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

Correlates of Person-Specific Rates of Change in Sensor-Derived Physical Activity Metrics of Daily Living in the Rush Memory and Aging Project

This study characterized person-specific rates of change of total daily physical activity (TDPA) and identified correlates of this change. TDPA metrics were extracted from multiday wrist-sensor recordings from 1083 older adults (average age 81 years; 76% female). Thirty-two covariates were collected at baseline. A series of linear mixed-effect models were used to identify covariates independently associated with the level and annual rate of change of TDPA. Though, person-specific rates of change varied during a mean follow-up of 5 years, 1079 of 1083 showed declining TDPA. The average decline was 16%/year, with a 4% increased rate of decline for every 10 years of age older at baseline. Following variable selection using multivariate modeling with forward and then backward elimination, age, sex, education, and 3 of 27 non-demographic covariates including motor abilities, a fractal metric, and IADL disability remained significantly associated with declining TDPA accounting for 21% of its variance (9% non-demographic and 12% demographics covariates). These results show that declining TDPA occurs in many very old adults. Few covariates remained correlated with this decline and the majority of its variance remained unexplained. Further work is needed to elucidate the biology underlying TDPA and to identify other factors that account for its decline.

The fractal brain: scale-invariance in structure and dynamics

The past 40 years have witnessed extensive research on fractal structure and scale-free dynamics in the brain. Although considerable progress has been made, a comprehensive picture has yet to emerge, and needs further linking to a mechanistic account of brain function. Here, we review these concepts, connecting observations across different levels of organization, from both a structural and functional perspective. We argue that, paradoxically, the level of cortical circuits is the least understood from a structural point of view and perhaps the best studied from a dynamical one. We further link observations about scale-freeness and fractality with evidence that the environment provides constraints that may explain the usefulness of fractal structure and scale-free dynamics in the brain. Moreover, we discuss evidence that behavior exhibits scale-free properties, likely emerging from similarly organized brain dynamics, enabling an organism to thrive in an environment that shares the same organizational principles. Finally, we review the sparse evidence for and try to speculate on the functional consequences of fractality and scale-freeness for brain computation. These properties may endow the brain with computational capabilities that transcend current models of neural computation and could hold the key to unraveling how the brain constructs percepts and generates behavior.

Running gait produces long range correlations: A systematic review

BACKGROUND

Walking and running are common forms of locomotion, both of which exhibit variability over many gait cycles. Many studies have investigated the patterns generated from that ebb and flow, and a large proportion suggests human gait exhibits Long Range Correlations (LRCs). LRCs refer to the observation that healthy gait characteristic, like stride times, are positively correlated to themselves over time. Literature on LRCs in walking gait is well known but less attention has been given to LRCs in running gait.

RESEARCH QUESTION

What is the state of the art concerning LRCs in running gait?

METHODS

We conducted a systematic review to identify the typical LRC patterns present in human running gait, in addition to disease, injury, and running surface effects on LRCs. Inclusion criteria were human subjects, running related experiments, computed LRCs, and experimental design. Exclusion criteria were studies on animals, non-humans, walking only, non-running, non-LRC analysis, and non-experiments.

RESULTS

The initial search returned 536 articles. After review and deliberation, our review included 26 articles. Almost every article produced strong evidence for LRCs apparent in running gait and in all running surfaces. Additionally, LRCs tended to decrease due to fatigue, past injury, increased load carriage and seem to be lowest at preferred running speed on a treadmill. No studies investigated disease effects on LRCs in running gait.

SIGNIFICANCE

LRCs seem to increase with deviations away from preferred running speed. Previously injured runners produced decreased LRCs compared to non-injured runners. LRCs also tended to decrease due to an increase in fatigue rate, which has been associated with increased injury rate. Lastly, there is a need for research on the typical LRCs in an overground environment, for which the typical LRCs found in a treadmill environment may or may not transfer.

Recruit-aged adults may preferentially weight task goals over deleterious cost functions during short duration loaded and imposed gait tasks

Optimal motor control that is stable and adaptable to perturbation is reflected in the temporal arrangement and regulation of gait variability. Load carriage and forced-marching are common military relevant perturbations to gait that have been implicated in the high incidence of musculoskeletal injuries in military populations. We investigated the interactive effects of load magnitude and locomotion pattern on motor variability, stride regulation and spatiotemporal complexity during gait in recruit-aged adults. We further investigated the influences of sex and task duration. Healthy adults executed trials of running and forced-marching with and without loads at 10% above their gait transition velocity. Spatiotemporal parameters were analyzed using a goal equivalent manifold approach. With load and forced-marching, individuals used a greater array of motor solutions to execute the task goal (maintain velocity). Stride-to-stride regulation became stricter as the task progressed. Participants exhibited optimal spatiotemporal complexity with significant but not meaningful differences between sexes. With the introduction of load carriage and forced-marching, individuals relied on a strategy that maximizes and regulates motor solutions that achieve the task goal of velocity specifically but compete with other task functions. The appended cost penalties may have deleterious effects during prolonged execution, potentially increasing the risk of musculoskeletal injuries.

Age and walking conditions differently affect domains of gait

INTRODUCTION

Analysing gait in controlled conditions that resemble daily life walking could overcome the limitations associated with gait analysis in uncontrolled real-world conditions. Such analyses could potentially aid the identification of a walking condition that magnifies age-differences in gait. Therefore, the aim of the current study was to determine the effects of age and walking conditions on gait performance.

METHODS

Trunk accelerations of young (n = 27, age: 21.6) and older adults (n = 26, age: 68.9) were recorded for 3 min in four conditions: walking up and down a university hallway on a track of 10 m; walking on a specified path, including turns, in a university hallway; walking outside on a specified path on a pavement including turns; and walking on a treadmill. Factor analysis was used to reduce 27 computed gait measures to five independent gait domains. A multivariate analysis of variance was used to examine the effects of age and walking condition on these gait domains.

