On the use of approximate entropy and sample entropy with centre of pressure time-series

A novel classification method for balance differences in elite versus expert athletes based on composite multiscale complexity index and ranking forests

Balance is crucial for various athletic tasks, and accurately assessing balance ability among elite athletes using simple and accessible measurement methods is a significant challenge in sports science. A common approach to balance assessment involves recording center of pressure (CoP) displacements using force platforms, with various indicators proposed to distinguish subtle balance differences. However, these indicators have not reached a consensus, and it remains unclear whether these analyses alone can fully explain the complex interactions of postural control. In this study, we investigated four parameters related to balance control-anterior-posterior (AP) displacement, medial-lateral (ML) displacement, length, and tilt angle-in 13 elite athletes and 12 freestyle skiing aerial expert athletes. Data were recorded during 30-second trials on both soft and hard support surfaces, with eyes open and closed. We calculated the CMCI and used four machine learning algorithms-Logistic Regression, Support Vector Machine(SVM), Naive Bayes, and Ranking Forest-to combine these features and assess each participant's balance ability. A classic train-test split method was applied, and the performance of different classifiers was evaluated using Receiver Operating Characteristic(ROC) analysis. The ROC results showed that traditional time-domain features were insufficient for accurately distinguishing athletes' balance abilities, whereas CMCI performed the best overall. Among all classifiers, the combination of CMCI and Ranking Forest yielded the best performance, with a sensitivity of 0.95 and specificity of 0.35. This nonlinear, multidimensional approach appears to be highly suitable for assessing the complexity of postural control.

Vestibular patients generate more regular head movements than healthy individuals during gaze-stabilization exercises

The vestibular system is vital for maintaining stable vision during daily activities. When peripheral vestibular input is lost, patients initially experience impaired gaze stability due to reduced effectiveness of the vestibular-ocular-reflex pathway. To aid rehabilitation, patients are often prescribed gaze-stabilization exercises during which they make self-initiated active head movements. Analyzing statistical pattern of sequences of stereotyped behaviors to characterize degrees of randomness or repeatability has proven to be a powerful approach for diagnosing disease states, yet this approach has not been applied to patients with vestibular loss. Accordingly, here we investigated whether the patterning of head movements is altered in vestibular-loss patients by using trial-based analysis and sample-entropy measurement. The subjects completed gaze-stability exercises in both the yaw and pitch directions. In trial-based analysis, we calculated the trial-to-trial variability of head movement duration and peak velocity for each individual head movement. Our results showed that healthy individuals exhibited a temporally repetitive (correlated) structure in peak velocity, especially for head movements in the pitch direction, which was absent in most patients. In the sample entropy analysis, which measures the irregularity or randomness of a time series, our results revealed that head-movement generation was more regular in vestibular-loss patients compared to healthy controls. Together, these analyses suggest that vestibular-loss patients display less flexibility in the patterning of their head motions. Our results provide the first experimental evidence that temporal head stability is a valuable metric for distinguishing individuals with impaired vestibular function from healthy ones.

The Influence of Dopaminergic Medication on Regularity and Determinism of Gait and Balance in Parkinson's Disease: A Pilot Analysis

Background/Objectives: Understanding how dual-tasking and Parkinson's disease medication affect gait and balance regularity can provide valuable insights to patients, caregivers, and clinicians regarding frailty and fall risk. However, dual-task gait and balance studies in PD most often only employ linear measures to describe movement regularity. Some have used nonlinear techniques to analyze PD performances, but only in the on-medication state. Thus, it is unclear how the nonlinear aspects of gait or standing balance are affected by PD medication. This study aimed to assess how dopaminergic medication influenced the regularity and determinism of joint angle and anterior-posterior (AP) and medial-lateral (ML) center of pressure (COP) path time-series data while single- and dual-tasking in PD. Methods: Sixteen subjects with PD completed single- and dual-task gait and standing balance trials for 3 min off and on dopaminergic medication. Sample entropy and percent determinism were calculated for bilateral hip, knee, and shoulder joints, and the AP and ML COP path. Results: There were no relevant medication X task interactions for either the joint angles series or the balance series. Instead, the results supported independent effects of medication, dual-tasking, or standing with eyes closed. Balance task difficulty (i.e., eyes open vs. eyes closed) was detected by the nonlinear analyses, but the nonlinear measures yielded opposing results such that standing with eyes closed simultaneously yielded less regular and more deterministic signals. Conclusions: When juxtaposed with previous findings, these results suggest that medication-induced functional improvements in people with PD might be accompanied by a shift from lesser to greater signal consistency, and the effects of dual-tasking and standing with eyes closed were mixed. Future studies would benefit from including both linear and nonlinear measures to better describe gait and balance performance and signal complexity in people with PD.

Machine learning's effectiveness in evaluating movement in one-legged standing test for predicting high autistic trait

Introduction

Research supporting the presence of diverse motor impairments, including impaired balance coordination, in children with autism spectrum disorder (ASD) is increasing. The one-legged standing test (OLST) is a popular test of balance. Since machine learning is a powerful technique for learning predictive models from movement data, it can objectively evaluate the processes involved in OLST. This study assesses machine learning's effectiveness in evaluating movement in OLST for predicting high autistic trait.

Methods

In this study, 64 boys and 62 girls participated. The participants were instructed to stand on one leg on a pressure sensor while facing the experimenter. The data collected in the experiment were time-series data pertaining to pressure distribution on the sole of the foot and full-body images. A model to identify the participants belonging to High autistic trait group and Low autistic trait group was developed using a support vector machine (SVM) algorithm with 16 explanatory variables. Further, classification models were built for the conventional, proposed, and combined explanatory variable categories. The probabilities of High autistic trait group were calculated using the SVM model.

Results

For proposed and combined variables, the accuracy, sensitivity, and specificity scores were 1.000. The variables shoulder, hip, and trunk are important since they explain the balance status of children with high autistic trait. Further, the total Social Responsiveness Scale score positively correlated with the probability of High autistic trait group in each category of explanatory variables.

Discussion

Results indicate the effectiveness of evaluating movement in OLST by using movies and machine learning for predicting high autistic trait. In addition, they emphasize the significance of specifically focusing on shoulder and waist movements, which facilitate the efficient predicting high autistic trait. Finally, studies incorporating a broader range of balance cues are necessary to comprehensively determine the effectiveness of utilizing balance ability in predicting high autistic trait.

Multi-Frequency Entropy for Quantifying Complex Dynamics and Its Application on EEG Data

Multivariate entropy algorithms have proven effective in the complexity dynamic analysis of electroencephalography (EEG) signals, with researchers commonly configuring the variables as multi-channel time series. However, the complex quantification of brain dynamics from a multi-frequency perspective has not been extensively explored, despite existing evidence suggesting interactions among brain rhythms at different frequencies. In this study, we proposed a novel algorithm, termed multi-frequency entropy (mFreEn), enhancing the capabilities of existing multivariate entropy algorithms and facilitating the complexity study of interactions among brain rhythms of different frequency bands. Firstly, utilizing simulated data, we evaluated the mFreEn's sensitivity to various noise signals, frequencies, and amplitudes, investigated the effects of parameters such as the embedding dimension and data length, and analyzed its anti-noise performance. The results indicated that mFreEn demonstrated enhanced sensitivity and reduced parameter dependence compared to traditional multivariate entropy algorithms. Subsequently, the mFreEn algorithm was applied to the analysis of real EEG data. We found that mFreEn exhibited a good diagnostic performance in analyzing resting-state EEG data from various brain disorders. Furthermore, mFreEn showed a good classification performance for EEG activity induced by diverse task stimuli. Consequently, mFreEn provides another important perspective to quantify complex dynamics.

Movement Diversity and Complexity Increase as Arm Impairment Decreases After Stroke: Quality of Movement Experience as a Possible Target for Wearable Feedback

Upper extremity (UE) impairment is common after stroke resulting in reduced arm use in daily life. A few studies have examined the use of wearable feedback of the quantity of arm movement to promote recovery, but with limited success. We posit that it may be more effective to encourage an increase in beneficial patterns of movement practice - i.e. the overall quality of the movement experience - rather than simply the overall amount of movement. As a first step toward testing this idea, here we sought to identify statistical features of the distributions of daily arm movements that become more prominent as arm impairment decreases, based on data obtained from a wrist IMU worn by 22 chronic stroke participants during their day. We identified several measures that increased as UE Fugl-Meyer (UEFM) score increased: the fraction of movements achieved at a higher speed, forearm postural diversity (quantified by kurtosis of the tilt-angle), and forearm postural complexity (quantified by sample entropy of tilt angle). Dividing participants into severe, moderate, and mild impairment groups, we found that forearm postural diversity and complexity were best able to distinguish the groups (Cohen's D =1.1, and 0.99, respectively) and were also the best subset of predictors for UEFM score. Based on these findings coupled with theories of motor learning that emphasize the importance of variety and challenge in practice, we suggest that using these measures of diversity and complexity in wearable rehabilitation could provide a basis to test whether the quality of the daily movement experience is therapeutic.

