Gait dynamics, fractals and falls: finding meaning in the stride-to-stride fluctuations of human walking

Gait variability predicts post-fatigue obstacle course performance among military cadets: An exploratory study

We explored the extent to which pre-fatigue gait variability during load carriage is associated with the ability of an individual to perform an obstacle course post-fatigue. Twenty-four military cadets were monitored during treadmill gait and completed an obstacle course before and after a full-body fatigue protocol. Gait variability measures were determined from spatiotemporal stride characteristics, joint angle trajectories, and inter-joint coordination. These measures were then used in multiple linear regression models to predict three measures of post-fatigue performance (i.e., hurdle completion time, maximum jump height, and maximum jump distance). Measures of joint kinematic variability predicted 73-89% of the variance in post-fatigue performance. Specifically, the significant predictors were sagittal plane variability of 1) hip angle and hip-knee coordination during swing phase; and 2) knee-ankle coordination during both stance and swing phase. Measures of joint kinematic variability obtained from gait thus appear relevant for predicting individual differences in adapting to fatigue, and such measures could aid in predicting post-fatigue performance in diverse dynamic tasks.

Verbal arm swing instructions alter arm-leg interlimb coordination but not prefrontal cortex hemodynamics in people with Parkinson's disease

Verbal instructions related to the arm swing amplitude and velocity change step gait behavior in people with Parkinson's disease (PwPD) and neurotypical individuals. However, how verbal instructions related to upper limb act on interlimb coordination and prefrontal cortex activation are not yet known. Therefore, the aim of this study was to investigate the effects of the instructions to increase arm swing amplitude and velocity during walking on prefrontal cortex (PFC) hemodynamics and arm-leg interlimb coordination in PwPD and neurotypical individuals. Fifteen PwPD and 13 neurotypical individuals walked over a 26.8 m pathway under three experimental conditions: usual walking, walking with increased arm swing amplitude, and walking with increased arm swing velocity. Gait step parameters, continuous relative phase and latency between arm and leg movements, and PFC hemodynamics were calculated. ANOVA two-way (groups x conditions) showed that the verbal instructions to increase arm swing amplitude and velocity during walking improved gait step parameters and arm-leg interlimb coordination, without changing PFC hemodynamics. Specifically, verbal instructions increased average continuous relative phase (F2,52 = 45.5; p < 0.001; ηp2 = 0.63) and decreased the average relative phase variability (F2,52 = 86.9; p < 0.001; ηp2 = 0.77) in both groups and decreased PwPD latency (F2,52 = 3.5; p = 0.03; ηp2 = 0.19). Verbal instructions also increased stride length (F2,52 = 27.7; p < 0.001; ηp2 = 0.51) and velocity (F2,52 = 46.6; p < 0.001; ηp2 = 0.64) and decreased double support phase in both groups. These results allow us to speculate that the engagement of the motor areas to follow the instructions and perform the ensuing action could be related to preservation of some automaticity and it is possible that the participants do not need to use their cognitive resources by increasing PFC activity to process and do the action.

Precision in Brief: The Bayesian Hurst-Kolmogorov Method for the Assessment of Long-Range Temporal Correlations in Short Behavioral Time Series

Various fields within biological and psychological inquiry recognize the significance of exploring long-range temporal correlations to study phenomena. However, these fields face challenges during this transition, primarily stemming from the impracticality of acquiring the considerably longer time series demanded by canonical methods. The Bayesian Hurst-Kolmogorov (HK) method estimates the Hurst exponents of time series-quantifying the strength of long-range temporal correlations or "fractality"-more accurately than the canonical detrended fluctuation analysis (DFA), especially when the time series is short. Therefore, the systematic application of the HK method has been encouraged to assess the strength of long-range temporal correlations in empirical time series in behavioral sciences. However, the Bayesian foundation of the HK method fuels reservations about its performance when artifacts corrupt time series. Here, we compare the HK method's and DFA's performance in estimating the Hurst exponents of synthetic long-range correlated time series in the presence of additive white Gaussian noise, fractional Gaussian noise, short-range correlations, and various periodic and non-periodic trends. These artifacts can affect the accuracy and variability of the Hurst exponent and, therefore, the interpretation and generalizability of behavioral research findings. We show that the HK method outperforms DFA in most contexts-while both processes break down for anti-persistent time series, the HK method continues to provide reasonably accurate H values for persistent time series as short as N=64 samples. Not only can the HK method detect long-range temporal correlations accurately, show minimal dispersion around the central tendency, and not be affected by the time series length, but it is also more immune to artifacts than DFA. This information becomes particularly valuable in favor of choosing the HK method over DFA, especially when acquiring a longer time series proves challenging due to methodological constraints, such as in studies involving psychological phenomena that rely on self-reports. Moreover, it holds significance when the researcher foreknows that the empirical time series may be susceptible to contamination from these processes.

Restoring the complexity of walking in the elderly and its impact on clinical measures around the risk of falls

Introduction: The hypothesis of the loss of complexity with aging and disease has received strong attention. Especially, the decrease of complexity of stride interval series in older people, during walking, was shown to correlate with falling propensity. However, recent experiments showed that a restoration of walking complexity in older people could occur through the prolonged experience of synchronized walking with a younger companion. This result was interpreted as the consequence of a complexity matching effect. Experiment: The aim of the present study was to analyze the link between the restoration of walking complexity in older people and clinical measures usually used in the context of rehabilitation or follow-up of older people. Results: We evidenced a link between restoring complexity, improving overall health and reducing fear of falling. In addition, we showed that 3 weeks of complexity matching training can have a positive effect on complexity up to 2 months post-protocol. Finally, we showed that the restoration of walking complexity obtained in the previous works is not guide-dependent.

The effect of pain on gait in older people: A systematic review and meta-analysis

Multi-site pain is common in people aged 60 years and over and is associated with a high risk of falls. To prevent and treat pain-related disabilities, it is crucial to identify the mechanisms underlying these associations. There is some evidence that pain leads to changes in walking, such as slower gait speed and shorter walking distance, which impair mobility and may increase the risk of falls. This review evaluated evidence on the relationship between pain and gait characteristics in older people. A comprehensive search on PubMed and Embase included observational studies and clinical trials assessing objective measures of walking, such as gait speed, cadence, stride length, and double-limb support time, in older people with and without pain. Of the 1218 studies screened, thirteen met the inclusion criteria from the primary search. An additional study was identified through the secondary search, resulting in fourteen studies included in this systematic review and meta-analysis. None of these studies investigated the relationship between fear of pain and gait characteristics in older people. Results showed that older people with pain had slower gait speed than those without pain, with a small effect size (Hedge's g = -0.30, 95% CI = -0.41 to -0.19, p < 0.0001). There were no statistically significant differences in cadence, stride length, and double-limb support time. These findings suggest that pain impacts walking speed in older people, highlighting the importance of addressing this association to manage mobility deficits and fall risk. PERSPECTIVE: This systematic review and meta-analysis show that pain is associated with reduced gait speed in older people. Recognising and addressing the impact of pain on walking may be important for preventing mobility-related disorders and falls in this population.

A new parallel-path ConvMixer neural network for predicting neurodegenerative diseases from gait analysis

Neurodegenerative disorders (NDD) represent a broad spectrum of diseases that progressively impact neurological function, yet available therapeutics remain conspicuously limited. They lead to altered rhythms and dynamics of walking, which are evident in the sequential footfall contact times measured from one stride to the next. Early detection of aberrant walking patterns can prevent the progression of risks associated with neurodegenerative diseases, enabling timely intervention and management. In this study, we propose a new methodology based on a parallel-path ConvMixer neural network for neurodegenerative disease classification from gait analysis. Earlier research in this field depended on either gait parameter-derived features or the ground reaction force signal. This study has emerged to combine both ground reaction force signals and extracted features to improve gait pattern analysis. The study is being carried out on the gait dynamics in the NDD database, i.e., on the benchmark dataset Physionet gaitndd. Leave one out cross-validation is carried out. The proposed model achieved the best average rates of accuracy, precision, recall, and an F1-score of 97.77 % , 96.37 % , 96.5 % , and 96.25 % , respectively. The experimental findings demonstrate that our approach outperforms the best results achieved by other state-of-the-art methods.

Relationships between spatiotemporal and kinematic domains during treadmill gait change across adulthood

BACKGROUND

Spatiotemporal and kinematic variables during gait undergo characteristic changes with aging. However, the relationships between these domains, and how these change with aging, have not been extensively investigated.

RESEARCH QUESTION

How does age affect relationships between spatiotemporal and joint/segment range-of-motion variables during treadmill gait?

METHODS

In this cross-sectional study, a motion capture system tracked 60 participants (20-80 years old), walking at self-selected and slow speeds on a treadmill. Spatiotemporal (step length, width, time, velocity) and range-of-motion (ankle, knee, hip, pelvis, trunk) variables were extracted from 50 steps at each speed. Mixed-effects models were used to quantify relationships between spatiotemporal variables and age, range-of-motion, and interactions between age and range-of-motion.