RESULTS

Factor analysis yielded 5 gait domains: variability, pace, stability, time & frequency, complexity, explaining 64% of the variance in 27 gait outcomes. Walking conditions affected all gait domains (p < 0.01) but age only affected the time & frequency domain (p < 0.05). Age and walking conditions differently affected the domains variability, stability, time & frequency. The largest age-differences occurred mainly during straight walking in a hallway (variability: 31% higher in older adults), or during treadmill walking (stability: 224% higher, time&frequency: 120% lower in older adults).

CONCLUSION

Walking conditions affect all domains of gait independent of age. Treadmill walking and walking on a straight path in a hallway, were the most constrained walking conditions in terms of limited possibilities to adjust step characteristics. The age by condition interaction suggests that for the gait domains variability, stability, and time & frequency, the most constrained walking conditions seem to magnify the age-differences in gait.

Spatio-Temporal Gait Parameters of Hospitalized Older Patients: Comparison of Fallers and Non-Fallers

Gait disorders are predisposing factors for falls. They are accessible to rehabilitation and can be analyzed using tools that collect spatio-temporal parameters of walking, such as the GAITRite^® mat. The objective of this retrospective study was to find differences between the spatio-temporal parameters in patients who had fallen compared to patients who did not fall in a population of older patients hospitalized in acute geriatrics department. Patients over 75 years were included. For each patient, spatio-temporal parameters were collected using the GAITRite^® mat. The patients were divided into two groups according to whether they had a history of fall. The spatio-temporal parameters were compared between the two groups and in relation to the general population. Sixty-seven patients, with an average age of 85.9 ± 6 years, were included. The patients had comorbidities, cognitive impairment and were polymedicated. The mean walking speed was 51.4 cm/s in non-fallers group and 47.3 cm/s in fallers group (p = 0.539), indicating pathological walking in comparison with the general population of the same age (average 100 cm/s). No association was found between the spatio-temporal parameters and fall, probably linked to many confounding factors such as the pathogenicity of walking of our patients and their comorbidities.

The Application of non-linear methods to quantify changes to movement dynamics during running: A scoping review

The aim of this scoping review was to evaluate research approaches that quantify changes to non-linear movement dynamics during running in response to fatigue, different speeds, and fitness levels. PubMed and Scopus were used to identify appropriate research articles. After the selection of eligible studies, study details and participant characteristics were extracted and tabulated to identify methodologies and findings. Twenty-seven articles were included in the final analysis. To evaluate non-linearities in the time series, a range of approaches were identified including motion capture, accelerometery, and foot switches. Common methods of analysis included measures of fractal scaling, entropy, and local dynamic stability. Conflicting findings were evident when studies examined non-linear features in fatigued states when compared to non-fatigued. More pronounced alterations to movement dynamics are evident when running speed is changed markedly. Greater fitness levels resulted in more stable and predictable running patterns. The mechanisms by which these changes are underpinned require further examination. These could include the physiological demand of running, biomechanical constraints of the runner, and the attentional demands of the task. Moreover, the practical implications are yet to be elucidated. This review has identified gaps in the literature which should be addressed for further understanding of the field.

CCR5-Δ32 polymorphism-a possible protective factor from gait impairment amongst post-stroke patients

BACKGROUND AND PURPOSE

Stroke and small vessel disease cause gait disturbances and falls. The naturally occurring loss-of-function mutation in the C-C chemokine receptor 5 gene (CCR5-Δ32) has recently been reported as a protective factor in post-stroke motor and cognitive recovery. We sought to examine whether it also influences gait and balance measures up to 2 years after stroke.

METHOD

Participants were 575 survivors of first-ever, mild-moderate ischaemic stroke or transient ischaemic attack from the TABASCO prospective study, who underwent a 3 T magnetic resonance imaging at baseline and were examined by a multi-professional team 6, 12 and 24 months after the event, using neurological, neuropsychological and mobility examinations. Gait rhythm and the timing of the gait cycle were measured by force-sensitive insoles. CCR5-Δ32 status and gait measures were available for 335 patients.

RESULTS

CCR5-Δ32 carriers (16.4%) had higher gait speed and decreased (better) stride and swing time variability 6 and 12 months after the index event compared to non-carriers (p < 0.01 for all). The association remained significant after adjustment for age, gender, education, ethnicity and stroke severity.

CONCLUSIONS

Significant associations were found between gait measurements and CCR5-Δ32 loss-of-function mutation amongst stroke survivors. This is the first study showing that genetic predisposition may predict long-term gait function after ischaemic stroke.

Model of Gait Control in Parkinson's Disease and Prediction of Robotic Assistance

Gait variability of healthy adults exhibits Long-Range Autocorrelations (LRA), meaning that the stride interval at any time statistically depends on previous gait cycles; and this dependency spans over several hundreds of strides. Previous works have shown that this property is altered in patients with Parkinson's disease, such that their gait pattern corresponds to a more random process. Here, we adapted a model of gait control to interpret the reduction in LRA that characterized patients in a computational framework. Gait regulation was modeled as a Linear-Quadratic-Gaussian control problem where the objective was to maintain a fixed velocity through the coordinated regulation of stride duration and length. This objective offers a degree of redundancy in the way the controller can maintain a given velocity, resulting in the emergence of LRA. In this framework, the model suggested that patients exploited less the task redundancy, likely to compensate for an increased stride-to-stride variability. Furthermore, we used this model to predict the potential benefit of an active orthosis on the gait pattern of patients. The orthosis was embedded in the model as a low-pass filter on the series of stride parameters. We show in simulations that, with a suitable level of assistance, the orthosis could help patients recovering a gait pattern with LRA comparable to that of healthy controls. Assuming that the presence of LRA in a stride series is a marker of healthy gait control, our study provides a rationale for developing gait assistance technology to reduce the fall risk associated with Parkinson's disease.