A Large Harmonized Upper and Lower Limb Accelerometry Dataset: A Resource for Rehabilitation Scientists

Wearable sensors can measure movement in daily life, an outcome that is salient to patients, and have been critical to accelerating progress in rehabilitation research and practice. However, collecting and processing sensor data is burdensome, leaving many scientists with limited access to such data. To address these challenges, we present a harmonized, wearable sensor dataset that combines 2,885 recording days of sensor data from the upper and lower limbs from eight studies. The dataset includes 790 individuals ages 0 - 90, nearly equal sex proportions (53% male, 47% female), and representation from a range of demographic backgrounds (69.4% White, 24.9% Black, 1.8% Asian) and clinical conditions (46% neurotypical, 31% stroke, 7% Parkinson's disease, 6% orthopedic conditions, and others). The dataset is publicly available and accompanied by open source code and an app that allows for interaction with the data. This dataset will facilitate the use of sensor data to advance rehabilitation research and practice, improve the reproducibility and replicability of wearable sensor studies, and minimize costs and duplicated scientific efforts.

Innovative approaches for managing patients with chronic vestibular disorders: follow-up indicators and predictive markers for studying the vestibular error signal

Introduction

Despite significant advancements in understanding the biochemical, anatomical, and functional impacts of vestibular lesions, developing standardized and effective rehabilitation strategies for patients unresponsive to conventional therapies remains a challenge. Chronic vestibular disorders, characterized by permanent or recurrent imbalances and blurred vision or oscillopsia, present significant complexity in non-pharmacological management. The complex interaction between peripheral vestibular damage and its impact on the central nervous system (CNS) raises questions about neuroplasticity and vestibular compensation capacity. Although fundamental research has examined the consequences of lesions on the vestibular system, the effect of a chronic peripheral vestibular error signal (VES) on the CNS remains underexplored. The VES refers to the discrepancy between sensory expectations and perceptions of the vestibular system has been clarified through recent engineering studies. This deeper understanding of VES is crucial not only for vestibular physiology and pathology but also for designing effective measures and methods of vestibular rehabilitation, shedding light on the importance of compensation mechanisms and sensory integration.

Methods

This retrospective study, targeting patients with chronic unilateral peripheral vestibulopathy unresponsive to standard treatments, sought to exclude any interference from pre-existing conditions. Participants were evaluated before and after a integrative vestibular exploratory and rehabilitation program through questionnaires, posturographic tests, and videonystagmography.

Results

The results indicate significant improvements in postural stability and quality of life, demonstrating positive modulation of the CNS and an improvement of vestibular compensation.

Discussion

Successful vestibular rehabilitation likely requires a multifaceted approach that incorporates the latest insights into neuroplasticity and sensory integration, tailored to the specific needs and clinical progression of each patient. Focusing on compensating for the VES and enhancing sensory-perceptual-motor integration, this approach aims not just to tailor interventions but also to reinforce coherence among the vestibular, visual, and neurological systems, thereby improving the quality of life for individuals with chronic vestibular disorders.

The use of nonlinear analysis in understanding postural control: A scoping review

Nonlinear analyses have emerged as an approach to unraveling the intricate dynamics and underlying mechanisms of postural control, offering insights into the complex interplay of physiological and biomechanical factors. However, achieving a comprehensive understanding of the application of nonlinear analysis in postural control studies remains a challenge due to the various nonlinear measurement methods currently available. Thus, this scoping review aimed to identify existing nonlinear analyses used to study postural control in both dynamic and quiet tasks, and to summarize and disseminate the available literature on the use of nonlinear analysis in postural control. For this purpose, a scoping review was conducted and reported following the PRISMA Extension for Scoping Reviews (PRISMA-ScR) Checklist and Explanation. Searches were conducted up to July 2023 on PubMed/Medline, Embase, CINAHL, Web of Science, and Google Scholar databases, resulting in the inclusion of 397 unique studies. The main classes employed among the studies were entropy-based, fractal-based, quantification of recurrence plots, and quantification of stability, with a total of 91 different algorithms distributed among these classes. The most common condition used to study postural control was quiet standing, followed by dynamic standing and gait tasks. Although various algorithms were utilized for this purpose, sample entropy was employed in 43% of studies to explore mechanisms related to postural control. Among them, 28% were in quiet standing, 3.27% were in dynamic standing, and 4.78% to study postural control during the gait. The results also provide insights into nonlinear analysis for future studies, concerning the complexity and interactions within the postural control system across various task demands.

Exploring the Real-Time Variability and Complexity of Sitting Patterns in Office Workers with Non-Specific Chronic Spinal Pain and Pain-Free Individuals

Chronic spinal pain (CSP) is a prevalent condition, and prolonged sitting at work can contribute to it. Ergonomic factors like this can cause changes in motor variability. Variability analysis is a useful method to measure changes in motor performance over time. When performing the same task multiple times, different performance patterns can be observed. This variability is intrinsic to all biological systems and is noticeable in human movement. This study aims to examine whether changes in movement variability and complexity during real-time office work are influenced by CSP. The hypothesis is that individuals with and without pain will have different responses to office work tasks. Six office workers without pain and ten with CSP participated in this study. Participant's trunk movements were recorded during work for an entire week. Linear and nonlinear measures of trunk kinematic displacement were used to assess movement variability and complexity. A mixed ANOVA was utilized to compare changes in movement variability and complexity between the two groups. The effects indicate that pain-free participants showed more complex and less predictable trunk movements with a lower degree of structure and variability when compared to the participants suffering from CSP. The differences were particularly noticeable in fine movements.

Brain complexity in stroke recovery after bihemispheric transcranial direct current stimulation in mice

Stroke is one of the leading causes of disability worldwide. There are many different rehabilitation approaches aimed at improving clinical outcomes for stroke survivors. One of the latest therapeutic techniques is the non-invasive brain stimulation. Among non-invasive brain stimulation, transcranial direct current stimulation has shown promising results in enhancing motor and cognitive recovery both in animal models of stroke and stroke survivors. In this framework, one of the most innovative methods is the bihemispheric transcranial direct current stimulation that simultaneously increases excitability in one hemisphere and decreases excitability in the contralateral one. As bihemispheric transcranial direct current stimulation can create a more balanced modulation of brain activity, this approach may be particularly useful in counteracting imbalanced brain activity, such as in stroke. Given these premises, the aim of the current study has been to explore the recovery after stroke in mice that underwent a bihemispheric transcranial direct current stimulation treatment, by recording their electric brain activity with local field potential and by measuring behavioural outcomes of Grip Strength test. An innovative parameter that explores the complexity of signals, namely the Entropy, recently adopted to describe brain activity in physiopathological states, was evaluated to analyse local field potential data. Results showed that stroke mice had higher values of Entropy compared to healthy mice, indicating an increase in brain complexity and signal disorder due to the stroke. Additionally, the bihemispheric transcranial direct current stimulation reduced Entropy in both healthy and stroke mice compared to sham stimulated mice, with a greater effect in stroke mice. Moreover, correlation analysis showed a negative correlation between Entropy and Grip Strength values, indicating that higher Entropy values resulted in lower Grip Strength engagement. Concluding, the current evidence suggests that the Entropy index of brain complexity characterizes stroke pathology and recovery. Together with this, bihemispheric transcranial direct current stimulation can modulate brain rhythms in animal models of stroke, providing potentially new avenues for rehabilitation in humans.

Biomechanical Assessment Methods Used in Chronic Stroke: A Scoping Review of Non-Linear Approaches

Non-linear and dynamic systems analysis of human movement has recently become increasingly widespread with the intention of better reflecting how complexity affects the adaptability of motor systems, especially after a stroke. The main objective of this scoping review was to summarize the non-linear measures used in the analysis of kinetic, kinematic, and EMG data of human movement after stroke. PRISMA-ScR guidelines were followed, establishing the eligibility criteria, the population, the concept, and the contextual framework. The examined studies were published between 1 January 2013 and 12 April 2023, in English or Portuguese, and were indexed in the databases selected for this research: PubMed®, Web of Science®, Institute of Electrical and Electronics Engineers®, Science Direct® and Google Scholar®. In total, 14 of the 763 articles met the inclusion criteria. The non-linear measures identified included entropy (n = 11), fractal analysis (n = 1), the short-term local divergence exponent (n = 1), the maximum Floquet multiplier (n = 1), and the Lyapunov exponent (n = 1). These studies focused on different motor tasks: reaching to grasp (n = 2), reaching to point (n = 1), arm tracking (n = 2), elbow flexion (n = 5), elbow extension (n = 1), wrist and finger extension upward (lifting) (n = 1), knee extension (n = 1), and walking (n = 4). When studying the complexity of human movement in chronic post-stroke adults, entropy measures, particularly sample entropy, were preferred. Kinematic assessment was mainly performed using motion capture systems, with a focus on joint angles of the upper limbs.