RESULTS

Significant relationships with range-of-motion were found for some spatiotemporal variables; the direction of the relationship was most often positive, with several negative relationships. Significant interaction effects were observed for several pairings (ankle range-of-motion - step length, ankle range-of-motion - step velocity, hip range-of-motion - step velocity), with stronger relationships between spatiotemporal and range-of-motion variables as age increased.

SIGNIFICANCE

Stronger relationships at both the ankle and hip in older adults may suggest that older adults rely more on motion at these joints, and constrain other degrees-of-freedom, in an attempt to maintain gait velocity for successful task execution and/or safety on the treadmill. This study statistically quantifies the effects of age on the relationships between spatiotemporal and kinematic domains while accounting for stride-to-stride variations during gait, which provides insight into the control of spatiotemporal variables in healthy individuals across adulthood, and may inform strategies for identifying gait dysfunction with aging.

Plantar pressure variability as a measure of cognitive load during gait

BACKGROUND

Cognitive decline impairs communications between the brain and the sensory systems but also alters gait, which explains why demented patients exhibit an increased risk of falling. Since cognition processes and gait control share a common neural network, cognitive loading has been shown to induce the same brain activity in healthy subjects as in demented patients.

RESEARCH QUESTION

Our overarching goal is to develop clinical methods based on gait variability to detect cognitive decline. Our main hypothesis is that gait variability discriminates between different cognitive loads applied to healthy younger subjects.

METHODS

Twenty-eight subjects walked on an instrumented treadmill at a self-selected pace for three-minutes under different levels of cognitive loadings (none, low and high). These loadings were applied by requesting the subjects to perform specific arithmetic operations while walking. Variability of eight parameters were quantified over 340 steps using coefficients of variation.

RESULTS

The variability of three of these eight parameters showed significant differences between different cognitive loads: center of pressure displacement in the ML direction and peak pressure under the heel and toe.

SIGNIFICANCE

These parameters can be measured using simple pressure insoles, thus enabling clinical use for early detection of dementia.

Effect of sleep deprivation on gait complexity

Gait complexity is considered an indicator of adaptability, reflecting the complex interaction between multiple components of the neuromuscular system. Previous research provided evidence that chronobiology, which reflects the individual expression of circadian rhythms, affects the regulation of gait dynamics. The literature also suggests the disruption of these circadian rhythms affects multiple human physiological systems. Considering the association between chronobiology and gait complexity, and its clinical relevance, it would be important to investigate whether the disruption of sleep-wake cycle could affect gait complexity. This study aimed to investigate the effect of 1 night of sleep deprivation on gait complexity and variability of healthy individuals, exploring potential implications for motor control. Seventeen healthy and young male adults underwent an in-lab supervised 24-hr sleep deprivation protocol, with gait complexity and variability assessed using detrended fluctuation analysis and coefficient of variation, respectively. Chronotype was also assessed through the Morningness-Eveningness Questionnaire. We observed a loss of gait complexity with sleep deprivation (PRE: 0.8 ± 0.13; POST24: 0.62 ± 0.08, p < 0.001), while gait variability remained unaltered (p = 0.132). Additionally, we demonstrated an association between gait complexity's relative changes and chronotype (r = -0.665, p = 0.004). Overall, our findings suggest sleep deprivation induces a decrease in the neuromuscular system's ability to flexibly adapt gait output. Moreover, we also highlight the importance of chronobiology in motor control, as we observed the more morning-type an individual is, the greater the loss of complexity following 1 night of sleep deprivation. Altogether, our findings underscore the potential impact of sleep deprivation on central processes underlying gait complexity.

Louis EK, Lowe VJ, Petersen RC, Ali F, Ehgoetz Martens K. Identifying gait differences between Alzheimer's disease and dementia with Lewy bodies and their associations with regional amyloid deposition

INTRODUCTION

We aimed to compare gait between individuals with Alzheimer's disease (AD), dementia with Lewy bodies (DLB), and cognitively unimpaired (CU) individuals and to evaluate the association between gait and regional amyloid beta (Aβ) burden in AD and DLB.

METHODS

We included 420 participants (70 AD, 70 DLB, 280 CU) in the Mayo Clinic Study of Aging (MCSA). Gait was assessed using a pressure-sensor walkway. Aβ deposition was analyzed with Pittsburgh compound B (PiB) positron emission topography (PET).

RESULTS

The DLB group had reduced stride velocity, step length, and stride width variability, as well as increased double support percentage (%DS) and variability in step length, swing time, and step time compared to the AD and CU groups. Aβ burden was not associated with any gait outcomes.

DISCUSSION

This study provides additional evidence that gait differs between AD and DLB. Larger studies are needed to investigate associations between Aβ burden and gait outcomes in dementia.

HIGHLIGHTS

Gait was more impaired in dementia than in cognitively unimpaired (CU) controls. Compared with Alzheimer's disease (AD), Dementia with Lewy bodies (DLB) had more impaired pace, variability, and postural control. Step length and double support (%) distinguished DLB and AD with moderate accuracy.

Intra-individual variability in cognitive performance predicts functional decline in Parkinson's disease

BACKGROUND

Cognitive deficits contribute to disability in Parkinson's disease (PD). Cognitive intra-individual variability (IIV) is associated with cognitive decline in age-related disorders, but IIV has not been related to functional ability in PD. We examined IIV in predicting functional ability in participants with PD.

METHODS

De-identified National Alzheimer's Coordinating Center data (N = 1,228) from baseline and follow-up visits included participants with PD propensity score matched to control participants at baseline on age (M = 72), education (M = 15), and gender (28% female). PD symptom duration averaged 6 years. Outcome measures included the Functional Ability Questionnaire (FAQ), overall test battery mean (OTBM) of ten cognitive variables, IIV calculated as the standard deviation of cognitive data for each participant, Geriatric Depression Scale (GDS), and Unified PD Rating Scale gait and posture items. Baseline FAQ status in the PD group was predicted using logistic regression with age, education, cognition, GDS, and motor function as predictors. We compared baseline characteristics of PD participants with and without functional impairment at follow up.

RESULTS

PD participants showed lower OTBM and greater IIV, GDS, and motor dysfunction than controls (p < .0001). Education, OTBM, IIV, GDS, and gait predicted functional status (77% overall classification; AUC = .84). PD participants with functional impairment at follow up showed significantly lower OTBM and greater IIV, GDS, and motor dysfunction at baseline (p < .001).

CONCLUSION

IIV independently predicts functional status in participants with PD while controlling for other variables. PD participants with functional impairment at follow up showed greater IIV than those without functional impairment at follow up.

Gait Parameters in Healthy Older Adults in Korea

OBJECTIVE

Gaits constitute the most fundamental and common form of human locomotion and are essential in daily activities. We aimed to investigate gait parameters in medically and cognitively healthy older adults to determine the independent effects of age, physical attributes, and cognition on these parameters.

METHODS

This retrospective study enrolled healthy older adult participants aged 50 years or older with normal cognition and no neurological symptoms or medical/surgical history that could affect gait. Quantitative gait analysis was conducted via the GAITRite Electronic Walkway, which categorizes gait parameters into spatiotemporal, spatial, temporal, phase, and variability. Gait parameters were compared between sexes across different age groups. The independent effects of age, Mini-Mental State Examination score, and physical characteristics were analyzed via a multiple regression model.

RESULTS

This study included 184 participants with an average age of 72.2 years. After adjusting for age, height, and footwear, only the base width and its variability differed between the sexes. Gait parameters varied significantly among different age groups, revealing multiple interparameter associations. Age was independently correlated with decreased velocity, step and stride lengths, single support time percentage and increased double support time, double support time percentage, and variability parameters, excluding the coefficient of variance of base width. Height was positively correlated with velocity, step and stride lengths, and base width, whereas leg length was negatively associated with cadence and positively associated with temporal parameters of gait.

CONCLUSION

Gait parameters in healthy older adults were not only associated with age and physical characteristics but also had interparameter correlations.

Changes in torque complexity and maximal torque after a fatiguing exercise protocol

Torque outputs exhibit non-random fluctuations in their temporal structure, i.e., complexity. Fatigue has been shown to alter this structure. The torque outputs typically become more regular, resulting in decreased adaptability. Importantly, torque complexity was shown a different recovery pattern after fatigue compared to maximal torque. However, it remains to be understood if these uncoupled patterns of recovery are muscle dependent. In addition, it also remains to be investigated if changes in maximal torque and complexity are correlated. This study investigated (i) the effects of a fatiguing protocol on the complexity and maximal torque from plantar flexors and (ii) the relationship between changes in these two outputs. Ten participants visited the laboratory, and measures were taken at baseline, immediately after, 1 h after and 24 h after the fatiguing protocol. Maximum voluntary contraction, isometric contractions at 30% of maximum and pain pressure threshold were collected. Both legs were assessed, but only one was given the fatiguing protocol. Two-way ANOVAs and correlations were conducted. The fatiguing protocol decreased torque complexity (~35%) and maximal torque (~20%), and they exhibited uncoupled patterns of recovery. Moreover, the correlation analysis showed no correlation between changes in these parameters. These findings support that these parameters are independent of each other.