Unilaterally Applied Resistance to Swing Leg Shows a Different Adaptation Pattern Compared to Split-Belt Treadmill in Patients with Stroke

Persons with chronic stroke (PwCS) have a decreased ability to ambulate and walk independently. We aimed to investigate the differences between the motor adaptation process for two different perturbation methods: split-belt treadmill walking and unilaterally applied resistance to the swing leg during walking. Twenty-two PwCS undergo split-belt treadmill walking and unilaterally applied resistance to the swing leg during walking, each one week apart. The test included three phases: the baseline period, the early-adaptation period and the late-adaptation period, as well as the early-de-adaptation period and the late-de-adaptation period. The average step length, swing duration, double-limb support duration, and coefficient of variance (CV) of these parameters were measured. During the split-belt treadmill walking, PwCS showed an adaptation of double-limb support duration symmetry (p = 0.004), specifically a trend between baseline versus early-adaptation (p = 0.07) and an after-effect (late-adaptation compare to early-de-adaptation, p = 0.09). In unilaterally applied resistance to the swing leg during walking, PwCS showed lower swing phase duration CV, in the adaptation period (baseline compare to adaptation, p = 0.006), and a trend toward increased variability of gait in the de-adaptation period compare to the adaptation periods (p = 0.099). The rate of adaptation and de-adaptation were alike between the two perturbation methods. Our findings show that the learning process happening in the central nervous system of PwCS may be dependent on the nature of the perturbation (mechanical resistance vs. split-belt) and that PwCS are able to adapt to two types of errors.

With life there is motion. Activity biomarkers signal important health and performance outcomes

Measures of human motion provide a rich source of health and physiological status information. This paper provides examples of motion-based biomarkers in the form of patterns of movement, quantified physical activity, and characteristic gaits that can now be assessed with practical measurement technologies and rapidly evolving physiological models and algorithms, with research advances fed by the increasing access to motion data and associated contextual information. Quantification of physical activity has progressed from step counts to good estimates of energy expenditure, useful to weight management and to activity-based health outcomes. Activity types and intensity durations are important to health outcomes and can be accurately classified even from carried smart phone data. Specific gaits may predict injury risk, including some re-trainable injurious running or modifiable load carriage gaits. Mood status is reflected in specific types of human movement, with slumped posture and shuffling gait signaling depression. Increased variability in body sway combined with contextual information may signify heat strain, physical fatigue associated with heavy load carriage, or specific neuropsychological conditions. Movement disorders might be identified earlier and chronic diseases such as Parkinson's can be better medically managed with automatically quantified information from wearable systems. Increased path tortuosity suggests head injury and dementia. Rapidly emerging wear-and-forget systems involving global positioning system and inertial navigation, triaxial accelerometry, smart shoes, and functional fiber-based clothing are making it easier to make important health and performance outcome associations, and further refine predictive models and algorithms that will improve quality of life, protect health, and enhance performance.

Better than DFA? A Bayesian Method for Estimating the Hurst Exponent in Behavioral Sciences

Detrended Fluctuation Analysis (DFA) is the most popular fractal analytical technique used to evaluate the strength of long-range correlations in empirical time series in terms of the Hurst exponent, H. Specifically, DFA quantifies the linear regression slope in log-log coordinates representing the relationship between the time series' variability and the number of timescales over which this variability is computed. We compared the performance of two methods of fractal analysis-the current gold standard, DFA, and a Bayesian method that is not currently well-known in behavioral sciences: the Hurst-Kolmogorov (HK) method-in estimating the Hurst exponent of synthetic and empirical time series. Simulations demonstrate that the HK method consistently outperforms DFA in three important ways. The HK method: (i) accurately assesses long-range correlations when the measurement time series is short, (ii) shows minimal dispersion about the central tendency, and (iii) yields a point estimate that does not depend on the length of the measurement time series or its underlying Hurst exponent. Comparing the two methods using empirical time series from multiple settings further supports these findings. We conclude that applying DFA to synthetic time series and empirical time series during brief trials is unreliable and encourage the systematic application of the HK method to assess the Hurst exponent of empirical time series in behavioral sciences.

Characterization of Anesthesia in Rats from EEG in Terms of Long-Range Correlations

Long-range correlations are often used as diagnostic markers in physiological research. Due to the limitations of conventional techniques, their characterizations are typically carried out with alternative approaches, such as the detrended fluctuation analysis (DFA). In our previous works, we found EEG-related markers of the blood-brain barrier (BBB), which limits the penetration of major drugs into the brain. However, anesthetics can penetrate the BBB, affecting its function in a dose-related manner. Here, we study two types of anesthesia widely used in experiments on animals, including zoletil/xylazine and isoflurane in optimal doses not associated with changes in the BBB. Based on DFA, we reveal informative characteristics of the electrical activity of the brain during such doses that are important for controlling the depth of anesthesia in long-term experiments using magnetic resonance imaging, multiphoton microscopy, etc., which are crucial for the interpretation of experimental results. These findings provide an important informative platform for the enhancement and refinement of surgery, since the EEG-based DFA analysis of BBB can easily be used during surgery as a tool for characterizing normal BBB functions under anesthesia.

Leveraging a virtual alley with continuously varying width modulates step width variability during self-paced treadmill walking

Increased fall risk in older adults and clinical populations is linked with increased amount and altered temporal structure of step width variability. One approach to rehabilitation seeks to reduce fall risk in older adults by reducing the amount of step width variability and restoring the temporal structure characteristic of healthy young adults. The success of such a program depends on our ability to modulate step width variability effectively. To this end, we investigated how manipulation of the visual walking space in a virtual environment could modulate the amount and temporal structure of step width variability. Nine healthy adults performed self-paced treadmill walking in a virtual alley in a fixed-width Control condition (1.91 m) and two conditions in which the alley's width oscillated sinusoidally at 0.03 Hz: between 0.38 and 1.14 m and 0.38-2.67 m in Narrow and Wide conditions, respectively. The step width time series from each condition was evaluated using: (i) the standard deviation to identify changes in the amount of variability and (ii) the fractal scaling exponent estimated using detrended fluctuation analysis (DFA) to identify changes in the temporal structure of variability in terms of persistence in fluctuations. The Wide condition neither affected the standard deviation nor the fractal scaling exponent of step width time series. The Narrow condition did not affect the standard deviation of step width time series compared to the Control condition but significantly increased its fractal scaling exponent compared to the Control and Wide conditions, suggestive of more persistent fluctuations characteristic of a healthy gait. These results show that virtual reality based rehabilitative intervention can modulate step width variability to potentially reduce fall risk in older adults and clinical populations.