Effects of environmental and task related conditions on postural control under concurrent visual feedback

BACKGROUND

Previous studies have yielded conflicting results on the facilitative effects of concurrent visual feedback (CVFB) on postural control. In addition, these effects have generally been assessed only during a single postural task, and their scope has been limited to training sessions in the acquisition phase but not in the later retention phase. One explanation for these conflicting results is that assessing postural control during a single postural task, such as quiet stance, may not be sufficiently challenging for the postural control system to infer balance abilities. We aimed to address these shortcomings by diversifying postural tasks and environmental conditions and by including acquisition and retention phases in the experiments.

RESEARCH QUESTIONS

Does the provision of CVFB of the instantaneous COP position improve performance on a variety of postural tasks compared to no-CVFB controls? Are the effects of the CVFB retained the following day? Do the observed effect sizes differ in magnitude between the environmental and task conditions under CVFB?

METHODS

Forty healthy young adults were randomly assigned to CVFB and no-CVFB control groups. The subjects performed three postural tasks: quiet, tandem, and single-leg stance, under two environmental conditions based on the stiffness of the supporting ground surface. Seven measures of postural sway, including ellipse area, mean speed, and sample entropy, were examined.

RESULTS

The provision of CVFB significantly increased sample entropy and sway-path length of the normalized posturogram. In addition, ellipse area, standard deviation of resultant distance, and range in the anteroposterior direction were significantly reduced in the CVFB group compared to the no-CVFB controls; however, these effects were not retained the following day without the addition of CVFB augmentation. The postural sway measures under CVFB were affected by task and environmental constraints, with varying effect sizes.

SIGNIFICANCE

This study demonstrated environment and task-specific changes in postural sway measures under CVFB, which facilitated postural control in a variety of postural tasks. Providing CVFB significantly increased sample entropy, indicating less regular postural sway. The features of CVFB that attract external attention and reduce cognitive overload are possible explanations for these findings.

Ground reaction forces better than center of pressure differentiate postural control between young female volleyball players and untrained peers

A comprehensive explanation of the relationship between postural control and athletic performance requires compare body balance in athletes with their never training counterparts. To fill this gap in relation to volleyball, the aim of this study was to compare the balance of intermediate adolescent female players (VOL, n = 61) with inactive peers (CON, n = 57). The participants were investigated in normal quiet stance during 20 s trials on a Kistler force plate. The traditional spatial (amplitude and mean speed) and temporal (frequency and entropy) indices were computed for ground reaction forces (GRF) and center-of-pressure (COP) time-series. The spatial parameters of the both time-series did not discriminate the two groups. However, the temporal GRF parameters revealed much lower values in VOL than in CON (p < .0001). This leads to three important conclusions regarding posturography applications. First, GRF and COP provide different information regarding postural control. Second, measures based on GRF are more sensitive to changes in balance related to volleyball training and perhaps to similar training and sports activity regimens. And third, the indicators calculated based on these two time series can complement each other and thus enrich the insight into the relationship between balance and sports performance level.

The influence of fear of falling on the control of upright stance across the lifespan

BACKGROUND

Standing at height, and subsequent changes in emotional state (e.g., fear of falling), lead to robust alterations in balance in adults. However, little is known about how height-induced postural threat affects balance performance in children. Children may lack the cognitive capability necessary to inhibit the processing of threat and fear-related stimuli, and as a result, may show more marked (and perhaps detrimental) changes in postural control compared to adults. This work explored the emotional and balance responses to standing at height in children, and compared responses to young and older adults.

METHODS

Children (age: 9.7 ± 0.8 years, n = 38), young adults (age: 21.8 ± 4.0 years, n = 45) and older adults (age: 73.3 ± 5.0 years, n = 15) stood in bipedal stance in two conditions: at ground level and 80 cm above ground. Centre of pressure (COP) amplitude (RMS), frequency (MPF) and complexity (sample entropy) were calculated to infer postural performance and strategy. Emotional responses were quantified by assessing balance confidence, fear of falling and perceived instability.

RESULTS

Young and older adults demonstrated a postural adaptation characterised by increased frequency and decreased amplitude of the COP, in conjunction with increased COP complexity (sample entropy). In contrast, children demonstrated opposite patterns of changes: they exhibited an increase in COP amplitude and decrease in both frequency and complexity when standing at height.

SIGNIFICANCE

Children and adults adopted different postural control strategies when standing at height. Whilst young and older adults exhibited a potentially protective "stiffening" response to a height-induced threat, children demonstrated a potentially maladaptive and ineffective postural adaptation strategy. These observations expand upon existing postural threat related research in adults, providing important new insight into understanding how children respond to standing in a hazardous situation.

Exploring the Hidden Complexity: Entropy Analysis in Pulse Oximetry of Female Athletes

This study examines the relationship between physiological complexity, as measured by Approximate Entropy (ApEn) and Sample Entropy (SampEn), and fitness levels in female athletes. Our focus is on their association with maximal oxygen consumption (VO2,max). Our findings reveal a complex relationship between entropy metrics and fitness levels, indicating that higher fitness typically, though not invariably, correlates with greater entropy in physiological time series data; however, this is not consistent for all individuals. For Heart Rate (HR), entropy measures suggest stable patterns across fitness categories, while pulse oximetry (SpO2) data shows greater variability. For instance, the medium fitness group displayed an ApEn(HR) = 0.57±0.13 with a coefficient of variation (CV) of 22.17 and ApEn(SpO2) = 0.96±0.49 with a CV of 46.08%, compared to the excellent fitness group with ApEn(HR) = 0.60±0.09 with a CV of 15.19% and ApEn(SpO2) =0.85±0.42 with a CV of 49.46%, suggesting broader physiological responses among more fit individuals. The larger standard deviations and CVs for SpO2 entropy may indicate the body's proficient oxygen utilization at higher levels of physical demand. Our findings advocate for combining entropy metrics with wearable sensor technology for improved biomedical analysis and personalized healthcare.

The sex effect on balance control while standing on vestibular-demanding tasks with/without vestibular simulations: implication for sensorimotor training for future space missions

Background: Anatomical differences between sexes in the vestibular system have been reported. It has also been demonstrated that there is a sex difference in balance control while standing on vestibular-demanding tasks. In 2024, NASA expects to send the first female to the Moon. Therefore, to extend the current knowledge, this study attempted to examine whether different sexes respond differently to vestibular-disrupted and vestibular-demanding environments. Method: A total of fifteen males and fifteen females participated in this study. The vestibular function was quantified through different SOT conditions (SOT1: baseline; SOT5: vestibular demanding by standing with blindfolded and sway reference surface). The vestibular stimulation (VS) was applied either unilaterally or bilaterally to vestibular system to induce the sensory-conflicted and challenging tasks. Thus, a total of 6 conditions (2 SOT conditions X 3 VSs: no-VS, unilateral VS, and bilateral VS) were randomly given to these participants. Three approaches can be quantified the balance control: 1) the performance ratio (PR) of center of gravity trajectories (CoG), 2) the sample entropy measure (SampEn) of CoG, and 3) the total traveling distance of CoG. A mixed three-way repeated ANOVA measure was used to determine the interaction among the sex effect, the effect of SOT, and the effect of VS on balance control. Results: A significant sex effect on balance control was found in the PR of CoG in the anterior-posterior (AP) direction (p = 0.026) and in the SampEn of CoG in both AP and medial-lateral (ML) directions (p = 0.025, p < 0.001, respectively). Also, a significant interaction among the sex effect, the effect of SOT, and the effect of VS on balance control was observed in PR of CoG in the ML direction (p < 0.001), SampEn of CoG in the AP and ML directions (p = 0.002, p < 0.001, respectively), and a traveling distance in AP direction (p = 0.041). Conclusion: The findings in the present study clearly revealed the necessity to take sex effect into consideration while standing in vestibular-perturbed or/and vestibular demanding tasks. Also, the results in the present study could be a fundamental reference for future sensorimotor training.

Reliability and minimal detectable change of nonlinear analysis measure of postural control in older adults with mild cognitive impairment

BACKGROUND

Evaluating quiet stance under various conditions using nonlinear analysis may be an effective method of measuring postural control in older adults with mild cognitive impairment (MCI). However, no studies have examined the reliability of using sample entropy (SampEn) in older adults with MCI.

RESEARCH QUESTION

What are the within- and between-session reliability and minimal detectable change (MDC) of a nonlinear analysis measure of postural control during quiet stance in older adults with MCI?