How Gait Nonlinearities in Individuals Without Known Pathology Describe Metabolic Cost During Walking Using Artificial Neural Network and Multiple Linear Regression

This study uses Artificial Neural Networks (ANNs) and multiple linear regression (MLR) models to explore the relationship between gait dynamics and the metabolic cost. Six nonlinear metrics—Lyapunov Exponents based on Rosenstein’s algorithm (LyER), Detrended Fluctuation Analysis (DFA), the Approximate Entropy (ApEn), the correlation dimension (CD), the Sample Entropy (SpEn), and Lyapunov Exponents based on Wolf’s algorithm (LyEW)—were utilized to predict the metabolic cost during walking. Time series data from 10 subjects walking under 13 conditions, with and without hip exoskeletons, were analyzed. Six ANN models, each corresponding to a nonlinear metric, were trained using the Levenberg–Marquardt backpropagation algorithm and compared with MLR models. Performance was assessed based on the mean squared error (MSE) and correlation coefficients. ANN models outperformed MLR, with DFA and Lyapunov Exponent models showing higher R2 values, indicating stronger predictive accuracy. The results suggest that gait’s nonlinear characteristics significantly impact the metabolic cost, and ANNs are more effective for analyzing these dynamics than MLR models. The study emphasizes the potential of focusing on specific nonlinear gait variables to enhance assistive device optimization, particularly for hip exoskeletons. These findings support the development of personalized interventions that improve walking efficiency and reduce metabolic demands, offering insights into the design of advanced assistive technologies.

Running Gait Complexity During an Overground, Mass-Participation Five-Kilometre Run

Human locomotion contains innate variability which may provide health insights. Detrended fluctuation analysis (DFA) has been used to quantify the temporal structure of variability for treadmill running, although it has been less commonly applied to uncontrolled overground running. This study aimed to determine how running gait complexity changes in response to gradient and elapsed exercise duration during uncontrolled overground running. Sixty-eight participants completed an overground, mass-participation five-kilometre run (a parkrun). Stride times were recorded using an inertial measurement unit mounted on the distal shank. Data were divided into four consecutive intervals (uphill lap 1, downhill lap 1, uphill lap 2, downhill lap 2). The magnitude (SD) and structure (DFA) of stride time variability were compared across elapsed exercise duration and gradient using a repeated-measures ANOVA. Participants maintained consistent stride times throughout the run. Stride time DFA-α displayed a moderate decrease (d = |0.39| ± 0.13) during downhill running compared to uphill running. DFA-α did not change in response to elapsed exercise duration, although a greater stride time SD was found during the first section of lap 1 (d = |0.30| ± 0.12). These findings suggest that inter- and intra-run changes in gait complexity should be interpreted in the context of course elevation profiles before conclusions on human health are drawn.

Monitoring Age-Related Changes in Gait Complexity in the Wild with a Smartphone Accelerometer System

Stride-to-stride fluctuations during walking reflect age-related changes in gait adaptability and are estimated with nonlinear measures that confine data collection to controlled settings. Smartphones, with their embedded accelerometers, may provide accessible gait analysis throughout the day. This study investigated age-related differences in linear and nonlinear gait measures estimated from a smartphone accelerometer (SPAcc) in an unconstrained, free-living environment. Thirteen young adults (YA) and 11 older adults (OA) walked within a shopping mall with a SPAcc placed in their front right pants pocket. The inter-stride interval, calculated as the time difference between ipsilateral heel contacts, was used for dependent measures calculations. One-way repeated-measures analysis of variance revealed significant (p < 0.05) age-related differences (mean: YA, OA) for stride-time standard deviation (0.04 s, 0.05 s) and coefficient of variation (3.47%, 4.16%), sample entropy (SaEn) scale 1 (1.70, 1.86) and scale 3 (2.12, 1.80), and statistical persistence decay (31 strides, 23 strides). The fractal scaling index was not different between groups (0.93, 0.95), but exceeded those typically found in controlled settings, suggesting an upregulation in adaptive behaviour likely to accommodate the increased challenge of free-living walking. These findings support the SPAcc as a viable telehealth instrument for remote monitoring of gait dynamics, with implications for unsupervised fall-risk assessment.

An Objective Assessment of Neuromotor Control Using a Smartphone App After Repeated Subconcussive Blast Exposure

Subconcussive blast exposure has been shown to alter neurological functioning. However, the extent to which neurological dysfunction persists after blast exposure is unknown. This longitudinal study examined the potential short- and long-term effects of repeated subconcussive blast exposure on neuromotor performance from heavy weapons training in military personnel. A total of 214 participants were assessed; 137 were exposed to repeated subconcussive blasts and 77 were not exposed to blasts (controls). Participants completed a short stepping-in-place task while an Android smartphone app placed on their thigh recorded movement kinematics. We showed acute suppression of neuromotor variability 6 h after subconcussive blast exposure, followed by a rebound to levels not different from baseline at the 72 h, 2-week, and 3-month post-tests. It is postulated that this suppression of neuromotor variability results from a reduction in the functional degrees of freedom from the subconcussive neurological insult. It is important to note that this change in behavior is short-lived, with a return to pre-blast exposure movement kinematics within 72 h.

Associations between less knee kinematic variability and worse patient-reported outcomes following anterior cruciate ligament reconstruction

Individuals with anterior cruciate ligament reconstruction (ACLR) exhibit less knee kinematic variability while walking than uninjured controls, associated with deleterious changes in cartilage composition linked to an increased risk for early knee osteoarthritis (KOA). It is unknown whether less knee kinematic variability is also associated with worse knee-related patient-reported outcomes (PROs) consistent with KOA development. This study examined associations between kinematic variability during gait and PROs in individuals post-ACLR. Gait kinematics and the Knee Injury and Osteoarthritis Outcome Score (KOOS) were collected from 45 participants 6-months post-ACLR (67% Females; 21.45 ± 4.56 years). Overground gait biomechanics using 3D motion capture were collected, and knee kinematics were extracted for post-processing. Sample entropy (SampEn) was used to calculate knee kinematic variability. Pearson's product-moment correlations were conducted to determine the associations between SampEn and KOOS sub-scores. Additionally, independent samples t-tests were performed to evaluate potential differences in SampEn outcomes between individuals with and without clinically relevant symptoms (defined in the introduction). Less sagittal plane kinematic variability is associated with greater pain (r = 0.37, p = 0.01) and symptoms (r = 0.32, p = 0.03). Symptomatic participants demonstrated less sagittal plane knee kinematic variability compared to asymptomatic participants (p = 0.01). The findings suggest less variable gait patterns 6-months post-ACLR may be linked to KOA-related symptoms.

Effects of extension ladder fly configuration on climbing safety

Fall injuries often occur on extension ladders. The extendable fly section of an extension ladder is typically closer to the user than the base section, though this design is minimally justified. This study investigates the effects of reversing the fly on foot placement, frictional requirements, adverse stepping events (repositioning the foot or kicking the rung), and user preferences. Participant foot placement was farther posterior (rung contacted nearer to toes) in the traditional ladder compared to the reversed fly condition during descent, with farther anterior foot placements during ascent. The reversed configuration had similar friction requirements during early/mid stance and significantly lower frictional requirements during late stance. Increased friction requirements during late stance were associated with farther anterior foot placement and further plantar flexed foot orientation. The reversed fly had 5 adverse stepping events versus 22 that occurred in the traditional configuration. Users typically preferred the reversed fly. These results suggest that a reversed extension ladder configuration offers potential benefits in reducing fall-related injuries that should motivate future research and development work.

Validation of Linear and Nonlinear Gait Variability Measures Derived From a Smartphone System Compared to a Gold-Standard Footswitch System During Overground Walking

Smartphones, with embedded accelerometers, may be a viable method to monitor gait variability in the free-living environment. However, measurements estimated using smartphones must first be compared to known quantities to ensure validity. This study assessed the validity and reliability of smartphone-derived gait measures compared to a gold-standard footswitch system during overground walking. Seventeen adults completed three 8-minute overground walking trials during 3 separate visits. The stride time series was calculated as the time difference between consecutive right heel contact events within the footswitch and smartphone-accelerometry signals. Linear (average stride time, stride time standard deviation, and stride time coefficient of variation) and nonlinear (fractal scaling index, approximate entropy, and sample entropy) measures were calculated for each stride time series. Bland-Altman plots with 95% limits of agreement assessed agreement between systems. Intraclass correlation coefficients assessed reliability across visits. Bland-Altman plots revealed acceptable limits of agreement for all measures. Intraclass correlation coefficients revealed good-to-excellent reliability for both systems, except for fractal scaling index, which was moderate. The smartphone system is a valid method and performs similarly to gold-standard research equipment. These findings suggest the development and implementation of an inexpensive, easy-to-use, and ubiquitous telehealth instrument that may replace traditional laboratory equipment for use in the free-living environment.