Quantitative Gait Feature Assessment on Two-Dimensional Body Axis Projection Planes Converted from Three-Dimensional Coordinates Estimated with a Deep Learning Smartphone App

To assess pathological gaits quantitatively, three-dimensional coordinates estimated with a deep learning model were converted into body axis plane projections. First, 15 healthy volunteers performed four gait patterns; that is, normal, shuffling, short-stepped, and wide-based gaits, with the Three-Dimensional Pose Tracker for Gait Test (TDPT-GT) application. Second, gaits of 47 patients with idiopathic normal pressure hydrocephalus (iNPH) and 92 healthy elderly individuals in the Takahata cohort were assessed with the TDPT-GT. Two-dimensional relative coordinates were calculated from the three-dimensional coordinates by projecting the sagittal, coronal, and axial planes. Indices of the two-dimensional relative coordinates associated with a pathological gait were comprehensively explored. The candidate indices for the shuffling gait were the angle range of the hip joint < 30° and relative vertical amplitude of the heel < 0.1 on the sagittal projection plane. For the short-stepped gait, the angle range of the knee joint < 45° on the sagittal projection plane was a candidate index. The candidate index for the wide-based gait was the leg outward shift > 0.1 on the axial projection plane. In conclusion, the two-dimensional coordinates on the body axis projection planes calculated from the 3D relative coordinates estimated by the TDPT-GT application enabled the quantification of pathological gait features.

The Effect of Lateral Wedge Insole on Gait Variability Assessed Using Wearable Sensors in Patients with Medial Compartment Knee Osteoarthritis

Background

Lateral thrust seen in people with medial compartment knee osteoarthritis can cause dynamic knee instability and poor postural control during gait cycles. A lateral wedge insole can reduce the lateral thrust and may have a favorable effect on gait variability, which in turn may indicate gait instability improves. The aim of this study was to investigate the effect of lateral wedge insole on gait variability in knee osteoarthritis patients.

Method

We involved 15 symptomatic knee osteoarthritis patients who were provided with lateral wedge insole and 13 healthy asymptomatic volunteers as the control group. The gait variability was evaluated as the coefficient of variation of stride, stance, and swing duration based on acceleration monitoring using a wearable sensor. The lateral thrust was estimated as the lateral acceleration peak on the shank sensor. These measurements were performed without lateral wedge insole (baseline), immediately with lateral wedge insole (T0) at the initial office visit and one month after intervention (T1).

Result

Our data showed that the stance duration coefficient of variation and lateral thrust at T1 in the knee osteoarthritis group, were significantly decreased compared to the baseline values and these values were identical to those in the control group.

Conclusion

The lateral wedge insole reduces dynamic knee instability and could improve gait variability in medial compartment knee osteoarthritis.

Obesity Is Associated With Gait Alterations and Gait Asymmetry in Older Adults

OBJECTIVES

The prevalence of obesity (OB) has increased in the older adult (OA) population. However, it is not quite clear whether OB exaggerates gait instability and leads to a higher risk of falls in OAs. The first goal of this study was to investigate whether OB is associated with gait alterations and gait asymmetry in OAs. The second goal of this study was to examine relationships between various OB measures with gait measures and gait symmetry measures in OAs.

METHODS

A total of 30 OAs were included and categorized according to their body mass index (BMI) values into groups of persons with normal weight (NW), overweight (OW), and OB. Participants were required to complete an anthropometric assessment, a body composition assessment, and overground walking tests.

RESULTS

The group with OB had shorter swing phase, longer stance phase, and shorter single support phase than the NW group. Increased body weight, BMI, visceral adipose tissue mass, and android fat had correlations with shorter swing phase, longer stance phase, and shorter single support phase. Increased body weight and BMI had significantly positive correlations with symmetry index of knee range of motion.

CONCLUSIONS

OB may impair gait automation capacity in OAs. Both body weight and BMI remain good measures in terms of establishing correlations with gait stability in OAs. However, the amount of fat mass surrounding the abdomen could be vital to interpreting the alterations in the gait of OAs with obesity.

Step-adaptive sound guidance enhances locomotor-respiratory coupling in novice female runners: A proof-of-concept study

Introduction

Many runners struggle to find a rhythm during running. This may be because 20-40% of runners experience unexplained, unpleasant breathlessness at exercise onset. Locomotor-respiratory coupling (LRC), a synchronization phenomenon in which the breath is precisely timed with the steps, may provide metabolic or perceptual benefits to address these limitations. It can also be consciously performed. Hence, we developed a custom smartphone application to provide real-time LRC guidance based on individual step rate.

Methods

Sixteen novice-intermediate female runners completed two control runs outdoors and indoors at a self-selected speed with auditory step rate feedback. Then, the runs were replicated with individualized breath guidance at specific LRC ratios. Hexoskin smart shirts were worn and analyzed with custom algorithms to estimate continuous LRC frequency and phase coupling.

Results

LRC guidance led to a large significant increase in frequency coupling outdoor from 26.3 ± 10.7 (control) to 69.9 ± 20.0 % (LRC) "attached". There were similarly large differences in phase coupling between paired trials, and LRC adherence was stronger for the indoor treadmill runs versus outdoors. There was large inter-individual variability in running pace, preferred LRC ratio, and instruction adherence metrics.