METHODS

Fourteen older adults with MCI performed static standing under four conditions, and the center of pressure signal was calculated and applied to SampEn nonlinear analysis. The within- and between-session reliability and MDC were explored.

RESULTS

Within-session reliability was found to be fair to good and excellent (ICC = 0.527-0.960), and between-session reliability was excellent (ICC = 0.795-0.979). MDC values were less than 0.15.

SIGNIFICANCE

The between-session reliability of SampEn in all conditions demonstrates SampEn's stable performance. This method may be useful in assessing postural control in older adults with MCI, and MDC values may be helpful in detecting subtle changes in patient performance.

Perceived cognitive fatigue has only marginal effects on static balance control in healthy young adults

We examined the influence of perceived cognitive fatigue on static balance control in healthy young adults to gain greater clarity about this issue than provided in previous research. Based on the prevailing assumption in pertinent literature, we hypothesized that the influence of cognitive fatigue on balance control depends on the attentional effort required by the balance tasks being performed. To test this hypothesis, 44 young adults (24 women and 20 men) were alternately assigned to either the experimental group that was cognitively fatigued (using the 16-min TloadDback-task with individualized settings) or the control group (who watched a documentary). Before and after the intervention, the participants performed six balance tasks that differed in (attentional) control requirements, while recording the center of pressure (COP). From these time series, sway variability, mean speed, and sample entropy were calculated and analyzed statistically. Additionally, perceived cognitive fatigue was assessed using VAS scales. Statistical analyses confirmed that the balance tasks differed in control characteristics and that cognitive fatigue was elevated in the experimental group, but not in the control group. Nevertheless, no significant main effects of cognitive fatigue were found on any of the COP measures of interest, except for some non-robust interaction effects related primarily to sample entropy. These results suggest that, in young adults, postural control in static balance tasks is largely automatic and unaffected by task-induced state fatigue.

Expecting the Unexpected: Entropy and Multifractal Systems in Finance

Entropy serves as a measure of chaos in systems by representing the average rate of information loss about a phase point's position on the attractor. When dealing with a multifractal system, a single exponent cannot fully describe its dynamics, necessitating a continuous spectrum of exponents, known as the singularity spectrum. From an investor's point of view, a rise in entropy is a signal of abnormal and possibly negative returns. This means he has to expect the unexpected and prepare for it. To explore this, we analyse the New York Stock Exchange (NYSE) U.S. Index as well as its constituents. Through this examination, we assess their multifractal characteristics and identify market conditions (bearish/bullish markets) using entropy, an effective method for recognizing fluctuating fractal markets. Our findings challenge conventional beliefs by demonstrating that price declines lead to increased entropy, contrary to some studies in the literature that suggest that reduced entropy in market crises implies more determinism. Instead, we propose that bear markets are likely to exhibit higher entropy, indicating a greater chance of unexpected extreme events. Moreover, our study reveals a power-law behaviour and indicates the absence of variance.

Clinical Static Balance Assessment: A Narrative Review of Traditional and IMU-Based Posturography in Older Adults and Individuals with Incomplete Spinal Cord Injury

Maintaining a stable upright posture is essential for performing activities of daily living, and impaired standing balance may impact an individual's quality of life. Therefore, accurate and sensitive methods for assessing static balance are crucial for identifying balance impairments, understanding the underlying mechanisms of the balance deficiencies, and developing targeted interventions to improve standing balance and prevent falls. This review paper first explores the methods to quantify standing balance. Then, it reviews traditional posturography and recent advancements in using wearable inertial measurement units (IMUs) to assess static balance in two populations: older adults and those with incomplete spinal cord injury (iSCI). The inclusion of these two groups is supported by their large representation among individuals with balance impairments. Also, each group exhibits distinct aspects in balance assessment due to diverse underlying causes associated with aging and neurological impairment. Given the high vulnerability of both demographics to balance impairments and falls, the significance of targeted interventions to improve standing balance and mitigate fall risk becomes apparent. Overall, this review highlights the importance of static balance assessment and the potential of emerging methods and technologies to improve our understanding of postural control in different populations.

An Absence of Persistent Postural Stability Deficits Following a Sport Concussion in Collegiate Athletes

OBJECTIVE

The purpose of our study was to determine whether persistent postural stability deficits exist in athletes following sport concussion (SC) in comparison with preinjury (baseline) values using Sample Entropy (SampEn).

SETTING

Sports medicine clinic.

PATIENTS OR OTHER PARTICIPANTS

Participants consisted of 71 collegiate athletes (44 male, 27 female) with an average age of 19.9 ± 0.96 years who had a history of 1 concussion that occurred during their time as a collegiate athlete.

DESIGN

In our prospective, cohort design participants completed the Sensory Organization Test (SOT) at baseline, upon reporting symptom-free following a diagnosed SC, and upon establishing a new baseline prior to the start of the subsequent sport season.

MAIN OUTCOME MEASURES

The SOT's condition scores were calculated and analyzed in alignment with the manufacturer's instructions. SampEn was calculated in the anterior-posterior (AP) and medial-lateral (ML) directions from the center-of-pressure oscillations over the 20-second time series for each SOT condition. The SOT and SampEn outcome scores for each condition were analyzed with repeated-measures analyses of variance.

RESULTS

Significant main effects were observed for the SOT's conditions 3 ( F1.6, 114.8 = 7.83, P = .001, η2 = 0.10 [0.02-0.20]), 5 ( F1.8, 126.8 = 11.53, P < .001, η2 = 0.14 [0.04-0.25]), and 6 ( F1.9, 134.5 = 25.11, P < .001, η2 = 0.26 [0.14-0.37]), with significant improvements across time. Significant main effects were also observed for SampEn in the AP direction for conditions 3 ( F2, 140 = 7.59, P = .001, η2 = 0.10 [0.02-0.19]) and 6 ( F2, 140 = 6.22, P = .003, η2 = 0.08 [0.011-0.170]), with significant improvements across time.

CONCLUSIONS

Following a diagnosed SC, our results suggest that collegiate athletes returned if not exceeded baseline values at the symptom-free and new baseline assessments. The application of linear and nonlinear measures of postural stability following a SC yielded similar outcomes in conjunction with a baseline assessment. Our findings support the clinical utility of the baseline SC assessment when evaluating persisting balance deficits when using linear or nonlinear measures.

Pressure stimulus study on acupuncture points with multi-channel multimode-fiber diffuse speckle contrast analysis (MMF-DSCA)

A multi-channel multimode-fiber deep tissue flowmetry system has been constructed based on diffuse speckle contrast analysis (DSCA) for simultaneous blood flow measurements at different locations on the human body. This system has been utilized in an acupuncture study within the field of traditional Chinese medicine (TCM), primarily focusing on acupuncture points along the large intestine meridian. Deep tissue blood flow was monitored at four different acupuncture points (LI1, LI5, LI10, and ST25) with a sampling rate of 60 Hz while applying pressure stimulus on LI4 (hegu or hapgok). Although the blood flow index (BFI) and blood volume (BV) did not exhibit significant changes after the pressure stimulus, an increase in the amplitude and complexity of low-frequency oscillations (LFOs) in microcirculation was observed.

Influences of smart glasses on postural control under single- and dual-task conditions for ergonomic risk assessment

Head worn displays have become increasingly popular at workplaces in logistics and assembly lines in recent years. Such displays are expected to improve productivity and safety at the workplace. However, their impact on balance in the workforce is still an open research question. Therefore, we investigated the influence of the Vuzix M400 and Realwear HMT1 smart glasses on postural control. A laboratory study was conducted with eleven participants. Balance parameters were recorded during bilateral quiet stance, together with parameters of cognitive load. The two different smart glasses used in this study were compared with a monitor and a tablet under single-task conditions and while performing a spatial 2-back task. As balance parameters, the prediction ellipse and sample entropy in anteroposterior as well as mediolateral direction of the center-of-pressure data were examined. No significant differences were observed in the cognitive task performance between the devices. The prediction ellipse of the smart glasses was smaller than the tablets but larger than the smartboard. The dynamic of sample entropy data suggests that the use of the spatial 2-back task induces postural sway in the participants. This effect was most profound when looking at the monitor and least recognizable in the data of the tablet.

Reliability of force plate-based measures of standing balance in the sub-acute stage of post-stroke recovery

Background

Difficulty controlling balance is one of the major contributors to the increased risk of falls among individuals with stroke. It is important to use reliable and objective measures to improve examination of balance impairments post-stroke, and to in turn inform clinical decision-making. The main objective of this study was to examine the relative and absolute reliabilities of force plate-based balance measures in quiet standing, in the sub-acute stage of stroke recovery.

Methods

Twenty-four people with sub-acute stroke (mean age = 61 years) performed two trials of quiet standing, each 30 s long. Sixteen force plate-based balance measures in the time, frequency, or nonlinear domains were calculated. Within-session test-retest reliabilities were investigated using intraclass correlation coefficient (ICC), standard error of measurement, and minimal detectable change.