The repeatability of stride time variability, regularity, and long-range correlations

BACKGROUND

Detrended fluctuation analysis (DFA) and sample entropy (SE) measure the long-term correlations and regularity of gait patterns, respectively, having previously been used to identify participants at risk of falling, previous history of injury, or patients with motor diseases. Since these measures are more sensitive to gait impairment than linear measures (e.g., the standard deviation [SD] of stride time), they can be potentially used in military medicine to identify soldiers at risk of injury. However, clinometric properties are yet to be established.

RESEARCH QUESTION

What is the repeatability of DFA, SE, and traditional linear measures of stride time variability (SD and coefficient of variation [CV]) under various load and speed constraints?

METHODS

Fourteen Australian Army trainee soldiers (age: 25.6 ± 5.9 y, height: 1.74 ± 0.08 m, body mass: 77.2 ± 15.1 kg, service: 1.5 ± 1.8 y) attended three sessions over two weeks, completing four 12-minute walking trials on an instrumented treadmill in each session. Participants walked with a combination of 0 kg or 23 kg loads at a self-selected or 5.5 km/h speed. Heel contacts from the right foot were identified using treadmill-embedded force plates. From 512 stride time intervals, linear (SD and CV), and non-linear (DFA and SE) measures were obtained. To assess the between-session repeatability, intraclass correlations (ICC 2,1) were employed.

RESULTS AND SIGNIFICANCE

There was poor-to-moderate repeatability for the SD (ICC: 0.357-0.545) and CV (ICC: 0.371-0.529). DFA showed poor-to-moderate repeatability (ICC: 0.013-0.504), while SE had poor repeatability (ICC: 0.133-0.226). Previous studies have shown that differences of > 0.19 in DFA and > 0.66 in SE can differentiate between healthy and pathological gait. These values are greater than this study's reported standard error of measurement, indicating that clinically meaningful changes may still be detectable despite low repeatability.

Development of a Gait Analysis Application for Assessing Upper and Lower Limb Movements to Detect Pathological Gait

Pathological gait in patients with Hakim's disease (HD, synonymous with idiopathic normal-pressure hydrocephalus; iNPH), Parkinson's disease (PD), and cervical myelopathy (CM) has been subjectively evaluated in this study. We quantified the characteristics of upper and lower limb movements in patients with pathological gait. We analyzed 1491 measurements of 1 m diameter circular walking from 122, 12, and 93 patients with HD, PD, and CM, respectively, and 200 healthy volunteers using the Three-Dimensional Pose Tracker for Gait Test. Upper and lower limb movements of 2D coordinates projected onto body axis sections were derived from estimated 3D relative coordinates. The hip and knee joint angle ranges on the sagittal plane were significantly smaller in the following order: healthy > CM > PD > HD, whereas the shoulder and elbow joint angle ranges were significantly smaller, as follows: healthy > CM > HD > PD. The outward shift of the leg on the axial plane was significantly greater, as follows: healthy < CM < PD < HD, whereas the outward shift of the upper limb followed the order of healthy > CM > HD > PD. The strongest correlation between the upper and lower limb movements was identified in the angle ranges of the hip and elbow joints on the sagittal plane. The lower and upper limb movements during circular walking were correlated. Patients with HD and PD exhibited reduced back-and-forth swings of the upper and lower limbs.

Seeking safety: Movement dynamics after post-contact immobility

Post-contact immobility (PCI) is a final attempt to avoid predation. Here, for the first time, we examine the pattern of movement and immobility when antlion larvae resume activity after PCI. To simulate contact with, and escape from, a predator we dropped the larvae onto three different substrates: Paper, Shallow sand (2.3mm-deep) and Deep sand (4.6mm-deep). The Paper lining a Petri dish represented a hard surface that antlion larvae could not penetrate to hide. The Shallow sand permitted the antlions to dig but not to submerge completely whereas the Deep sand allowed them both to dig and to submerge. We tracked their paths automatically and recorded alternating immobility and movement durations over 90min. On the impenetrable substrate, antlion larvae showed super-diffusive dispersal, their movement durations became longer, their immobility durations became shorter and their instantaneous speeds increased. This is consistent with the antlions needing to leave an area of hard substrate and quickly to find somewhere to hide. On Shallow sand, antlion larvae exhibited a modest increase in movement duration, a modest decrease in immobility duration and a concomitant diffusive dispersal. This is consistent with their use of a spiral search, presumably for a suitable depth of sand, to conceal themselves. On Deep sand, the movement and immobility durations of the antlion larvae did not change and their dispersal was sub-diffusive because they were able to bury themselves. On Paper, the distribution of immobility durations had a long tail, consistent with a log-normal distribution. On Shallow and Deep sand, most of the distribution was fitted better by a power law or a log-normal. Our results suggest that PCI in antlion larvae is a disruptive event and that post-PCI movement and immobility gradually return to the pattern typical of intermittent locomotion, depending on the scope for burying and hiding in the substrate.

Mouse tracking performance: A new approach to analyzing continuous mouse tracking data

Mouse tracking is an important source of data in cognitive science. Most contemporary mouse tracking studies use binary-choice tasks and analyze the curvature or velocity of an individual mouse movement during an experimental trial as participants select from one of the two options. However, there are many types of mouse tracking data available beyond what is produced in a binary-choice task, including naturalistic data from web users. In order to utilize these data, cognitive scientists need tools that are robust to the lack of trial-by-trial structure in most normal computer tasks. We use singular value decomposition (SVD) and detrended fluctuation analysis (DFA) to analyze whole time series of unstructured mouse movement data. We also introduce a new technique for describing two-dimensional mouse traces as complex-valued time series, which allows SVD and DFA to be applied in a straightforward way without losing important spatial information. We find that there is useful information at the level of whole time series, and we use this information to predict performance in an online task. We also discuss how the implications of these results can advance the use of mouse tracking research in cognitive science.

Pink noise promotes sooner state transitions during bimanual coordination

The seemingly straightforward task of tying one's shoes requires a sophisticated interplay of joints, muscles, and neural pathways, posing a formidable challenge for researchers studying the intricacies of coordination. A widely accepted framework for measuring coordinated behavior is the Haken-Kelso-Bunz (HKB) model. However, a significant limitation of this model is its lack of accounting for the diverse variability structures inherent in the coordinated systems it frequently models. Variability is a pervasive phenomenon across various biological and physical systems, and it changes in healthy adults, older adults, and pathological populations. Here, we show, both empirically and with simulations, that manipulating the variability in coordinated movements significantly impacts the ability to change coordination patterns-a fundamental feature of the HKB model. Our results demonstrate that synchronized bimanual coordination, mirroring a state of healthy variability, instigates earlier transitions of coordinated movements compared to other variability conditions. This suggests a heightened adaptability when movements possess a healthy variability. We anticipate our study to show the necessity of adapting the HKB model to encompass variability, particularly in predictive applications such as neuroimaging, cognition, skill development, biomechanics, and beyond.

Effects of metronome walking on long-term attractor divergence and correlation structure of gait: a validation study in older people

This study investigates the effects of metronome walking on gait dynamics in older adults, focusing on long-range correlation structures and long-range attractor divergence (assessed by maximum Lyapunov exponents). Sixty older adults participated in indoor walking tests with and without metronome cues. Gait parameters were recorded using two triaxial accelerometers attached to the lumbar region and to the foot. We analyzed logarithmic divergence of lumbar acceleration using Rosenstein's algorithm and scaling exponents for stride intervals from foot accelerometers using detrended fluctuation analysis (DFA). Results indicated a concomitant reduction in long-term divergence exponents and scaling exponents during metronome walking, while short-term divergence remained largely unchanged. Furthermore, long-term divergence exponents and scaling exponents were significantly correlated. Reliability analysis revealed moderate intrasession consistency for long-term divergence exponents, but poor reliability for scaling exponents. Our results suggest that long-term divergence exponents could effectively replace scaling exponents for unsupervised gait quality assessment in older adults. This approach may improve the assessment of attentional involvement in gait control and enhance fall risk assessment.

Females Present Reduced Minimum Toe Clearance During Walking As Compared to Males in Active Older Adults

BACKGROUND

Physical decline due to aging has been associated with the risk of falls. Minimum toe clearance (MTC) is a gait parameter that might play a role in the mechanism of tripping and falling. However, it is unclear if there are any sex-related effects regarding MTC as people age. The present study investigated if there are sex-related differences in MTC in older active adults.