Discussion

Our approach demonstrates how personalized, step-adaptive sound guidance can be used to support this breathing strategy in novice runners. Subsequent investigations should evaluate the skill learning of LRC on a longer time basis to effectively clarify its risks and advantages.

Military training alters the fractal behavior of step width

Non-linear analyses have been successfully applied to gait with evidence that fractal behavior of gait-related variables provide insights into function. Specifically, shifts in the fractal behavior of step width from pink toward white noise reflects a loss of complexity and diminished adaptive capacity and functionality. We previously reported an apparent difference in the fractal behavior of step width during treadmill walking between Service members with transtibial amputations and able-bodied civilian. We now combine recently collected data and data from two previous studies to further explore the relationship between lower limb injury, military service, and step width fractal behavior. Service member, regardless of the presence or type of injury, demonstrate step width fractal behavior walked in a way that the fractal behavior of their gait was significantly closer to white noise (-0.5 dB/Hz²) than uninjured civilians (-0.82 dB/Hz²). This data suggests that military training/service leads to a change in step width fractal behavior. Further studies are needed to explore what may cause this difference and any implications this may have on stability or performance.

Effects of exercise habituation and aging on the intersegmental coordination of lower limbs during walking with sinusoidal speed change

Background

The time courses of the joint elevation angles of the thigh, shank, and foot in one stride during walking can be well approximated by a “plane” in a triaxial space. This intersegmental coordination (IC) of the lower limb elevation angles is referred to as the planar covariation law. We examined the effects of exercise habituation and aging on the thickness of the IC plane of the lower limbs under sinusoidal speed changing conditions.

Methods

Seventeen sedentary young (SY), 16 active young (AY), and 16 active elderly (AE) adults walked on a treadmill in accordance with a sinusoidal speed changing protocol at 120, 60, and 30 s periods with an amplitude of ± 0.56 m·s⁻¹. Motion of the lower limbs from the sagittal direction was recorded to calculate the elevation angles of the lower limbs. When the best-fit IC plane was determined, the smallest standard deviation of the IC plane was considered as the anteroposterior gait variability of the lower limbs. The coefficient of variance of the step width was also quantified to evaluate the lateral step variability (CV_SW).

Results

The standard deviation of the IC plane was significantly greater in the order of SY, AY, and AE, regardless of the sinusoidal wave periods of the changing speed. The CV_SW was not significantly different among the three groups.

Conclusions

Exercise habituation influences anteroposterior gait variability of the lower limbs, but not lateral step variability, even in young adults. Given these, gait adaptability for sinusoidal speed changes does not always decline with aging.

Trial registration

UMIN000031456 (R000035911; registered February 23, 2018).

Supplementary Information

The online version contains supplementary material available at 10.1186/s40101-022-00298-w.

APDM gait and balance measures fail to predict symptom progression rate in Parkinson's disease

Parkinson's disease (PD) results in progressively worsening gait and balance dysfunction that can be measured using computerized devices. We utilized the longitudinal database of the Parkinson's Disease Biomarker Program to determine if baseline gait and balance measures predict future rates of symptom progression. We included 230, 222, 164, and 177 PD subjects with 6, 12, 18, and 24 months of follow-up, respectively, and we defined progression as worsening of the following clinical parameters: MDS-UPDRS total score, Montreal Cognitive Assessment, PDQ-39 mobility subscale, levodopa equivalent daily dose, Schwab and England score, and global composite outcome. We developed ridge regression models to independently estimate how each gait or balance measure, or combination of measures, predicted progression. The accuracy of each ridge regression model was calculated by cross-validation in which 90% of the data were used to estimate the ridge regression model which was then tested on the 10% of data left out. While the models modestly predicted change in outcomes at the 6-month follow-up visit (accuracy in the range of 66–71%) there was no change in the outcome variables during this short follow-up (median change in MDS-UPDRS total score = 0 and change in LEDD = 0). At follow-up periods of 12, 18, and 24 months, the models failed to predict change (accuracy in the held-out sets ranged from 42 to 60%). We conclude that this set of computerized gait and balance measures performed at baseline is unlikely to help predict future disease progression in PD. Research scientists must continue to search for progression predictors to enhance the performance of disease modifying clinical trials.

Six-month change in gait speed to discriminate between those with and without falls history in older people with Mild Cognitive Impairment and mild Alzheimer disease

BACKGROUND AND PURPOSE

The purposes of this study were to identify differences in gait speed performance over 6 months between older people with Preserved Cognition (PrC), with Mild Cognitive Impairment (MCI) and with Alzheimer disease (AD) in mild stage; and to verify if the change in gait speed could discriminate fallers in older people with MCI and AD in a mild stage METHODS: A longitudinal study was conducted with community-dwelling older adults, including 40 with PrC, 36 with MCI and 34 with AD in the mild stage. Gait speed (in m/s) changes were captured through a 10-meter walk test. We documented the number of self-reported falls by monthly calendars that were returned after a 6-month follow-up. During this period, the participants received monthly telephone calls to remind them to fill in the calendar RESULTS: There was a significant difference in terms of sex and age between the groups: 23%, 31% and 19% were female and had a mean age of 72.8, 75.9 and 76.9 years in the PrC, MCI and AD groups respectively. During the follow-up, 45%, 52.7% and 52.9% of the PrC, MCI and AD groups fell. The MCI and AD groups presented lower gait speed compared to the PrC Group at both moments. There was no significant difference in the change of gait speed between groups. In the model adjusted by age, the change in gait speed failed to discriminate fallers in older people with MCI and with AD CONCLUSION: Older people with MCI and AD in the mild stage present lower gait speed compared to older people with PrC. Changes in gait speed over a short period of time do not discriminate fallers in older people with MCI or AD in a mild stage.

The effect of first-time 4-wheeled walker use on the gait of younger and older adults

INTRODUCTION

The 4-wheeled walker is intended to enhance balance and gait for older adults. Yet, some research suggests that walking aids increase falls risk. An understanding of the influence of age with walker use on gait performance is required.

