mass = 72.4 ± 15.0 kg) participated., Main Outcome Measure(s): We examined the equilibrium scores based on the first 10 seconds of trials in which participants completed 6 environmental conditions of the Sensory Organization Test during 3 tasks (double-limb and single-limb [uninjured and injured] stances). Sensory reweighting ratios for sensory systems (somatosensory, vision, and vestibular) were computed from paired equilibrium scores based on the first 10 seconds of the trials., Results: We observed 3-factor interactions between groups, sensory systems, and tasks (F4,160 = 3.754, P = .006) and for group, task, and environment (F10,400 = 2.455, P = .007). The CAI group did not downweight vestibular feedback compared with the control group while maintaining posture on the injured limb (P = .03). The CAI group demonstrated better postural stability than the control group while standing with absent vision (ie, eyes closed), fixed surroundings, and a moving platform on the injured limb (P = .03)., Conclusions: The CAI group relied on vestibular feedback while maintaining better postural stability than the control group in injured-limb stance. Group differences in postural control depended on both environmental (absent vision and moving platform) and task (injured limb) constraints., (© by the National Athletic Trainers’ Association, Inc.)

Background: Assessing postural control is important for the assessment of motor function after concussion. Data used for postural control assessment typically do not take the sport played, age, or sex of the athlete into consideration. It is plausible these variables may be significant when making return-to-play decisions., Research Question: This study used the BTrackS database to examine differences in postural control in athletes playing different types of sports and across sex and age., Methods: BTrackS data from 9093 high school to college-aged athletes (aged 14-22 years) were examined employing a One-way ANOVA with a post-hoc test to compare CoP path length between sport types. A moderation analysis was used to test interaction effects of sex and age on a CoP/BMI ratio., Results: Significant differences were observed between sport types, F(3,9089) = 42.4, p <.001, η2 = 0.014. Post hoc tests indicated that collision (M = 25.0, SD = 7.6) sport athletes exhibited significantly higher CoP measures compared to the contact (M = 23.4, SD = 7.4), limited contact (M = 22.9, SD = 6.9), and non-contact (M = 23.0, SD = 7.4) athletes. There was no difference between other sport types (p >.20). A significant mean sex difference (Mmale = 0.924, Mfemale = 0.898, p <.001) and a quadratic association with age, (β = -0.042, p <.001) was observed. Further, magnitude of those age differences decreased with age (β = 0.011, p <.001). An interaction of age and sex was significant for linear (β = 0.020, p <.001) and quadratic terms (β = -0.006, p <.001)., Significance: Athletes exhibited different postural control when the type of sport, age, and sex was taken into consideration. This data possess clinical significance as this suggests that normative postural control data for collision sport athletes should be derived from data based upon type of sport played, age, and sex of the athlete., Competing Interests: Declaration of Competing Interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests:Daniel J. Goble reports financial support was provided by Balance Tracking Systems, Inc. Daniel J. Goble reports a relationship with Balance Tracking Systems, Inc. that includes: equity or stocks. Daniel J. Goble has patent #10,660,558,2020 issued to Daniel J. Goble. DJG is eligible for royalties from a patent (US Patent 10,660,558,2020) related to the technology used in this study. In addition, he has an equity stake (stock options) in Balance Tracking Systems, Inc. This financial conflict of interest is mitigated by a management plan put in place by his academic institution to ensure the integrity of his research.The other authors of this manuscript report no conflicts of interest in this work. If there are other authors, they declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper, (Copyright © 2024 Elsevier B.V. All rights reserved.)