METHODS

Twenty-three females and 23 males (F: 65.5 ± 4.8 years; M: 61.9 ± 5.2 years) walked on a treadmill at a preferred walking speed, while kinematic data were obtained at a sampling frequency of 100 Hz and up-sampled to 120 and 240 Hz. MTC was calculated from the kinematics data and evaluated concerning its magnitude (ie, MTC and MTC/leg length), the time between left/right MTC (ie, T-MTC), amount of variability (ie, coefficient of variation [CV] and coefficient of variation modified [CVm]), and temporal structure of variability, that is, the complexity of the time series (ie, MTC α, T-MTC α).

RESULTS

No sex effects were found for MTC/leg length, for the amount of variability (ie, CV and CVm), and for the complexity of the time series (MTC α, T-MTC α). However, females exhibited significantly lower MTC and T-MTC after adjusting for walking speed, mass, and age as covariates.

CONCLUSIONS

The reduced MTC in females suggests a potential sex-related disparity in the risk of tripping and falling among active older adults.

3D Kinematics Quantifies Gait Response to Levodopa earlier and to a more Comprehensive Extent than the MDS-Unified Parkinson's Disease Rating Scale in Patients with Motor Complications

BACKGROUND

Quantitative 3D movement analysis using inertial measurement units (IMUs) allows for a more detailed characterization of motor patterns than clinical assessment alone. It is essential to discriminate between gait features that are responsive or unresponsive to current therapies to better understand the underlying pathophysiological basis and identify potential therapeutic strategies.

OBJECTIVES

This study aims to characterize the responsiveness and temporal evolution of different gait subcomponents in Parkinson's disease (PD) patients in their OFF and various ON states following levodopa administration, utilizing both wearable sensors and the gold-standard MDS-UPDRS motor part III.

METHODS

Seventeen PD patients were assessed while wearing a full-body set of 15 IMUs in their OFF state and at 20-minute intervals following the administration of a supra-threshold levodopa dose. Gait was reconstructed using a biomechanical model of the human body to quantify how each feature was modulated. Comparisons with non-PD control subjects were conducted in parallel.

RESULTS

Significant motor changes were observed in both the upper and lower limbs according to the MDS-UPDRS III, 40 minutes after levodopa intake. IMU-assisted 3D kinematics detected significant motor alterations as early as 20 minutes after levodopa administration, particularly in upper limbs metrics. Although all "pace-domain" gait features showed significant improvement in the Best-ON state, most rhythmicity, asymmetry, and variability features did not.

CONCLUSION

IMUs are capable of detecting motor alterations earlier and in a more comprehensive manner than the MDS-UPDRS III. The upper limbs respond more rapidly to levodopa, possibly reflecting distinct thresholds to levodopa across striatal regions.

Gait variability, fractal dynamics, and statistical regularity of treadmill and overground walking recorded with a smartphone

BACKGROUND

The nonlinear variability present during steady-state gait may provide a signature of health and showcase one's walking adaptability. Although treadmills can capture vast amounts of walking data required for estimating variability within a small space, gait patterns may be misrepresented compared to an overground setting. Smartphones may provide a low-cost and user-friendly estimate of gait patterns among a variety of walking settings. However, no study has investigated differences in gait patterns derived from a smartphone between treadmill walking (TW) and overground walking (OW).

RESEARCH QUESTION

This study implemented a smartphone accelerometer to compare differences in temporal gait variability and gait dynamics between TW and OW.

METHODS

Sixteen healthy adults (8F; 24.7 ± 3.8 years) visited the laboratory on three separate days and completed three 8-minute OW and three TW trials, at their preferred speed, during each visit. The inter-stride interval was calculated as the time difference between right heel contact events located within the vertical accelerometery signals recorded from a smartphone while placed in participants front right pant pocket during walking trials. The inter-stride interval series was used to calculate stride time standard deviation (SD) and coefficient of variation (COV), statistical persistence (fractal scaling index), and statistical regularity (sample entropy). Two-way analysis of variance compared walking condition and laboratory visits for each measure.

RESULTS

Compared to TW, OW displayed significantly (p < 0.01) greater stride time SD (0.014 s, 0.020 s), COV (1.26 %, 1.82 %), fractal scaling index (0.70, 0.79) and sample entropy (1.43, 1.63). No differences were found between visits for all measures.

SIGNIFICANCE

Smartphone-based assessment of gait provides the ability to distinguish between OW and TW conditions, similar to previously established methodologies. Furthermore, smartphones may be a low-cost and user-friendly tool to estimate gait patterns outside the laboratory to improve ecological validity, with implications for free-living monitoring of gait among various populations.

Spatiotemporal variability after stroke reflects more than just slow walking velocity

BACKGROUND

Increased spatiotemporal gait variability is considered a clinical biomarker of ageing and pathology, and a predictor of future falls. Nevertheless, it is unclear whether the increased spatiotemporal variability observed in persons with stroke is directly related to the pathology or simply reflects their choice of walking velocity.

RESEARCH QUESTION

Does increased spatiotemporal gait variability directly relate to motor coordination deficits after stroke?

METHODS

Forty persons with stroke participated in this cross-sectional study. Participants performed the lower-extremity motor coordination test (LEMOCOT) on an electronic mat equipped with force sensors. Then, participants walked for 120 s on a computerized treadmill at their comfortable walking velocity. For the LEMOCOT we used the traditional score of in-target touch count and computed the absolute and variable error around the targets. For gait variability, we extracted the standard deviation of step time, step length, step velocity, and step width. Using linear modeling, we tested the correlations of gait variability with the outcome measures from the LEMOCOT, after controlling for walking velocity.

RESULTS

The variability in step time, step length and step width correlated with walking velocity, while the variability in step velocity did not. After controlling for walking velocity, we observed that the LEMOCOT score correlated with the variance in step time, and the variable error in the LEMOCOT correlated with the variance in step length, in step width, and in step velocity. No significant correlation with any of the velocity-controlled step parameters was found for the absolute error in the LEMOCOT.

SIGNIFICANCE

Decreased performance in the LEMOCOT was associated with increased spatiotemporal variability in persons with stroke, regardless of their walking velocity. Our results demonstrate the connection between lower-extremity coordination impairments and deficits in gait function.

Knee biomechanics variability before and after total knee arthroplasty: an equality of variance prospective study

This study evaluated gait variability in patients before and after total knee arthroplasty (TKA) using the equality of variance method to determine where variability differences occur in the movement cycle. Twenty-eight patients underwent TKA with cruciate-sacrificed implants. Patients underwent motion analysis which measured knee biomechanics as they walked overground at their preferred pace before and 12 months after TKA. Equality of variance results were compared with 14 healthy controls of similar age. Before surgery, patients had reduced knee extension moment variability throughout the early stance phase (4-21% gait cycle, p < 0.05) compared to controls. Knee power variability was lower preoperatively compared to controls for most of the stance phase (0-13% and 17-60% gait cycle, p < 0.05). Sagittal knee moment and power variability further decreased following TKA. Knee extension moment variability was lower postoperatively throughout stance phase compared to preoperatively (4-22% and 36-60% gait cycle, p < 0.05) and compared to controls (4-30% and 45-60% gait cycle, p < 0.05). Knee power variability remained lower following TKA throughout stance phase compared to preoperatively (10-24% and 36-58% gait cycle, p < 0.05) and controls (3-60% gait cycle, p < 0.05). TKA patients may be less stable, and this may be in part due to an unresolved adaptation developed while awaiting TKA surgery and the cruciate sacrificing design of the implants utilized in this study.

Gait and sEMG characteristics of lower limbs in children with unilateral spastic cerebral palsy during walking

BACKGROUND

Children with unilateral spastic cerebral palsy (USCP) have muscle hypertonia, balance, and coordination defects that affect gross motor skills, especially walking. Understanding the gait characteristics and lower limb muscle activation patterns of USCP children can provide an objective and quantitative basis for patient assessment and treatment plan formulation.

OBJECTIVE

This study compared the gait and lower limb muscle activation characteristics of children with USCP and with typical development (TD) during walking.

METHODS

We recorded gait and sEMG data of 20 children with USCP, and 20 with typical development. sEMG signals were acquired from the bilateral tibialis anterior (TA) and lateral gastrocnemius muscles (LG) during walking. The root mean square (RMS) value, integrated electromyographic (iEMG) value and co-contraction ratio (CR) were used to evaluate muscle activity. Student's t Test and non-parametric rank sum Test were used to compare the differences between the data groups (significance level of 0.05).

RESULTS

The stance time, step length, speed, single leg support time ratio, ground impact, pre-swing angle, and muscle strength of the affected side were significantly decreased compared to those of the unaffected side in children with USCP (P < 0.05), while the swing phase, muscle tonus of LG were significantly prolonged (P < 0.05). Compared with TD children, children with USCP exhibited reduced bilateral walking ability, particularly noticeable in their smaller pre-swing angle(P < 0.05), diminished muscle strength of the TA and LG, as well as LG spasms(P < 0.05).