OBJECTIVE

To examine the effect of initial 4-wheeled walker use on spatiotemporal gait parameters between younger and older adults.

DESIGN

Cross-sectional, repeated-measures.

SETTING

Community-dwelling.

PARTICIPANTS

Twenty-five younger (age: 26.5 ± 4.1 years) and 24 older (age: 68.5 ± 10.5 years) adults participated. Younger adults were aged 18 to 35 years, whereas older adults were 50 years or older. Included were people not requiring the use of a walking aid, and those able to converse in English.

INTERVENTIONS

Not applicable.

MAIN OUTCOME MEASURE(S)

Gait velocity and stride time variability were recorded using accelerometers. Gait was examined under three conditions: unassisted walking; walking with a 4-wheeled walker; and walking with a 4-wheeled walker while completing a secondary task. Conditions were performed across two walking paths: straight and figure-of-8 Walk Test. Separate mixed-methods analyses of variance (ANOVAs; within-subject: condition/path; between-subject: group) were used for statistical analyses.

RESULTS

Velocity was lower when walking using a walker while completing a cognitive task (p < .001), in the figure-of-8 Walk Test (p < .001), and in older adults (p = .001). Stride time variability increased with walking path and condition difficulty (p < .001) for the straight path versus the figure-of-8 Walk Test.

CONCLUSIONS

Using a 4-wheeled walker resulted in a slower and more inconsistent gait pattern across both age groups. Walking more complex configurations resulted in the prioritization of gait over the cognitive task while performing the dual-task conditions. No evidence of an age-related difference in the effect of initial walker use on gait was observed. Nonetheless, walkers are cognitively demanding and their introduction should warrant a clinical follow-up.

From anticipation to impulsivity in Parkinson's disease

Anticipatory actions require to keep track of elapsed time and inhibitory control. These cognitive functions could be impacted in Parkinson's disease (iPD). To test this hypothesis, a saccadic reaction time task was used where a visual warning stimulus (WS) predicted the occurrence of an imperative one (IS) appearing after a short delay. In the implicit condition, subjects were not informed about the duration of the delay, disfavoring anticipatory behavior but leaving inhibitory control unaltered. In the explicit condition, delay duration was cued. This should favor anticipatory behavior and perhaps alter inhibitory control. This hypothesis was tested in controls (N = 18) and age-matched iPD patients (N = 20; ON and OFF L-DOPA). We found that the latency distribution of saccades before the IS was bimodal. The 1^st mode weakly depended on temporal information and was more prominent in iPD. Saccades in this mode were premature and could result of a lack of inhibition. The 2^nd mode covaried with cued duration suggesting that these movements were genuine anticipatory saccades. The explicit condition increased the probability of anticipatory saccades before the IS in controls and iPD_ON but not iPD_OFF patients. Furthermore, in iPD patients the probability of sequences of 1^st mode premature responses increased. In conclusion, the triggering of a premature saccade or the initiation of a controlled anticipatory one could be conceptualized as the output of two independent stochastic processes. Altered time perception and increased motor impulsivity could alter the balance between these two processes in favor of the latter in iPD, particularly OFF L-Dopa.

Association between Self-Reported Prior Night's Sleep and Single-Task Gait in Healthy, Young Adults: A Study Using Machine Learning

Failure to obtain the recommended 7−9 h of sleep has been associated with injuries in youth and adults. However, most research on the influence of prior night’s sleep and gait has been conducted on older adults and clinical populations. Therefore, the objective of this study was to identify individuals who experience partial sleep deprivation and/or sleep extension the prior night using single task gait. Participants (n = 123, age 24.3 ± 4.0 years; 65% female) agreed to participate in this study. Self-reported sleep duration of the night prior to testing was collected. Gait data was collected with inertial sensors during a 2 min walk test. Group differences (<7 h and >9 h, poor sleepers; 7−9 h, good sleepers) in gait characteristics were assessed using machine learning and a post-hoc ANCOVA. Results indicated a correlation (r = 0.79) between gait parameters and prior night’s sleep. The most accurate machine learning model was a Random Forest Classifier using the top 9 features, which had a mean accuracy of 65.03%. Our findings suggest that good sleepers had more asymmetrical gait patterns and were better at maintaining gait speed than poor sleepers. Further research with larger subject sizes is needed to develop more accurate machine learning models to identify prior night’s sleep using single-task gait.

Nonlinear Analyses Distinguish Load Carriage Dynamics in Walking and Standing: A Systematic Review

Load carriage experiments are typically performed from a linear perspective that assumes that movement variability is equivalent to error or noise in the neuromuscular system. A complimentary, nonlinear perspective that treats variability as the object of study has generated important results in movement science outside load carriage settings. To date, no systematic review has yet been conducted to understand how load carriage dynamics change from a nonlinear perspective. The goal of this systematic review is to fill that need. Relevant literature was extracted and reviewed for general trends involving nonlinear perspectives on load carriage. Nonlinear analyses that were used in the reviewed studies included sample, multiscale, and approximate entropy; the Lyapunov exponent; fractal analysis; and relative phase. In general, nonlinear tools successfully distinguish between unloaded and loaded conditions in standing and walking, although not in a consistent manner. The Lyapunov exponent and entropy were the most used nonlinear methods. Two noteworthy findings are that entropy in quiet standing studies tends to decrease, whereas the Lyapunov exponent in walking studies tends to increase, both due to added load. Thus, nonlinear analyses reveal altered load carriage dynamics, demonstrating promise in applying a nonlinear perspective to load carriage while also underscoring the need for more research.