Background: The development of stable postural control is characterized by changes in sway variability and periods of rapid reorganization of motor system components., Research Question: The current study examined whether changing biomechanical and perceptual demands influences the postural control behavior during development., Method: The center of pressure (COP) was assessed via a cross-sectional design. Data were collected from 48 females in three age groups (late childhood, mid-adolescence, and young adulthood) during four quiet stance conditions: (1) eyes open with feet apart, (2) eyes open with feet together, (3) eyes closed with feet apart, and (4) eyes closed with feet together. Linear measures included total path length of the COP and the mean/standard deviation of the overall COP position and speed. To characterize the sway patterns via nonlinear analyses, the speed and two-dimensional positional time series were submitted to sample entropy and Renyi entropy, respectively., Results: The linear results indicated that the late childhood group displayed longer COP trajectories (p < .001) and faster and more variable COP speed (p's < .001). These results held for both the feet apart and feet together conditions, independent of vision. The nonlinear results indicated that the late childhood group exhibited less regularity, overall, in their COP sway position (i.e., Renyi entropy) compared to the two older groups in the feet apart condition (p's ≤ .041), and to the young adults in the feet together condition, independent of vision (p <  .001). However, the mid-adolescent group demonstrated greater regularity in their COP speed (i.e., sample entropy) when their eyes were closed compared to the other two groups, independent of stance (p's < .05)., Significance: The linear results support previous findings, while the nonlinear measures indicate sway characteristics that may provide a window into the development of underlying control processes that regulate quiet standing., (Copyright © 2021 Elsevier B.V. All rights reserved.)

Context: Previous work suggests that balance behavior is a sex-dependent, complex process that can be characterized by linear and nonlinear metrics. Although a certain degree of center of pressure variability may be expected based on sexual dimorphism, there is evidence to suggest that these effects are obscured by potential interactions between sex and anthropometric factors. To date, no study has accounted for such interactive effects using both linear and nonlinear measures., Objective: This investigation sought to analyze interactive models featuring sex, height, and weight as predictors of linear and nonlinear aspects of postural control., Design: Cross-sectional study., Setting: Controlled laboratory., Participants: A total of 26 males (23.80 [3.44] y, 177.87 [6.44] cm, 81.70 [10.80] kg) and 28 females (21.14 [2.03] y, 169.57 [8.80] cm, 64.48 [8.86] kg) were sampled from a healthy university population., Main Outcome Measures: Linear (range [RNG], velocity [VEL], and SD) and nonlinear (detrended fluctuation analysis scaling exponent, multivariate multiscale sample entropy [MMSECI]) summary metrics of center of pressure time series., Procedure: Participants stood on a force plate for 20 seconds in 3 conditions: double (D), single (S), and tandem (T) stance. Data for each stance condition were analyzed using regression models with interaction terms for sex × height and sex × weight. In D, weight had a positive, significant main effect on VELy, MMSECId, and MMSECIv. In men, height was observed to have a positive effect on SDy (S), RNGy (S), and RNGx (T) and a negative effect on MMSECIv (T). In women, weight was observed to have a positive effect on SDy and VELx (both T)., Conclusions: Our findings suggest that men and women differ with respect to certain linear and nonlinear aspects of balance behavior, and that these differences may reflect sex-specific behavioral patterns in addition to effects related to sexual dimorphism.

Falls in older adults are a public health challenge due to their influence on well-being and health-care costs. One way to address this challenge is to discover new methods to enhance postural control in older adults so they are better prepared to maintain an upright stance. Older and younger adults (N = 32) performed a static balance task on a force plate with no instructions, internal focus instructions, or external focus instructions. Center of pressure displacement time series were analyzed using sample entropy and standard deviation. Only the external focus condition significantly increased postural control entropy, which was observed across both age groups. This study showed that an external focus of attention can be used to increase postural control entropy within a single session of testing.