SIGNIFICANCE

Children with USCP have decreased ambulatory gait stability. Step length, pull acceleration, pre-swing angle, and CR can be used as sensitive indicators for gait assessment. Strengthening the TA muscle and reducing ankle spasm may help improve gait and postural stability in children with USCP.

Fractal Analysis in Neurodegenerative Diseases

Neurodegenerative diseases are defined by progressive nervous system dysfunction and death of neurons. The abnormal conformation and assembly of proteins is suggested to be the most probable cause for many of these neurodegenerative disorders, leading to the accumulation of abnormally aggregated proteins, for example, amyloid β (Aβ) (Alzheimer's disease and vascular dementia), tau protein (Alzheimer's disease and frontotemporal lobar degeneration), α-synuclein (Parkinson's disease and Lewy body dementia), polyglutamine expansion diseases (Huntington disease), or prion proteins (Creutzfeldt-Jakob disease). An aberrant gain-of-function mechanism toward excessive intraparenchymal accumulation thus represents a common pathogenic denominator in all these proteinopathies. Moreover, depending upon the predominant brain area involvement, these different neurodegenerative diseases lead to either movement disorders or dementia syndromes, although the underlying mechanism(s) can sometimes be very similar, and on other occasions, clinically similar syndromes can have quite distinct pathologies. Non-Euclidean image analysis approaches such as fractal dimension (FD) analysis have been applied extensively in quantifying highly variable morphopathological patterns, as well as many other connected biological processes; however, their application to understand and link abnormal proteinaceous depositions to other clinical and pathological features composing these syndromes is yet to be clarified. Thus, this short review aims to present the most important applications of FD in investigating the clinical-pathological spectrum of neurodegenerative diseases.

Association of Gait Quality With Daily-Life Mobility: An Actigraphy and Global Positioning System Based Analysis in Older Adults

OBJECTIVE

Walking is a key component of daily-life mobility. We examined associations between laboratory-measured gait quality and daily-life mobility through Actigraphy and Global Positioning System (GPS). We also assessed the relationship between two modalities of daily-life mobility i.e., Actigraphy and GPS.

METHODS

In community-dwelling older adults (N = 121, age = 77±5 years, 70% female, 90% white), we obtained gait quality from a 4-m instrumented walkway (gait speed, walk-ratio, variability) and accelerometry during 6-Minute Walk (adaptability, similarity, smoothness, power, and regularity). Physical activity measures of step-count and intensity were captured from an Actigraph. Time out-of-home, vehicular time, activity-space, and circularity were quantified using GPS. Partial Spearman correlations between laboratory gait quality and daily-life mobility were calculated. Linear regression was used to model step-count as a function of gait quality. ANCOVA and Tukey analysis compared GPS measures across activity groups [high, medium, low] based on step-count. Age, BMI, and sex were used as covariates.

RESULTS

Greater gait speed, adaptability, smoothness, power, and lower regularity were associated with higher step-counts (0.20<|ρp| < 0.26, p < .05). Age(β = -0.37), BMI(β = -0.30), speed(β = 0.14), adaptability(β = 0.20), and power(β = 0.18), explained 41.2% variance in step-count. Gait characteristics were not related to GPS measures. Participants with high (>4800 steps) compared to low activity (steps<3100) spent more time out-of-home (23 vs 15%), more vehicular travel (66 vs 38 minutes), and larger activity-space (5.18 vs 1.88 km2), all p < .05.

CONCLUSIONS

Gait quality beyond speed contributes to physical activity. Physical activity and GPS-derived measures capture distinct aspects of daily-life mobility. Wearable-derived measures should be considered in gait and mobility-related interventions.

Vertical Ground Reaction Forces in Parkinson's Disease: A Speed-Matched Comparative Analysis with Healthy Subjects

This study aimed to investigate and compare the vertical Ground Reaction Forces (vGRFs) of patients with Parkinson's Disease (PwPD) and healthy subjects (HS) when the confounding effect of walking speed was absent. Therefore, eighteen PwPD and eighteen age- and linear walking speed-matched HS were recruited. Using plantar pressure insoles, participants walked along linear and curvilinear paths at self-selected speeds. Interestingly, PwPD exhibited similar walking speed to HS during curvilinear trajectories (p = 0.48) and similar vGRF during both linear and curvilinear paths. In both groups, vGRF at initial contact and terminal stance was higher during linear walking, while vGRF at mid-stance was higher in curvilinear trajectories. Similarly, the time to peak vGRF at each phase showed no significant group differences. The vGRF timing variability was different between the two groups, particularly at terminal stance (p < 0.001). In conclusion, PwPD and HS showed similar modifications in vGRF and a similar reduction in gait speed during curvilinear paths when matched for linear walking speed. This emphasized the importance of considering walking speed when assessing gait dynamics in PwPD. This study also suggests the possibility of the variability of specific temporal measures in differentiating the gait patterns of PwPD versus those of HS, even in the early stages of the disease.

Children with developmental coordination disorder have less variable motor unit firing rate characteristics across contractions compared to typically developing children

Introduction

Understanding the nuances of neuromuscular control is crucial in unravelling the complexities of developmental coordination disorder (DCD), which has been associated with differences in skeletal muscle activity, implying that children with DCD employ distinct strategies for muscle control. However, force generation and control are dependent on both recruitment of motor units and their firing rates and these fine details of motor function have yet to be studied in DCD. The purpose of this study was therefore to compare motor unit characteristics in a small muscle of the hand during low level, handgrip contractions in typically developing (TD) children and children with DCD.

Methods

Eighteen children (9 TD vs. 9 DCD) completed a series of manual handgrip contractions at 10 ± 5% of their maximum voluntary contraction. High density surface electromyography was used to record excitation of the first dorsal interosseus muscle. Recorded signals were subsequently decomposed into individual motor unit action potential trains. Motor unit characteristics (firing rate, inter-pulse interval, and action potential amplitude) were analysed for contractions that had a coefficient variation of <10%.

Results and Discussion

This study found few differences in average motor unit characteristics (number of motor units: TD 20.24 ± 9.73, DCD 27.32 ± 14.00; firing rate: TD 7.74 ± 2.16 p.p.s., DCD 7.86 ± 2.39 p.p.s.; inter-pulse interval: TD 199.72 ± 84.24 ms, DCD 207.12 ± 103 ms) when force steadiness was controlled for, despite the DCD group being significantly older (10.89 ± 0.78 years) than the TD group (9.44 ± 1.67 years). However, differences were found in the variability of motor unit firing statistics, with the children with DCD surprisingly showing less variability across contractions (standard deviation of coefficient of variation of inter-pulse interval: TD 0.38 ± 0.12, DCD 0.28 ± 0.11). This may suggest a more fixed strategy to stabilise force between contractions used by children with DCD. However, as variability of motor unit firing has not been considered in previous studies of children further work is required to better understand the role of variability in motor unit firing during manual grasping tasks, in all children.

NONAN GaitPrint: An IMU gait database of healthy young adults

An ongoing thrust of research focused on human gait pertains to identifying individuals based on gait patterns. However, no existing gait database supports modeling efforts to assess gait patterns unique to individuals. Hence, we introduce the Nonlinear Analysis Core (NONAN) GaitPrint database containing whole body kinematics and foot placement during self-paced overground walking on a 200-meter looping indoor track. Noraxon Ultium MotionTM inertial measurement unit (IMU) sensors sampled the motion of 35 healthy young adults (19-35 years old; 18 men and 17 women; mean ± 1 s.d. age: 24.6 ± 2.7 years; height: 1.73 ± 0.78 m; body mass: 72.44 ± 15.04 kg) over 18 4-min trials across two days. Continuous variables include acceleration, velocity, position, and the acceleration, velocity, position, orientation, and rotational velocity of each corresponding body segment, and the angle of each respective joint. The discrete variables include an exhaustive set of gait parameters derived from the spatiotemporal dynamics of foot placement. We technically validate our data using continuous relative phase, Lyapunov exponent, and Hurst exponent-nonlinear metrics quantifying different aspects of healthy human gait.

Association of Prospective Falls in Older People With Ubiquitous Step-Based Fall Risk Parameters Calculated From Ambulatory Inertial Signals: Secondary Data Analysis

Background

In recent years, researchers have been advocating for the integration of ambulatory gait monitoring as a complementary approach to traditional fall risk assessments. However, current research relies on dedicated inertial sensors that are fixed on a specific body part. This limitation impacts the acceptance and adoption of such devices.

Objective

Our study objective is twofold: (1) to propose a set of step-based fall risk parameters that can be obtained independently of the sensor placement by using a ubiquitous step detection method and (2) to evaluate their association with prospective falls.