Augmented Cooper test: Biomechanical contributions to endurance performance

Running mechanics are modifiable with training and adopting an economical running technique can improve running economy and hence performance. While field measurement of running economy is cumbersome, running mechanics can be assessed accurately and conveniently using wearable inertial measurement units (IMUs). In this work, we extended this wearables-based approach to the Cooper test, by assessing the relative contribution of running biomechanics to the endurance performance. Furthermore, we explored different methods of estimating the distance covered in the Cooper test using a wearable global navigation satellite system (GNSS) receiver. Thirty-three runners (18 highly trained and 15 recreational) performed an incremental laboratory treadmill test to measure their maximum aerobic speed (MAS) and speed at the second ventilatory threshold (sVT2). They completed a 12-minute Cooper running test with foot-worm IMUs and a chest-worn GNSS-IMU on a running track 1–2 weeks later. Using the GNSS receiver, an accurate estimation of the 12-minute distance was obtained (accuracy of 16.5 m and precision of 1.1%). Using this distance, we showed a reliable estimation [R² > 0.9, RMSE ϵ (0.07, 0.25) km/h] of the MAS and sVT2. Biomechanical metrics were extracted using validated algorithm and their association with endurance performance was estimated. Additionally, the high-/low-performance runners were compared using pairwise statistical testing. All performance variables, MAS, sVT2, and average speed during Cooper test, were predicted with an acceptable error (R² ≥ 0.65, RMSE ≤ 1.80 kmh⁻¹) using only the biomechanical metrics. The most relevant metrics were used to develop a biomechanical profile representing the running technique and its temporal evolution with acute fatigue, identifying different profiles for runners with highest and lowest endurance performance. This profile could potentially be used in standardized functional capacity measurements to improve personalization of training and rehabilitation programs.

A systematic review of chiropractic care for fall prevention: rationale, state of the evidence, and recommendations for future research

BACKGROUND

Falls in older adults are a significant and growing public health concern. There are multiple risk factors associated with falls that may be addressed within the scope of chiropractic training and licensure. Few attempts have been made to summarize existing evidence on multimodal chiropractic care and fall risk mitigation. Therefore, the broad purpose of this review was to summarize this research to date. BODY: Systematic review was conducted following PRISMA guidelines. Databases searched included PubMed, Embase, Cochrane Library, PEDro, and Index of Chiropractic Literature. Eligible study designs included randomized controlled trials (RCT), prospective non-randomized controlled, observational, and cross-over studies in which multimodal chiropractic care was the primary intervention and changes in gait, balance and/or falls were outcomes. Risk of bias was also assessed using the 8-item Cochrane Collaboration Tool. The original search yielded 889 articles; 21 met final eligibility including 10 RCTs. One study directly measured the frequency of falls (underpowered secondary outcome) while most studies assessed short-term measurements of gait and balance. The overall methodological quality of identified studies and findings were mixed, limiting interpretation regarding the potential impact of chiropractic care on fall risk to qualitative synthesis.

CONCLUSION

Little high-quality research has been published to inform how multimodal chiropractic care can best address and positively influence fall prevention. We propose strategies for building an evidence base to inform the role of multimodal chiropractic care in fall prevention and outline recommendations for future research to fill current evidence gaps.

Wrist Movement Variability Assessment in Individuals with Parkinson's Disease

(1) Background: Parkinson’s disease (PD) is a neurodegenerative disorder represented by the progressive loss of dopamine-producing neurons, it decreases the individual’s motor functions and affects the execution of movements. There is a real need to include quantitative techniques and reliable methods to assess the evolution of PD. (2) Methods: This cross-sectional study assessed the variability of wrist RUD (radial and ulnar deviation) and FE (flexion and extension) movements measured by two pairs of capacitive sensors (PS25454 EPIC). The hypothesis was that PD patients have less variability in wrist movement execution than healthy individuals. The data was collected from 29 participants (age: 62.13 ± 9.7) with PD and 29 healthy individuals (60.70 ± 8). Subjects performed the experimental tasks at normal and fast speeds. Six features that captured the amplitude of the hand movements around two axes were estimated from the collected signals. (3) Results: The movement variability was greater for healthy individuals than for PD patients (p < 0.05). (4) Conclusion: The low variability seen in the PD group may indicate they execute wrist RUD and FE in a more restricted way. The variability analysis proposed here could be used as an indicator of patient progress in therapeutic programs and required changes in medication dosage.

Association of Muscle Mass, Muscle Strength, and Muscle Function with Gait Ability Assessed Using Inertial Measurement Unit Sensors in Older Women

Aging-related muscle atrophy is associated with decreased muscle mass (MM), muscle strength (MS), and muscle function (MF) and may cause motor control, balance, and gait pattern impairments. This study determined associations of three speed-based gait variables with loss of MM, MS, and MF in older women. Overall, 432 older women aged ≥65 performed appendicular skeletal muscle, handgrip strength, and five times sit-to-stand test to evaluate MM, MS, and MF. A gait test was performed at three speeds by modifying the preferred walking speed (PWS; slower walking speed (SWS); faster-walking speed (FWS)) on a straight 19 m walkway. Stride length (SL) at PWS was significantly associated with MM. FWS and coefficient of variance (CV) of double support phase (DSP) and DSP at PWS showed significant associations with MS. CV of step time and stride time at SWS, FWS, and single support phase (SSP) at PWS showed significant associations with MF. SL at PWS, DSP at FWS, CV of DSP at PWS, stride time at SWS, and CV of SSP at PWS showed significant associations with composite MM, MS, and MF variables. Our study indicated that gait tasks under continuous and various speed conditions are useful for evaluating MM, MS, and MF.