Context: Predicting and promoting physical performance are important goals within the tactical professional community. Movement screens are frequently used in this capacity but are poor predictors of performance outcomes. It has recently been shown that prediction improved when movement quality was evaluated under load, but the mechanisms underlying this improvement remain unclear. Because balance, range of motion, and strength are mutually relevant to physical performance and movement quality, these attributes may mediate load-related decreases in movement quality and account for the resulting increase in performance prediction., Objective: To quantify the roles of balance, range of motion, and strength in mediating load-related decreases in clinical movement-screen scores., Design: Crossover study., Setting: Research laboratory., Patients or Other Participants: Twenty-five male (age = 23.96 ± 3.74 years, height = 178.82 ± 7.51 cm, mass = 79.66 ± 12.66 kg) and 25 female (age = 22.00 ± 2.02 years, height = 165.40 ± 10.24 cm, mass = 63.98 ± 11.07 kg) recreationally active adults., Intervention(s): Participants completed a clinical movement screen under a control condition and while wearing an 18.10-kg weighted vest as well as tests of balance, range of motion, and strength., Main Outcome Measure(s): Item score differences were assessed using Wilcoxon signed rank tests for matched pairs. Interactions between (1) balance, range of motion, and strength and (2) load condition were modeled using penalized varying-coefficients regression with item scores as the dependent measure., Results: Except for the hurdle step, item scores were lower in the weighted-vest than in the control condition for all tests ( P < .05). Except for rotary stability, F statistics were significant for all models ( P values < .05, R 2 values = 0.22-0.77). Main effects of balance, range of motion, and strength on Functional Movement Screen scores were observed ( P < .05); however, little evidence was found to suggest that these attributes mediated load-related decreases in Functional Movement Screen item scores., Conclusions: Balance, range of motion, and strength affected movement quality but did not mediate the effect of the load treatment.

Context: Movement screening has become increasingly popular among tactical professionals. This popularity has motivated the design of interventions that cater to improving outcomes on the screens themselves, which are often scored in reference to an objective norm. In contrast to the assumptions underlying this approach, dynamical systems theory suggests that movements arise as a function of continuously evolving constraints and that optimal movement strategies may not exist. To date, few data address behavioral complexity in the fundamental movement tasks commonly used in clinical screenings., Objective: To provide evidence of complex variability during movement screens and test the role of modifiable-that is, trainable-constraints in mediating loss of complexity during experimental-task manipulations., Design: Crossover study., Setting: Research laboratory., Patients or Other Participants: Twenty-five male (age = 23.96 ± 3.74 years, height = 178.82 ± 7.51 cm, mass = 79.66 ± 12.66 kg) and 25 female (age = 22.00 ± 2.02 years, height = 165.40 ± 10.24 cm, mass = 63.98 ± 11.07 kg) recreationally active adults., Intervention(s): Participants performed tests of balance, range of motion, and strength. Additionally, they performed cyclical movement tasks under a control (C) condition and while wearing an 18.10-kg weight vest (W)., Main Outcome Measure(s): Ground reaction forces were sampled at 1000 Hz and used to calculate center of pressure during cyclical movement tests. Multivariate multiscale entropy (MMSE) for the center-of-pressure signal was then calculated. Condition effects (C versus W) were analyzed using paired t tests, and penalized varying-coefficients regression was used to identify models predicting entropy outcomes from balance, range of motion, and strength., Results: The MMSE decreased during the W condition (MMSE C > MMSE W ; t 49 range = 3.17-5.21; all P values < .01)., Conclusions: Moderate evidence supported an association between modifiable constraints and behavioral complexity, but a role in mediating load-related loss of complexity was not demonstrated.

This study examined the training effect of attentional focus (external focus, internal focus, or no focus instructions) on a dynamic balance task. Participants completed baseline balance testing, seven consecutive days of dynamic balance board training, and retention testing 24 hours after the last session. The novel finding of this study was the presence of a training effect on balance control when adopting an external focus relative to an internal focus or no focus instructions. Further, we report the unique observation that more patterned behavior was adopted regardless of the focus instructions. These findings provide insight into how instructions can be altered to enhance human balance control and complement the constrained-action hypothesis.