Results

Mean speed of displacements of the centre of pressure along the anterior-posterior axis (ICC = 0.91; CI95 % = [0.83, 0.95]), and directional weight-bearing asymmetry (ICC = 0.91; CI95 % = [0.82, 0.95]) demonstrated high relative reliabilities, followed by the speed-based symmetry index and absolute weight-bearing asymmetry (both ICCs = 0.86; CI95 % = [0.74, 0.93]).

Conclusions

Mean speeds of centre of pressure, directional weight-bearing asymmetry, and speed-based symmetry index are the most reliable force plate-based measures that were evaluated in our study, and can be included in the balance assessments of individuals within the sub-acute stage of post-stroke recovery. These findings can better inform clinicians about the specific balance problems experienced by people in this population.

Sport dependent effects on the sensory control of balance during upright posture: a comparison between professional horseback riders, judokas and non-athletes

Introduction

Compared to judokas (JU) and non-athletes (NA), horseback riders (HR) may develop specific changes in their sensory control of balance.

Methods

Thirty-four international-level JU, twenty-seven international-level HR and twenty-one NA participated. Participants stood upright on a plateform (static condition) or on a seesaw device with an instability along the mediolateral (ML) or the anteroposterior (AP) direction (dynamic conditions). These conditions were carried out with eyes opened (EO) or closed (EC), and with (wF) or without a foam (nF). Experimental variables included conventional (linear), non-linear center-of-pressure (COP) parameters, Romberg Quotient (RQ) and Plantar Quotient (PQ).

Results

Group effects. COP Surface (COPS) and standard deviation of COP along AP (SDY) were lower in HR than in JU in Static. SD Y was lower in HR than in JU in Dynamic AP. COP velocity (COPV) was lower in both HR and JU than in NA in Static and Dynamic. Sample entropy along AP and ML (SampEnY and SampEnX) were higher in HR than in JU in Static. SampEnY was higher in HR than in JU in Dynamic ML. Sensory effects. In EC, COPV was lower in JU than in NA in Dynamic AP, and lower in JU than in both HR and NA in Dynamic ML. In EO, COPV was lower in both JU and HR than in NA in Dynamic ML. RQ applied to COPS was lower in JU than in both HR and NA in Dynamic AP, and lower in JU than in HR in Dynamic ML. RQ applied to COPV was lower in JU than in both HR and NA in Static and Dynamic. PQ applied to COPS was higher in JU than in both HR and NA in Dynamic ML.

Conclusion

Results showed that the effects of sport expertise on postural control could only be revealed with specific COP variables and were directionally oriented and sport-dependant. HR seem to rely more on vision than JU, thus revealing that the contribution of the sensory inputs to balance control is also sport-dependent. Results open up new knowledge on the specificity of sport practice on multisensory balance information during upright posture.

Recurrence quantification analysis for fine-scale characterisation of arrhythmic patterns in cardiac tissue

This paper uses recurrence quantification analysis (RQA) combined with entropy measures and organization indices to characterize arrhythmic patterns and dynamics in computer simulations of cardiac tissue. We performed different simulations of cardiac tissues of sizes comparable to the human heart atrium. In these simulations, we observed four classic arrhythmic patterns: a spiral wave anchored to a highly fibrotic region resulting in sustained re-entry, a meandering spiral wave, fibrillation, and a spiral wave anchored to a scar region that breaks up into wavelets away from the main rotor. A detailed analysis revealed that, within the same simulation, maps of RQA metrics could differentiate regions with regular AP propagation from ones with chaotic activity. In particular, the combination of two RQA metrics, the length of the longest diagonal string of recurrence points and the mean length of diagonal lines, was able to identify the location of rotor tips, which are the active elements that maintain spiral waves and fibrillation. By proposing low-dimensional models based on the mean value and spatial correlation of metrics calculated from membrane potential time series, we identify RQA-based metrics that successfully separate the four different types of cardiac arrhythmia into distinct regions of the feature space, and thus might be used for automatic classification, in particular distinguishing between fibrillation driven by self-sustaining chaos and that created by a persistent rotor and wavebreak. We also discuss the practical applicability of such an approach.

Postural threat increases sample entropy of postural control

Introduction

Postural threat elicits modifications to standing balance. However, the underlying neural mechanism(s) responsible remain unclear. Shifts in attention focus including directing more attention to balance when threatened may contribute to the balance changes. Sample entropy, a measure of postural sway regularity with lower values reflecting less automatic and more conscious control of balance, may support attention to balance as a mechanism to explain threat-induced balance changes. The main objectives were to investigate the effects of postural threat on sample entropy, and the relationships between threat-induced changes in physiological arousal, perceived anxiety, attention focus, sample entropy, and traditional balance measures. A secondary objective was to explore if biological sex influenced these relationships.

Methods

Healthy young adults (63 females, 42 males) stood quietly on a force plate without (No Threat) and with (Threat) the expectation of receiving a postural perturbation (i.e., forward/backward support surface translation). Mean electrodermal activity and anterior-posterior centre of pressure (COP) sample entropy, mean position, root mean square, mean power frequency, and power within low (0-0.05 Hz), medium (0.5-1.8 Hz), and high-frequency (1.8-5 Hz) components were calculated for each trial. Perceived anxiety and attention focus to balance, task objectives, threat-related stimuli, self-regulatory strategies, and task-irrelevant information were rated after each trial.

Results and Discussion

Significant threat effects were observed for all measures, except low-frequency sway. Participants were more physiologically aroused, more anxious, and directed more attention to balance, task objectives, threat-related stimuli, and self-regulatory strategies, and less to task-irrelevant information in the Threat compared to No Threat condition. Participants also increased sample entropy, leaned further forward, and increased the amplitude and frequency of COP displacements, including medium and high-frequency sway, when threatened. Males and females responded in the same way when threatened, except males had significantly larger threat-induced increases in attention to balance and high-frequency sway. A combination of sex and threat-induced changes in physiological arousal, perceived anxiety, and attention focus accounted for threat-induced changes in specific traditional balance measures, but not sample entropy. Increased sample entropy when threatened may reflect a shift to more automatic control. Directing more conscious control to balance when threatened may act to constrain these threat-induced automatic changes to balance.

Multiscale Entropy Algorithms to Analyze Complexity and Variability of Trunk Accelerations Time Series in Subjects with Parkinson's Disease

The aim of this study was to assess the ability of multiscale sample entropy (MSE), refined composite multiscale entropy (RCMSE), and complexity index (CI) to characterize gait complexity through trunk acceleration patterns in subjects with Parkinson's disease (swPD) and healthy subjects, regardless of age or gait speed. The trunk acceleration patterns of 51 swPD and 50 healthy subjects (HS) were acquired using a lumbar-mounted magneto-inertial measurement unit during their walking. MSE, RCMSE, and CI were calculated on 2000 data points, using scale factors (τ) 1-6. Differences between swPD and HS were calculated at each τ, and the area under the receiver operating characteristics, optimal cutoff points, post-test probabilities, and diagnostic odds ratios were calculated. MSE, RCMSE, and CIs showed to differentiate swPD from HS. MSE in the anteroposterior direction at τ4 and τ5, and MSE in the ML direction at τ4 showed to characterize the gait disorders of swPD with the best trade-off between positive and negative posttest probabilities and correlated with the motor disability, pelvic kinematics, and stance phase. Using a time series of 2000 data points, a scale factor of 4 or 5 in the MSE procedure can yield the best trade-off in terms of post-test probabilities when compared to other scale factors for detecting gait variability and complexity in swPD.

EEG frequency band analysis in chronic neuropathic pain: A linear and nonlinear approach to classify pain severity

BACKGROUND AND OBJECTIVE

Chronic neuropathic pain (NP) is a chronic pain condition that severely impacts a patient's life. Pain management has proved to be inefficient due to a lack of a simple clinical tool that may identify and monitor NP. A low-cost, noninvasive tool that provides relevant information on NP is the electroencephalogram (EEG). However, the commonly used linear EEG features have proved to be limited in characterizing NP pathophysiology. This study sought to determine whether nonlinear EEG features such as approximate entropy (ApEn) would better differentiate pain severity than absolute band power.

METHODS

A non-parametric statistical approach based on the Brief Pain Inventory (BPI), along with linear and nonlinear EEG features, is proposed in this study. For this purpose, thirty-six chronic NP patients were recruited, and 22 channels were registered. Additionally, a control database of 13 participants with no NP was used as a reference, where 19 channels were registered. For both groups, EEG was recorded for 10 min in a resting state: 5 min with eyes open (EO) and 5 min with eyes closed (EC). Absolute band power and ApEn EEG features in the five clinical frequency bands (delta, theta, alpha, beta, and gamma) were estimated for all channels in both groups. As a result, 220-dimensional and 190-dimensional feature vectors were obtained for experimental and control classes respectively. For the experimental class, NP patients were grouped according to their BPI evaluation in three groups: low, moderate, and high pain. Finally, feature vectors were compared between groups using Kruskal Wallis and post-hoc Dunn's tests.