Methods

A reanalysis was conducted on the 1-week ambulatory inertial data from the StandingTall study, which was originally described by Delbaere et al. The data were from 301 community-dwelling older people and contained fall occurrences over a 12-month follow-up period. Using the ubiquitous and robust step detection method Smartstep, which is agnostic to sensor placement, a range of step-based fall risk parameters can be calculated based on walking bouts of 200 steps. These parameters are known to describe different dimensions of gait (ie, variability, complexity, intensity, and quantity). First, the correlation between parameters was studied. Then, the number of parameters was reduced through stepwise backward elimination. Finally, the association of parameters with prospective falls was assessed through a negative binomial regression model using the area under the curve metric.

Results

The built model had an area under the curve of 0.69, which is comparable to models exclusively built on fixed sensor placement. A higher fall risk was noted with higher gait variability (coefficient of variance of stride time), intensity (cadence), and quantity (number of steps) and lower gait complexity (sample entropy and fractal exponent).

Conclusions

These findings highlight the potential of our method for comprehensive and accurate fall risk assessments, independent of sensor placement. This approach has promising implications for ambulatory gait monitoring and fall risk monitoring using consumer-grade devices.

Fluctuations in Upper and Lower Body Movement during Walking in Normal Pressure Hydrocephalus and Parkinson's Disease Assessed by Motion Capture with a Smartphone Application, TDPT-GT

We aimed to capture the fluctuations in the dynamics of body positions and find the characteristics of them in patients with idiopathic normal pressure hydrocephalus (iNPH) and Parkinson's disease (PD). With the motion-capture application (TDPT-GT) generating 30 Hz coordinates at 27 points on the body, walking in a circle 1 m in diameter was recorded for 23 of iNPH, 23 of PD, and 92 controls. For 128 frames of calculated distances from the navel to the other points, after the Fourier transforms, the slopes (the representatives of fractality) were obtained from the graph plotting the power spectral density against the frequency in log-log coordinates. Differences in the average slopes were tested by one-way ANOVA and multiple comparisons between every two groups. A decrease in the absolute slope value indicates a departure from the 1/f noise characteristic observed in healthy variations. Significant differences in the patient groups and controls were found in all body positions, where patients always showed smaller absolute values. Our system could measure the whole body's movement and temporal variations during walking. The impaired fluctuations of body movement in the upper and lower body may contribute to gait and balance disorders in patients.

Stride-to-Stride Fluctuations of Human Gait Are Affected By Chronobiology: An Exploratory Study

Physiological processes present daily oscillations of ≈24 h, called circadian rhythms. Motor performance, for example, reaches its peak in the afternoon, although this can be affected by chronotype. Certain motor activities, for example, walking, can also be affected by circadian rhythms. Healthy walking exhibits stride-to-stride fluctuations with a fractal-like structure that enables adaptability. While pathology and aging are shown to lead to random-like fluctuations; and, therefore, decreased adaptability; the influence of circadian rhythms remains unknown. This study investigates how these fluctuations present in healthy gait are affected by the time of day and chronotype. Eighteen young adults walk for 10 min every 2 h, from 8 a.m. to 6 p.m. Footswitches are used to determine heel-strike and calculate stride time. Then, detrended fluctuation analysis is used to calculate fractal scaling. A mixed-model Analysis of Variance is used and followed by a backward stepwise elimination process. Tukey's tests are used for pairwise comparisons. The statistical model shows the effect of time during the day (12 p.m. exhibits a higher fractal scaling compared to 8 a.m.); and chronotype (evening-types exhibit higher fractal scaling compared to morning-types). This study reveals the influence of chronobiology on stride-to-stride fluctuations. These findings open new perspectives to integrate circadian medicine in biomechanics.

Children with developmental coordination disorder are less able to fine-tune muscle activity in anticipation of postural perturbations than typically developing counterparts

The majority of children with developmental coordination disorder (DCD) struggle with static and dynamic balance, yet there is limited understanding of the underlying neuromechanical mechanisms that underpin poor balance control in these children. Eighteen children with DCD and seven typically developing (TD) children aged 7-10 years stood with eyes open on a moveable platform progressively translated antero-posteriorly through three frequencies (0.1, 0.25 and 0.5 Hz). Myoelectric activity of eight leg muscles, whole-body 3D kinematics and centre of pressure were recorded. At each frequency, postural data were divided into transition-state and steady-state cycles. Data were analyzed using a linear mixed model with follow-up Tukey's pairwise comparisons. At the slowest frequency, children with DCD behaved like age-matched TD controls. At the fastest frequency, children with DCD took a greater number of steps, had a greater centre of mass variability, had a greater centre of pressure area, and tended to activate their muscles earlier and for longer than TD children. Children with DCD did not alter their postural response following prolonged exposure to platform movement, however they made more, non-structured postural adjustments in the medio-lateral direction as task difficulty increased. At the faster oscillation frequencies, children with DCD adopted a different muscle recruitment strategy to TD children. Activating their muscles earlier and for longer may suggest that children with DCD attempt to predict and react to postural disturbances, however the resulting anticipatory muscle excitation patterns do not seem as finely tuned to the perturbation as those demonstrated by TD children. Future work should examine the impact of balance training interventions on the muscle recruitment strategies of children with DCD, to ensure optimal interventions can be prescribed.

Multifractality in stride-to-stride variations reveals that walking involves more movement tuning and adjusting than running

Introduction: The seemingly periodic human gait exhibits stride-to-stride variations as it adapts to the changing task constraints. The optimal movement variability hypothesis (OMVH) states that healthy stride-to-stride variations exhibit "fractality"-a specific temporal structure in consecutive strides that are ordered, stable but also variable, and adaptable. Previous research has primarily focused on a single fractality measure, "monofractality." However, this measure can vary across time; strideto-stride variations can show "multifractality." Greater multifractality in stride-tostride variations would highlight the ability to tune and adjust movements more. Methods: We investigated monofractality and multifractality in a cohort of eight healthy adults during self-paced walking and running trials, both on a treadmill and overground. Footfall data were collected through force-sensitive sensors positioned on their heels and feet. We examined the effects of self-paced walking vs. running and treadmill vs. overground locomotion on the measure of monofractality, α-DFA, in addition to the multifractal spectrum width, W, and the asymmetry in the multifractal spectrum, WAsym, of stride interval time series. Results: While the α-DFA was larger than 0.50 for almost all conditions, α-DFA was higher in running and locomoting overground than walking and locomoting on a treadmill. Similarly, W was greater while locomoting overground than on a treadmill, but an opposite trend indicated that W was greater in walking than running. Larger WAsym values in the negative direction suggest that walking exhibits more variation in the persistence of shorter stride intervals than running. However, the ability to tune and adjust movements does not differ between treadmill and overground, although both exhibit more variation in the persistence of shorter stride intervals. Discussion: Hence, greater heterogeneity in shorter than longer stride intervals contributed to greater multifractality in walking compared to running, indicated by larger negative WAsym values. Our results highlight the need to incorporate multifractal methods to test the predictions of the OMVH.

Emotional states affect steady state walking performance

Gait is a large component and indicator of health. Many factors affect gait including age, disease, and even mood disorders. Few studies have looked at the influence of emotional states on gait. This study aimed to investigate the influence of emotional states on walking performance to understand whether an emotional state may be an important factor to consider when evaluating gait. Thirty-six young adults were recruited (23F, 13M) and performed a neutral baseline condition of walking which included six passes of walking across an 8m walkway (a total of 48m of walking). Participants then completed 6 pseudo-randomized emotional state induction conditions while immersive 360-degree videos were used to induce the following emotional conditions: happiness, excitement, sadness, fear, and anger. Participants viewed the emotion elicitation videos using a virtual reality head-mounted display (HMD), then rated their emotional state using self-assessment manikins and walked (without the HMD) over a pressure sensor walkway. One-way repeated measures ANOVA and pairwise comparisons were used to examine differences in gait parameters across the emotional conditions. Participants walked with significantly reduced step length and speed during the sadness condition compared to the other emotional conditions and the neutral condition. Furthermore, participants adjusted the timing of their walking during the sadness condition and walked with significantly increased step, stance, and swing times compared to other emotional conditions, but not the neutral condition. Step time was significantly reduced during the conditions of excitement and fear compared to the neutral condition. Emotions may impact variety of gait parameters involving pace and rhythm, however have little influence on gait variability and postural control. These results indicate that perhaps the emotions of sadness and excitement should be taken into account as potential confounds for future gait analysis.