Objective: Postural control is frequently compromised after sub-concussive and concussive head trauma, and balance testing is an integral part of neuromotor assessment and management. The main objective of this paper is to develop a novel smartphone-based neuromotor assessment protocol for screening of dynamic balance decrements stemming from head trauma., Approach: Experiments 1 and 2 compared Android smartphone orientation detection algorithms to a biomechanics laboratory motion capture system using a pendulum (i.e. non-biological movement) and a human stepping task (i.e. biological movement). Experiment 3 examined the test-retest reliability of a stepping-in-place protocol in three different sensory conditions (eyes open, no-vision, head shake) using temporal and spatial variability metrics extracted from thigh orientation signal in a sample of healthy young adults., Main Results: Smartphone sensors provided valid measurements of movement timing and amplitude variables. However, sensor firmware version and Android OS version significantly affected quality of measurement. High test-retest reliability was shown for the temporal and spatial variables of interest during the stepping-in-place task., Significance: Collectively, these experiments show that our smartphone application is a valid and reliable way to measure leg movement characteristics (mean stride time and its variability (CV), Peak Thigh SD, Thigh ROM, and Peak Return Velocity) during dynamic balance activity, which could provide an objective way to assess neuromotor function after head trauma and in other populations with balance dysfunction.

Complexity measures have become increasingly prominent in the postural control literature. Several studies have found associations between clinical balance improvements and complexity, but the relationship between sensory reweighting and complexity changes has remained unobserved. The purpose of this study was to determine the relationship between sensory reweighting via Wii Fit balance training and complexity. Twenty healthy adults completed 6 weeks of training. Participants completed the sensory organization test (SOT) before and after the sessions. Complexity of postural control was analyzed through sample entropy of the center-of-pressure velocity time series in the resultant, anterior-posterior (AP), and medial-lateral directions, and compared to SOT summary score changes. Significant differences were found between pre- and post-training for the condition five (p < .001, d = .525) and vestibular summary scores (p < .001, d = .611). Similarly, changes in complexity were observed from pre- to post-training in the resultant (p = .040, d = .427) direction. While the AP velocity was not significant (p = .07, d = .355), its effect size was moderate. A moderate correlation was revealed in the posttest between AP complexity and condition 5 (r = .442, p = .05), as well as between AP complexity and the vestibular summary score (r = .351, p = .13). The results of this study show that a moderate relationship exists between postural control complexity and the vestibular system, suggesting that complexity may reflect the neurosensory organization used to maintain upright stance.

Postural control is commonly assessed by quantifying center of pressure (CoP) variability during quiet stance. CoP data is traditionally filtered prior to analysis. However, some researchers suggest filtering may lead to undesirable consequences. Further, sampling frequency may also affect CoP analysis, as filtering CoP signals of different sampling frequencies may influence variability metrics. This study examined the influence of sampling frequency and filtering on metrics that index the magnitude and structure of variability in CoP displacement and velocity. Healthy adults (N=8, 27.4±2.6 years) balanced on their right foot for 60s on a force plate. CoP data recorded at 100Hz was then downsampled and/or filtered (2nd order dual-pass 10Hz low-pass Butterworth) to create six different CoP time series for each participant: (1) original, (2) filtered, (3) downsampled to 50Hz, (4) downsampled to 25Hz, (5) downsampled to 50Hz and filtered, and (6) down-sampled to 25Hz and filtered. Data were then analyzed using four common variability metrics (standard deviation [SD], root mean square [RMS], detrended fluctuation analysis α [DFA α], and sample entropy [SampEn]). Data processing techniques did not influence the magnitude of variability (SD and RMS), but did influence the structure of variability (DFA α and SampEn) in CoP displacement. All metrics were influenced by data processing techniques in CoP velocity. Thus, when interpreting changes in CoP variability, one must be careful to identify how much change is driven by the neuromotor system and how much is a function of data processing technique., (Copyright © 2015 Elsevier B.V. All rights reserved.)