RESULTS

ApEn revealed significant statistical difference (p <=0.0001) in most frequency bands and conditions among the groups. In contrast, power had less significant differences between groups, particularly with EO. Furthermore, NP groups were notably clustered using only ApEn in theta, alpha, and beta bands.

CONCLUSIONS

The results indicate that ApEn effectively characterizes the different severities of chronic NP rather than the commonly used linear features. ApEn and other nonlinear techniques (e.g., spectral entropy, Shannon entropy) might be a more suitable methodology to monitor chronic NP experience.

Which Multivariate Multi-Scale Entropy Algorithm Is More Suitable for Analyzing the EEG Characteristics of Mild Cognitive Impairment?

So far, most articles using the multivariate multi-scale entropy algorithm mainly use algorithms to analyze the multivariable signal complexity without clearly describing what characteristics of signals these algorithms measure and what factors affect these algorithms. This paper analyzes six commonly used multivariate multi-scale entropy algorithms from a new perspective. It clarifies for the first time what characteristics of signals these algorithms measure and which factors affect them. It also studies which algorithm is more suitable for analyzing mild cognitive impairment (MCI) electroencephalograph (EEG) signals. The simulation results show that the multivariate multi-scale sample entropy (mvMSE), multivariate multi-scale fuzzy entropy (mvMFE), and refined composite multivariate multi-scale fuzzy entropy (RCmvMFE) algorithms can measure intra- and inter-channel correlation and multivariable signal complexity. In the joint analysis of coupling and complexity, they all decrease with the decrease in signal complexity and coupling strength, highlighting their advantages in processing related multi-channel signals, which is a discovery in the simulation. Among them, the RCmvMFE algorithm can better distinguish different complexity signals and correlations between channels. It also performs well in anti-noise and length analysis of multi-channel data simultaneously. Therefore, we use the RCmvMFE algorithm to analyze EEG signals from twenty subjects (eight control subjects and twelve MCI subjects). The results show that the MCI group had lower entropy than the control group on the short scale and the opposite on the long scale. Moreover, frontal entropy correlates significantly positively with the Montreal Cognitive Assessment score and Auditory Verbal Learning Test delayed recall score on the short scale.

Effects of Motor Task Difficulty on Postural Control Complexity during Dual Tasks in Young Adults: A Nonlinear Approach

Few studies have evaluated the effect of a secondary motor task on the standing posture based on nonlinear analysis. However, it is helpful to extract information related to the complexity, stability, and adaptability to the environment of the human postural system. This study aimed to analyze the effect of two motor tasks with different difficulty levels in motor performance complexity on the static standing posture in healthy young adults. Thirty-five healthy participants (23.08 ± 3.92 years) performed a postural single task (ST: keep a quiet standing posture) and two motor dual tasks (DT). i.e., mot-DT(A)—perform the ST while performing simultaneously an easy motor task (taking a smartphone out of a bag, bringing it to the ear, and putting it back in the bag)—and mot-DT(T)—perform the ST while performing a concurrent difficult motor task (typing on the smartphone keyboard). The approximate entropy (ApEn), Lyapunov exponent (LyE), correlation dimension (CoDim), and fractal dimension (detrending fluctuation analysis, DFA) for the mediolateral (ML) and anterior-posterior (AP) center-of-pressure (CoP) displacement were measured with a force plate while performing the tasks. A significant difference was found between the two motor dual tasks in ApEn, DFA, and CoDim-AP (p < 0.05). For the ML CoP direction, all nonlinear variables in the study were significantly different (p < 0.05) between ST and mot-DT(T), showing impairment in postural control during mot-DT(T) compared to ST. Differences were found across ST and mot-DT(A) in ApEn-AP and DFA (p < 0.05). The mot-DT(T) was associated with less effectiveness in postural control, a lower number of degrees of freedom, less complexity and adaptability of the dynamic system than the postural single task and the mot-DT(A).

Clinical measures of balance and gait cannot differentiate somatosensory impairments in people with lower-limb amputation

BACKGROUND

In addition to a range of functional impairments seen in individuals with a lower-limb amputation, this population is at a substantially elevated risk of falls. Studies postulate that the lack of sensory feedback from the prosthetic limb contributes heavily to these impairments, but the extent to which sensation affects functional measures remains unclear.

RESEARCH QUESTION

The purpose of this study is to determine how sensory impairments in the lower extremities relate to performance with common clinical functional measures of balance and gait in individuals with a lower-limb amputation. Here we evaluate the effects of somatosensory integrity to clinical and lab measures of static, reactive and dynamic balance, and gait stability.

METHODS

In 20 individuals with lower-limb amputation (AMP) and 20 age and gender-matched able-bodied controls (CON), we evaluated the effects of sensory integrity (pressure, proprioception, and vibration) on measures of balance and gait. Static, reactive, and dynamic balance were assessed using the Sensory Organization Test (SOT), Motor Control Test (MCT), and Functional Gait Assessment (FGA), respectively. Gait stability was assessed through measures of step length asymmetry and step width variability. Sensation was categorized into intact or impaired sensation by pressure thresholds and differences across groups were analyzed.

RESULTS

There were significant differences between AMP and CON groups for reliance on vision for static balance in the SOT, MCT, and FGA (p < 0.01). Despite differences across groups, there were no significant differences within the AMP group based on intact or impaired sensation across all functional measures.

SIGNIFICANCE

Despite being able to detect differences between able-bodied individuals and individuals with an amputation, these functional measures cannot distinguish between levels of impairment within participants with an amputation. These findings suggest that more challenging and robust metrics are needed to evaluate the effects of sensation and function in individuals with an amputation.

The Impact of Hoffmann Reflex on Standing Postural Control Complexity in the Elderly with Impaired Plantar Sensation

In people with peripheral neuropathy (PN), impaired plantar sensation can cause adaptive changes in the central nervous system (CNS), resulting in changes in the standing postural control, which is reflected in the variability of standing output signals. Standard deviation (SD) and entropy are reliable indicators of system variability, especially since entropy is highly sensitive to diseased populations. The relation between SD and entropy, CNS and center of pressure (COP) variability is unclear for people with severe PN. The purpose of this study was to explore the adaptability of the CNS to the severe of PN and its effect on the degree and complexity of COP variability. Here, people with PN were divided into less affected (LA) and more affected (MA) groups based on plantar pressure sensitivity. We studied Hoffmann reflex (H-reflex) and standing balance performance with the control group (n = 8), LA group (n = 10), and MA group (n = 9), recording a 30 s COP time series (30,000 samples) of double-leg standing with eyes open. We observed that the more affected group had less COP complexity than people without PN. There is a significant negative correlation between the SD and sample entropy in people without PN, less affected and more affected. The COP complexity in people without PN was inversely correlated with H-reflex. We concluded that: (1) The complexity of COP variability in patients with severe plantar sensory impairment is changed, which will not affect the degree of COP variability; (2) The independence of the COP entropy in the AP and ML directions decreased, and the interdependence increased in people with PN; (3) Although the CNS of people with PN has a greater contribution to standing balance, its modulation of standing postural control is decreased.

Approximate entropy analysis across electroencephalographic rhythmic frequency bands during physiological aging of human brain

Aging is the inevitable biological process that results in a progressive structural and functional decline associated with alterations in the resting/task-related brain activity, morphology, plasticity, and functionality. In the present study, we analyzed the effects of physiological aging on the human brain through entropy measures of electroencephalographic (EEG) signals. One hundred sixty-one participants were recruited and divided according to their age into young (n = 72) and elderly (n = 89) groups. Approximate entropy (ApEn) values were calculated in each participant for each EEG recording channel and both for the total EEG spectrum and for each of the main EEG frequency rhythms: delta (2-4 Hz), theta (4-8 Hz), alpha 1 (8-11 Hz), alpha 2 (11-13 Hz), beta 1 (13-20 Hz), beta 2 (20-30 Hz), and gamma (30-45 Hz), to identify eventual statistical differences between young and elderly. To demonstrate that the ApEn represents the age-related brain changes, the computed ApEn values were used as features in an age-related classification of subjects (young vs elderly), through linear, quadratic, and cubic support vector machine (SVM). Topographic maps of the statistical results showed statistically significant difference between the ApEn values of the two groups found in the total spectrum and in delta, theta, beta 2, and gamma. The classifiers (linear, quadratic, and cubic SVMs) revealed high levels of accuracy (respectively 93.20 ± 0.37, 93.16 ± 0.30, 90.62 ± 0.62) and area under the curve (respectively 0.95, 0.94, 0.93). ApEn seems to be a powerful, very sensitive-specific measure for the study of cognitive decline and global cortical alteration/degeneration in the elderly EEG activity.