Visual feedback influences the consistency of the locomotor pattern in Asian elephants (Elephas maximus)

Elephants are atypical of most quadrupeds in that they maintain the same lateral sequence footfall pattern across all locomotor speeds. It has been speculated that the preservation of the footfall patterns is necessary to maintain a statically stable support polygon. This should be a particularly important constraint in large, relatively slow animals. This suggests that elephants must rely on available sensory feedback mechanisms to actively control their massive pillar-like limbs for proper foot placement and sequencing. How the nervous system of elephants integrates the available sensory information for a stable gait is unknown. Here we explored the role that visual feedback plays in the control of the locomotor pattern in Asian elephants. Four Asian elephants (Elephas maximus) walked with and without a blindfold as we measured their stride time intervals. Coefficient of variation was used to assess changes in the overall variability of the stride time intervals, while approximate entropy was used to measure the stride-to-stride consistency of the time intervals. We show that visual feedback plays a role in the stride-to-stride consistency of the locomotor pattern in Asian elephants. These results suggest that elephants use visual feedback to correct and maintain proper sequencing of the limbs during locomotion.

Temporal organization of stride-to-stride variations contradicts predictive models for sensorimotor control of footfalls during walking

Walking exhibits stride-to-stride variations. Given ongoing perturbations, these variations critically support continuous adaptations between the goal-directed organism and its surroundings. Here, we report that stride-to-stride variations during self-paced overground walking show cascade-like intermittency-stride intervals become uneven because stride intervals of different sizes interact and do not simply balance each other. Moreover, even when synchronizing footfalls with visual cues with variable timing of presentation, asynchrony in the timings of the cue and footfall shows cascade-like intermittency. This evidence conflicts with theories about the sensorimotor control of walking, according to which internal predictive models correct asynchrony in the timings of the cue and footfall from one stride to the next on crossing thresholds leading to the risk of falling. Hence, models of the sensorimotor control of walking must account for stride-to-stride variations beyond the constraints of threshold-dependent predictive internal models.

Age-related changes in mobility assessments correlate with repetitive goal-directed arm-movement performance

BACKGROUND

There is ample evidence that mobility abilities between healthy young and elderly people differ. However, we do not know whether these differences are based on different lower leg motor capacity or instead reveal a general motor condition that could be detected by monitoring upper-limb motor behavior. We therefore captured body movements during a standard mobility task, namely the Timed Up and Go test (TUG) with subjects following different instructions while performing a rapid, repetitive goal-directed arm-movement test (arm-movement test). We hypothesized that we would be able to predict gait-related parameters from arm motor behavior, even regardless of age.

METHODS

Sixty healthy individuals were assigned to three groups (young: mean 26 ± 3 years, middle-aged 48 ± 9, old 68 ± 7). They performed the arm-movement and TUG test under three conditions: preferred (at preferred movement speed), dual-task (while counting backwards), and fast (at fast movement speed). We recorded the number of contacts within 20 s and the TUG duration. We also extracted TUG walking sequences to analyze spatiotemporal gait parameters and evaluated the correlation between arm-movement and TUG results.

RESULTS

The TUG condition at preferred speed revealed differences in gait speed and step length only between young and old, while dual-task and fast execution increased performance differences significantly among all 3 groups. Our old group's gait speed decreased the most doing the dual-task, while the young group's gait speed increased the most during the fast condition. As in our TUG results, arm-movements were significant faster in young than in middle-aged and old. We observed significant correlations between arm movements and the fast TUG condition, and that the number of contacts closely predicts TUG timefast and gait speedfast. This prediction is more accurate when including age.

CONCLUSION

We found that the age-related decline in mobility performance that TUG reveals strongly depends on the test instruction: the dual-task and fast condition clearly strengthened group contrasts. Interestingly, a fast TUG performance was predictable by the performance in a fast repetitive goal-directed arm-movements test, even beyond the age effect. We assume that arm movements and the fast TUG condition reflect similarly reduced motor function.

TRIAL REGISTRATION

German Clinical Trials Register (DRKS) number: DRKS00016999, prospectively registered on March, 26, 2019.

The impact of neck pain on gait health: a systematic review and meta-analysis

BACKGROUND

Evidence exists demonstrating the negative impacts of chronic musculoskeletal pain on key measures of gait. Despite neck pain being the second most common musculoskeletal pain condition, there is a paucity of evidence exploring the impacts of neck pain specifically on these outcomes. The aims of this work were to systematically review the current evidence of the associations between chronic neck pain and measures of gait health and to conduct meta-analysis for quantitative assessment of the effect sizes under different walking conditions.

METHODS

Systematic review was conducted following PRISMA guidelines. Databases searched included MEDLINE, Embase, Web of Science, CINAHL, and PEDro. Eligible study designs included observational studies consisting of an exposure group with chronic neck pain and control group without chronic neck pain and primary outcomes relating to gait health. For outcomes amenable to meta-analysis, a random-effects model was used to derive summary estimates of Hedge's g depicted graphically with forest plots. Other gait outcomes were narratively summarized. Risk of bias was also assessed.

RESULTS

The original search yielded 1918 articles; 12 met final eligibility criteria including 10 cross-sectional studies. Outcomes were grouped first by the five domains of gait: pace, rhythm, asymmetry, variability, and postural control; and second by the tested walking conditions. Meta-analyses for gait speed revealed large effect-sizes indicating that individuals with chronic neck pain had slower measures of gait and lower measures of cadence. Gait outcomes that were narratively summarized supported these findings.

CONCLUSION

The quantitative and qualitative findings of this systematic review and meta-analysis suggest a negative impact of CNNP on measures of gait health, particularly gait speed, under various walking conditions. However, broad interpretation of these results should be cautious. Testing gait under dual task conditions may be particularly sensitive to the impact of CNNP, and future work is needed to better understand how pain disrupts this important functionality of the locomotor system. Additionally, consideration should be made to assess measures of variability and investigate these relationships in the older adult population.

Stride-to-stride variability and fluctuations at intensities around lactate threshold in distance runners

Stride-to-stride variability and fluctuations in running have been widely investigated in relation to fatigue, injury, and other factors. However, no studies have examined the relationship of stride-to-stride variability and fluctuations with lactate threshold (LT), a well-known performance indicator for distance runners that represents the threshold at which fast-twitch muscle fibers are activated and the glycolytic system is hyperactivated. In this study, we examined a relationship between LT and stride-to-stride variability and fluctuations in trained middle- and long-distance runners (n = 33). All runners were asked to perform multistage graded exercise tests while wearing accelerometers on the upper surface of their shoes. The LT was determined by measuring blood lactate concentrations after each stage. Three gait parameters for each step were calculated based on the acceleration data: stride time (ST), ground contact time (CT), and peak acceleration (PA). The coefficient of variation (CV) and the long-range correlations (α) for each parameter were also calculated. The effects of the runner's group and the relative intensity for CV and α on gait parameters were evaluated using a two-way repeated measures analysis of variance. Although no significant effect was observed in the CV and α of ST, significant intensity main effects were observed for the CV and α of CT and PA. The lack of significant changes in ST might be the result of runners' adequate control of ST to minimize energy cost. All the parameters showing significant changes with increasing intensity decreased dramatically when they were close to LT. This might have been caused by an increase in physiological load near LT and be interpreted as a variation in motor control because of alternations in the mobilized muscle fibers and physiological changes around the LT. The α should be useful for non-invasive LT detection.

Sensor-Based Assessment of Variability in Daily Physical Activity and Frailty

INTRODUCTION

Frailty is a common geriatric syndrome associated with decline in physiological reserve. While several digital biomarkers of daily physical activity (DPA) have been used in frailty assessment, the association between DPA variability and frailty is still not clear. The goal of this study was to determine the association between frailty and DPA variability.

METHODS

This is an observational cross-sectional study conducted between September 2012 and November 2013. Older adults (≥65 years), without any severe mobility disorder, and the ability to walk 10 m (with or without an assistive device) were eligible for the study. DPA including sitting, standing, walking, lying, and postural transition were recorded for 48 h continuously. DPA variability was analyzed from two perspectives: (i) DPA duration variability in terms of coefficient of variation (CoV) of sitting, standing, walking, and lying down durations; and (ii) DPA performance variability in terms of CoV of sit-to-stand (SiSt) and stand-to-sit (StSi) durations and stride time (i.e., slope of power spectral density - PSD).

RESULTS

Data was analyzed from 126 participants (44 non-frail, 60 pre-frail, and 22 frail). For DPA duration variability, CoV of lying and walking duration was significantly larger among non-frail compared to pre-frail and frail groups (p < 0.03, d = 0.89 ± 0.40). For DPA performance variability, StSi CoV and PSD slope were significantly smaller for non-frail compared to pre-frail and frail groups (p < 0.05, d = 0.78 ± 0.19).

CONCLUSION

Lower DPA duration variability in pre-frail and frail groups may be attributed to the set daily routines frail older adults tend to follow, compared to variable physical activity routines of non-frail older adults. Higher DPA performance variability in the frail group may be attributed to reduced physiological capabilities toward walking for longer durations and the reduced muscle strength in the lower extremities, leading to incosistency in performing postural transitions.