Background: Over the last two decades, various measures of entropy have been used to examine the complexity of human postural control. In general, entropy measures provide information regarding the health, stability and adaptability of the postural system that is not captured when using more traditional analytical techniques. The purpose of this study was to examine how noise, sampling frequency and time series length influence various measures of entropy when applied to human center of pressure (CoP) data, as well as in synthetic signals with known properties. Such a comparison is necessary to interpret data between and within studies that use different entropy measures, equipment, sampling frequencies or data collection durations., Methods and Findings: The complexity of synthetic signals with known properties and standing CoP data was calculated using Approximate Entropy (ApEn), Sample Entropy (SampEn) and Recurrence Quantification Analysis Entropy (RQAEn). All signals were examined at varying sampling frequencies and with varying amounts of added noise. Additionally, an increment time series of the original CoP data was examined to remove long-range correlations. Of the three measures examined, ApEn was the least robust to sampling frequency and noise manipulations. Additionally, increased noise led to an increase in SampEn, but a decrease in RQAEn. Thus, noise can yield inconsistent results between the various entropy measures. Finally, the differences between the entropy measures were minimized in the increment CoP data, suggesting that long-range correlations should be removed from CoP data prior to calculating entropy., Conclusions: The various algorithms typically used to quantify the complexity (entropy) of CoP may yield very different results, particularly when sampling frequency and noise are different. The results of this study are discussed within the context of the neural noise and loss of complexity hypotheses.

Context: Previous work suggests that balance behavior is a sex-dependent, complex process that can be characterized by linear and nonlinear metrics. Although a certain degree of center of pressure variability may be expected based on sexual dimorphism, there is evidence to suggest that these effects are obscured by potential interactions between sex and anthropometric factors. To date, no study has accounted for such interactive effects using both linear and nonlinear measures. Objective: This investigation sought to analyze interactive models featuring sex, height, and weight as predictors of linear and nonlinear aspects of postural control. Design: Cross-sectional study. Setting: Controlled laboratory. Participants: A total of 26 males (23.80 [3.44] y, 177.87 [6.44] cm, 81.70 [10.80] kg) and 28 females (21.14 [2.03] y, 169.57 [8.80] cm, 64.48 [8.86] kg) were sampled from a healthy university population. MainOutcomeMeasures: Linear (range [RNG], velocity [VEL], and SD) and nonlinear (detrended fluctuation analysis scaling exponent, multivariate multiscale sample entropy [MMSECI]) summary metrics of center of pressure time series. Procedure: Participants stood on a force plate for 20 seconds in 3 conditions: double (D), single (S), and tandem (T) stance. Data for each stance condition were analyzed using regression models with interaction terms for sex × height and sex × weight. In D, weight had a positive, significant main effect on VELy, MMSECId, and MMSECIv. In men, height was observed to have a positive effect on SDy (S), RNGy (S), and RNGx (T) and a negative effect on MMSECIv (T). In women, weight was observed to have a positive effect on SDy and VELx (both T). Conclusions: Our findings suggest that men and women differ with respect to certain linear and nonlinear aspects of balance behavior, and that these differences may reflect sex-specific behavioral patterns in addition to effects related to sexual dimorphism. [ABSTRACT FROM AUTHOR]

Gait control challenges commonly coincide with vestibular dysfunction and there is a long history in using balance and gait activities to enhance functional mobility in this population. While much has been learned using traditional rehabilitation exercises, there is a new line of research emerging that is using visual stimuli in a very specific way to enhance gait control. For example, avatars can be created in an individualized manner to incorporate specific gait characteristics. The avatar could then be used as a visual stimulus to which the patient can synchronize their own gait cycle. This line of research builds upon the rich history of sensorimotor control research in which augmented sensory information (visual, haptic, or auditory) is used to probe, and even enhance, human motor control. This review paper focuses on gait control challenges in patients with vestibular dysfunction, provides a brief historical perspective on how various visual displays have been used to probe sensorimotor and gait control, and offers some recommendations for future research. [ABSTRACT FROM AUTHOR]