A Feasibility Study of Bilateral Wrist Sensors for Measuring Motor Traits in Children With Autism

Direct, quantitative measures of hyperactivity and motor coordination, two motor characteristics associated with impairment in autism, are limited. Wearable sensors can objectively index real-world movement variables that may relate to these behaviors. Here, we explored the feasibility of bilateral wrist accelerometers for measuring upper limb activity in 3-10-year-olds with autism (n = 22; 19 boys, 3 girls; M age = 5.64, SD = 2.73 years) and without autism (n = 26; 15 boys, 11 girls; M age = 6.26, SD = 2.47 years). We investigated the relationships between movement characteristics related to duration, intensity, complexity, and symmetry on the one hand and parent-reported hyperactivity and motor coordination on the other. Participants with and without autism wore the sensors for 12-hour periods. Sensor variables varied by age but not sex, with movement intensity and complexity moderately related to motor coordination. These findings lend preliminary support to wearable sensors as a means of providing ecologically-valid metrics of motor characteristics that impact adaptive function in children with autism.

A Comparative Study on the Influence of Undersampling and Oversampling Techniques for the Classification of Physical Activities Using an Imbalanced Accelerometer Dataset

Accelerometer data collected from wearable devices have recently been used to monitor physical activities (PAs) in daily life. While the intensity of PAs can be distinguished with a cut-off approach, it is important to discriminate different behaviors with similar accelerometry patterns to estimate energy expenditure. We aim to overcome the data imbalance problem that negatively affects machine learning-based PA classification by extracting well-defined features and applying undersampling and oversampling methods. We extracted various temporal, spectral, and nonlinear features from wrist-, hip-, and ankle-worn accelerometer data. Then, the influences of undersampilng and oversampling were compared using various ML and DL approaches. Among various ML and DL models, ensemble methods including random forest (RF) and adaptive boosting (AdaBoost) exhibited great performance in differentiating sedentary behavior (driving) and three walking types (walking on level ground, ascending stairs, and descending stairs) even in a cross-subject paradigm. The undersampling approach, which has a low computational cost, exhibited classification results unbiased to the majority class. In addition, we found that RF could automatically select relevant features for PA classification depending on the sensor location by examining the importance of each node in multiple decision trees (DTs). This study proposes that ensemble learning using well-defined feature sets combined with the undersampling approach is robust for imbalanced datasets in PA classification. This approach will be useful for PA classification in the free-living situation, where data imbalance problems between classes are common.

Nonlinear and Linear Measures in the Differentiation of Postural Control in Patients after Total Hip or Knee Replacement and Healthy Controls

Primary osteoarthritis treatments such as a total hip (THR) or knee (TKR) replacement lead to postural control changes reinforced by age. Balance tests such as standing with eyes open (EO) or closed (EC) give a possibility to calculate both linear and nonlinear indicators. This study aimed to find the group of linear and/or nonlinear measures that can differentiate healthy people and patients with TKR or THR from each other. This study enrolled 49 THR patients, 53 TKR patients, and 16 healthy controls. The center of pressure (CoP) path length, sample entropy (SampEn), fractal dimension (FD), and the largest Lyapunov exponent (LyE) were calculated separately for AP and ML directions from standing with EO/EC. Cluster analysis did not result in correct allocation to the groups according to all variables. The discriminant model included LyE (ML-EO, ML-EC, AP-EC), FD (AP-EO, ML-EC, AP-EC), CoP-path AP-EC, and SampEn AP-EC. Regression analysis showed that all nonlinear variables depend on the group. The CoP path length is different only in THR patients. It was concluded that standing with EC is a better way to assess the amount of regularity of CoP movement and attention paid to maintain balance. Nonlinear measures better differentiate TKR and THR patients from healthy controls.

Comparison of Postural Control of Females with and without Urinary Incontinence: A Case-Control Study

Background: So far, there is much less information about the effects of urinary incontinence on postural control. Therefore the aim of this study is to investigate the differences in postural control using linear and non-linear analyses of the center of pressure (COP) time-series in anteroposterior (AP) and mediolateral (ML) directions between females with and without stress urinary incontinence (SUI). Methods: This case-control study included 22 continent females and 22 SUI females. In this study, static postural control during four different postural tasks was evaluated using a force plate. All participants performed separate 60-sec standing trials with eyes open in the empty bladder and full bladder conditions. Mean, range, velocity, area circle of COP displacements, and approximate entropy (ApEn) of COP time-series were calculated from the 60-sec standing trials for all participants. The independent sample t-test was also used to compare COP variables between the two groups and paired sample t-test was used to assess changes between the full bladder and empty bladder conditions within each group. The effect size of Cohen's d was used to assess the magnitude of the differences between the two groups. Results: The findings revealed a significant group × task interaction for the mean of ML displacement and ApEn of COP. SUI females showed more AP displacement range in the full bladder (pvalue= 0.020, effect size=0.74) and a higher velocity (empty bladder: p=0.040, effect size=0.63) (full bladder: p=0.020, effect size=0.75) than the continent group. Generally, the SUI females had lower ApEn than the continent females, although the differences were not significant. While the variables of COP were unaffected by bladder fullness in the continent group, the SUI group in full bladder condition experienced more AP range (p=0.030), and area circle (p=0.007) of COP sway in quiet standing. Conclusion: These results provide more support for the hypothesis that postural control can be impaired following SUI, although future investigations on this topic are recommended.

Transient abnormal signal acquisition system based on approximate entropy and sample entropy

In the field of time domain measurement, with increasing complexity of measured signals, the periodic stationarity of signals is destroyed and the transient non-stationarity starts to stand out, specifically manifested as frequent presence of transient abnormal signals, such as burrs, harmonics, noises, and modulating waves in the periodic signals. By applying the entropy estimation of signals to the field of time domain measurement, this paper designs a transient abnormal signal acquisition system based on approximate entropy (ApEn) and sample entropy (SampEn). In the process of data acquisition, the ApEn and SampEn of sampled data are computed in real time and the complexities of measured signals are differentiated, thus realizing abnormal signal detection. The experimental results demonstrate that SampEn generally has a higher sensitivity and wider application than ApEn in the detection process of transient abnormal signals. The study can provide a new method for the design of a time-domain measuring instrument with abnormal signal detection ability.

Fifty years of Shannon information theory in assessing the accuracy and agreement of diagnostic tests

Since 1948, Shannon theoretic methods for modeling information have found a wide range of applications in several areas where information plays a key role, which goes well beyond the original scopes for which they have been conceived, namely data compression and error correction over a noisy channel. Among other uses, these methods have been applied in the broad field of medical diagnostics since the 1970s, to quantify diagnostic information, to evaluate diagnostic test performance, but also to be used as technical tools in image processing and registration. This review illustrates the main contributions in assessing the accuracy of diagnostic tests and the agreement between raters, focusing on diagnostic test performance measurements and paired agreement evaluation. This work also presents a recent unified, coherent, and hopefully, final information-theoretical approach to deal with the flows of information involved among the patient, the diagnostic test performed to appraise the state of disease, and the raters who are checking the test results. The approach is assessed by considering two case studies: the first one is related to evaluating extra-prostatic cancers; the second concerns the quality of rapid tests for COVID-19 detection.

Analysis of complexity in the EEG activity of Parkinson's disease patients by means of approximate entropy

The objective of the present study is to explore the brain resting state differences between Parkinson's disease (PD) patients and age- and gender-matched healthy controls (elderly) in terms of complexity of electroencephalographic (EEG) signals. One non-linear approach to determine the complexity of EEG is the entropy. In this pilot study, 28 resting state EEGs were analyzed from 13 PD patients and 15 elderly subjects, applying approximate entropy (ApEn) analysis to EEGs in ten regions of interest (ROIs), five for each brain hemisphere (frontal, central, parietal, occipital, temporal). Results showed that PD patients presented statistically higher ApEn values than elderly confirming the hypothesis that PD is characterized by a remarkable modification of brain complexity and globally modifies the underlying organization of the brain. The higher-than-normal entropy of PD patients may describe a condition of low order and consequently low information flow due to an alteration of cortical functioning and processing of information. Understanding the dynamics of brain applying ApEn could be a useful tool to help in diagnosis, follow the progression of Parkinson's disease, and set up personalized rehabilitation programs.

Sample entropy discriminates balance performance of older cannabis users from non-users

BACKGROUND

Maintaining an upright stance involves a complex interaction of sensory processing and motor outputs to adequately perform this fundamental motor skill. Aging and cannabis use independently disrupt balance performance, but our recent data did not find differences in static balance performance between older cannabis Users and older Non-Users using traditional linear measures (i.e., characteristics of the center of pressure sway). The purpose of this analysis was to determine whether an unbiased entropy measure (sample entropy) can differentiate postural control (standing posture) strategies between older cannabis Users and Non-Users when typical linear measures could not.

METHODS

Eight medical cannabis Users and eight age- and sex-matched controls completed static posturography testing in an eyes-open condition for 60 s. Linear measures included pathlength of the anterior-posterior and medio-lateral directions and an ellipse that encapsulates 95% of the 2D area explored. The nonlinear measure was the sample entropy of the center of pressure time-series in anterior-posterior and medio-lateral directions. Group comparisons were accomplished via pairwise testing and effect size calculations.

FINDINGS

The statistical testing revealed that sample entropy in the anterior-posterior direction was significantly larger in the Users (mean ± SD = 0.29 ± 0.08) compared to the Non-Users (0.19 ± 0.05; P = 0.01, d = 1.55).

INTERPRETATION

This finding indicates that the Users had a decreased regularity of their center of pressure signal in the anterior-posterior direction, which might reflect reduced balance adaptability and accompanies the increased fall risk observed in our recent report on these same subjects.

Capturing and Quantifying Tactical Behaviors in Small-Sided and Conditioned Games in Soccer: A Systematic Review

Purpose: To systematically describe and analyze the tracking systems, the variables, and the statistical methods used to evaluate the players and teams' tactical behavior in small-sided and conditioned games (SSCGs). Methods: A search was done in Web of Science, PubMed, Science Direct, and Scielo databases to identify manuscripts published between 2008 and 2019 that manipulated small-sided and conditioned games (SSCGs) and analyzed tactical behaviors of players and teams. Results: From 349 articles identified, 31 were selected for review. To collect positional data, the global positioning system (GPS), the local position measurement (LPM) system, and TACTO were identified as reliable tracking systems. Twenty-one positional variables were identified to evaluate tactical behaviors, grouped into five main categories: team balance, playing space, width and length of playing space, and interpersonal distance. Tactical behavior patterns were analyzed using approximate entropy, sample entropy, Shannon entropy, and patterns of coordination between players and teams were analyzed using relative phase and running correlation. Discussion: The tracking systems analyzed were reliable but revealed different advantages and disadvantages of their use. Authors should define the use of each tracking system based on their purpose and level of precision required for analysis. A great duplication was observed on the variables used with similar purposes of tactical analysis. The identification of the variables according to their purpose of analysis will allow a better understanding of their use in the future.

Tangle: A metric for quantifying complexity and erratic behavior in short time series

Temporal complexity refers to qualities of a time series that are emergent, erratic, or not easily described by linear processes. Quantifying temporal complexity within a system is key to understanding the time based dynamics of said system. However, many current methods of complexity quantification are not widely used in psychological research because of their technical difficulty, computational intensity, or large number of required data samples. These requirements impede the study of complexity in many areas of psychological science. A method is presented, tangle, which overcomes these difficulties and allows for complexity quantification in relatively short time series, such as those typically obtained from psychological studies. Tangle is a measure of how dissimilar a given process is from simple periodic motion. Tangle relies on the use of a three-dimensional time delay embedding of a one-dimensional time series. This embedding is then iteratively scaled and premultiplied by a modified upshift matrix until a convergence criterion is reached. The efficacy of tangle is shown on five mathematical time series and using emotional stability, anxiety time series data obtained from 65 socially anxious participants over a 5-week period, and positive affect time series derived from a single participant who experienced a major depression episode during measurement. Simulation results show tangle is able to distinguish between different complex temporal systems in time series with as few as 50 samples. Tangle shows promise as a reliable quantification of irregular behavior of a time series. Unlike many other complexity quantification metrics, tangle is technically simple to implement and is able to uncover meaningful information about time series derived from psychological research studies. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

Postural Control and Adaptation Strategy of Young Adults on Unstable Surface

Balance control is essential for postural adjustment in physical activities. This study investigates the behavior of human postural control and the coordination and adaptation strategy of hip, knee, and ankle when standing on an unstable surface. Twenty participants were recruited. Four different conditions were investigated: a quiet bipedal stance with eyes open and eyes closed, and standing on an unstable surface with eyes open and eyes closed. Other than the joint angle, the standard body sway measures, such as sway area and sway velocity, were computed. A nonlinear time series measure, that is, sample entropy, was used to determine the regularity of the time series and body adaptability to change and perturbation. The results show that the body sway increases as the difficulty increases. This study also confirms the coordination of the hip, knee, and ankle to maintain body balance on the unstable surface by decreasing the joint angle and adopting a lower posture. Even though the individual joint has lower sample entropy value and is deemed to be rigid and less adaptive to perturbation, the postural control exhibits higher sample entropy value, particularly in the anterior–posterior direction, and has the ability to stabilize the body by manipulating the joints simultaneously. These outcomes suggest that an unstable surface not only challenges the human postural control, but also reduces the hip, knee, and ankle adaptability to perturbation, thus making it a great tool to train body balance.

Deficient Interhemispheric Connectivity Underlies Movement Irregularities in Parkinson's Disease

BACKGROUND

Movement execution is impaired in patients with Parkinson's disease. Evolving neurodegeneration leads to altered connectivity between distinct regions of the brain and altered activity at interconnected areas. How connectivity alterations influence complex movements like drawing spirals in Parkinson's disease patients remains largely unexplored.

OBJECTIVE

We investigated whether deteriorations in interregional connectivity relate to impaired execution of drawing.

METHODS

Twenty-nine patients and 31 age-matched healthy control participants drew spirals with both hands on a digital graphics tablet, and the regularity of drawing execution was evaluated by sample entropy. We recorded resting-state fMRI and task-related EEG, and calculated the time-resolved partial directed coherence to estimate effective connectivity for both imaging modalities to determine the extent and directionality of interregional interactions.

RESULTS

Movement performance in Parkinson's disease patients was characterized by increased sample entropy, corresponding to enhanced irregularities in task execution. Effective connectivity between the motor cortices of both hemispheres, derived from resting-state fMRI, was significantly reduced in Parkinson's disease patients in comparison to controls. The connectivity strength in the nondominant to dominant hemisphere direction in both modalities was inversely correlated with irregularities during drawing, but not with the clinical state.

CONCLUSION

Our findings suggest that interhemispheric connections are affected both at rest and during drawing movements by Parkinson's disease. This provides novel evidence that disruptions of interhemispheric information exchange play a pivotal role for impairments of complex movement execution in Parkinson's disease patients.

On Quantization Errors in Approximate and Sample Entropy

Approximate and sample entropies are acclaimed tools for quantifying the regularity and unpredictability of time series. This paper analyses the causes of their inconsistencies. It is shown that the major problem is a coarse quantization of matching probabilities, causing a large error between their estimated and true values. Error distribution is symmetric, so in sample entropy, where matching probabilities are directly summed, errors cancel each other. In approximate entropy, errors are accumulating, as sums involve logarithms of matching probabilities. Increasing the time series length increases the number of quantization levels, and errors in entropy disappear both in approximate and in sample entropies. The distribution of time series also affects the errors. If it is asymmetric, the matching probabilities are asymmetric as well, so the matching probability errors cease to be mutually canceled and cause a persistent entropy error. Despite the accepted opinion, the influence of self-matching is marginal as it just shifts the error distribution along the error axis by the matching probability quant. Artificial lengthening the time series by interpolation, on the other hand, induces large error as interpolated samples are statistically dependent and destroy the level of unpredictability that is inherent to the original signal.

Disparity between Perceptual Fall Risk and Physiological Fall Risk in Older Cannabis Users: A Pilot Study

Aging is associated with cognitive decline and increased fall risk. Cognitive impairment is associated with cannabis use, which is increasing among older adults. Perceptual and physiological fall risk are discordant in some older adults, but whether cannabis use influences this association is unknown. The purpose of this study was to investigate possible disparities between perceptual and physiological fall risk in older cannabis users. Eight older medical cannabis users and eight sex- and age-matched non-users provided data on perceptual and physiological fall risk. Group differences were assessed, and perceptual fall risk was correlated with physiological fall risk. Perceptual risk and most of the physiological fall risk variables were equivalent between the groups. However, cannabis users performed significantly worse on unipedal stance than non-users. In addition, perceptual fall risk had weak correlations with physiological fall risk in the users (Spearman’s rho = 0.17–0.41) and moderate-strong correlations in non-users (rho = −0.18–0.67). Cannabis users might have a discrepancy between perceptual and physiological fall risk. Because both concepts play a role in quality of life, identifying strategies to improve them may have significant benefits. Future studies investigating additional perceptual (e.g., cognition, fear of falling, depression, anxiety), physiological (e.g., more challenging static and dynamic balance conditions), and general fall risk are warranted.