Complexity of Running and Its Relationship with Joint Kinematics during a Prolonged Run

We investigated the effect of prolonged running on joint kinematics and its association with stride complexity between novice and elite runners. Ten elite marathoners and eleven healthy individuals took part in a 20 min submaximal prolonged running experiment at their preferred running speed (PRS). A three-dimensional motion capture system was utilized to capture and calculate the alpha exponent, stride-to-stride fluctuations (SSFs), and stride-to-stride variability (SSV) of spatiotemporal parameters and joint kinematics. In the results, the elite athletes ran at a considerably higher PRS than the novice runners, yet no significant differences were found in respiratory exchange ratio with increasing time intervals. For the spatiotemporal parameters, we observed a significant increase in the step width and length variability in novice runners with increasing time-interval (p < 0.05). However, we did not observe any differences in the alpha exponent of spatiotemporal parameters. Significant differences in SSF of joint kinematics were observed, particularly in the sagittal plane for ankle, knee, and hip at heel strike (p < 0.05). While in mid-stance, time-interval differences were observed in novices who ran with a lower knee flexion angle (p < 0.05). During toe-off, significantly higher SSV was observed, particularly in the hip and ankle for novices (p < 0.05). The correlation analysis of joint SSV revealed a distinct negative relationship with the alpha exponent of step-length and step-width for elite runners, while, for novices, a positive relation was observed only for the alpha exponent of step-width. In conclusion, our study shows that increased step-width variability seen in novices could be a compensatory mechanism to maintain performance and mitigate the loss of stability. On the other hand, elite runners showed a training-induced effective modulation of lower-limb kinematics to improve their running performance.

Characterizing stroke-induced changes in the variability of lower limb kinematics using multifractal detrended fluctuation analysis

Movement variability reflects the adaptation of the neuromuscular control system to internal or external perturbations, but its relationship to stroke-induced injury is still unclear. In this study, the multifractal detrended fluctuation analysis was used to explore the stroke-induced changes in movement variability by analyzing the joint angles in a treadmill-walking task. Eight healthy subjects and ten patients after stroke participated in the experiment, performing a treadmill-walking task at a comfortable speed. The kinematics data of the lower limbs were collected by the motion-capture system, and two indicators, the degree of multifractality (α) and degree of correlation [h(2)], were used to investigate the mechanisms underlying neuromuscular control. The results showed that the knee and ankle joint angles were multifractal and persistent at various scales, and there was a significant difference in the degree of multifractality and the degree of correlation at the knee and ankle joint angles among the three groups, with the values being ranked in the following order: healthy subjects < non-paretic limb < paretic limb. These observations highlighted increased movement variability and multifractal strength in patients after stroke due to neuromotor defects. This study provided evidence that multifractal detrended analysis of the angles of the knee and ankle joints is useful to investigate the changes in movement variability and multifractal after stroke. Further research is needed to verify and promote the clinical applications.

Cardio-Hypothalamic-Pituitary Coupling during Rest and in Response to Exercise

The objective of this study was to examine cardio hypothalamic-pituitary coupling and to better understand how the temporal relations between these systems are altered during rest and exercise conditions. An intensive within subjects study design was used. Seven adult males completed two visits, each consisting of either a 24 h period of complete rest or a 24 h period containing a high-intensity exercise bout. An intravenous catheter was used to collect serum samples every 10 min throughout the 24 h period (i.e., 145 samples/person/condition) to assess growth hormone (GH) dynamics throughout the 24 h period. Cardiac dynamics were also collected throughout the 24 h period and epoched into 3 min windows every 10 min, providing serial short-time measurements of heart rate variability (HRV) concurrent to the GH sampling. The standard deviation of the normal RR interval (SDNN), the root mean square of successive differences (rMSSD), and sample entropy (SampEn) was calculated for each epoch and used to create new profiles. The dynamics of these profiles were individually quantified using SampEn and recurrence quantification analysis (RQA). To address our central question, the coupling between these profiles with GH was assessed using cross-SampEn and cross-RQA (cRQA). A comparison between the epoched HRV profiles indicated a main effect between profiles for sample entropy (p < 0.001) and several measures from RQA. An interaction between profile and condition was observed for cross-SampEn (p = 0.04) and several measures from cRQA. These findings highlight the potential application of epoched HRV to assess changes in cardiac dynamics, with specific applications to assessing cardio hypothalamic-pituitary coupling.

Development of Smartphone Application for Markerless Three-Dimensional Motion Capture Based on Deep Learning Model

To quantitatively assess pathological gait, we developed a novel smartphone application for full-body human motion tracking in real time from markerless video-based images using a smartphone monocular camera and deep learning. As training data for deep learning, the original three-dimensional (3D) dataset comprising more than 1 million captured images from the 3D motion of 90 humanoid characters and the two-dimensional dataset of COCO 2017 were prepared. The 3D heatmap offset data consisting of 28 × 28 × 28 blocks with three red-green-blue colors at the 24 key points of the entire body motion were learned using the convolutional neural network, modified ResNet34. At each key point, the hottest spot deviating from the center of the cell was learned using the tanh function. Our new iOS application could detect the relative tri-axial coordinates of the 24 whole-body key points centered on the navel in real time without any markers for motion capture. By using the relative coordinates, the 3D angles of the neck, lumbar, bilateral hip, knee, and ankle joints were estimated. Any human motion could be quantitatively and easily assessed using a new smartphone application named Three-Dimensional Pose Tracker for Gait Test (TDPT-GT) without any body markers or multipoint cameras.

Cognition Meets Gait: Where and How Mind and Body Weave Each Other in a Computational Psychometrics Approach in Aging

Aging may be associated with conditions characterized by motor and cognitive alterations, which could have a detrimental impact on daily life. Although motors and cognitive aspects have always been treated as separate entities, recent literature highlights their relationship, stressing a strong association between locomotion and executive functions. Thus, designing interventions targeting the risks deriving from both components’ impairments is crucial: the dual-task represents a starting point. Although its role in targeting and decreasing difficulties in aging is well known, most interventions are focused on a single domain, proposing a vertical model in which patients emerge only for a single aspect per time during assessment and rehabilitation. In this perspective, we propose a view of the individual as a whole between mind and body, suggesting a multicomponent and multidomain approach that could integrate different domains at the same time retracing lifelike situations. Virtual Reality, thanks to the possibility to develop daily environments with engaging challenges for patients, as well as to manage different devices to collect multiple data, provides the optimal scenario in which the integration could occur. Artificial Intelligence, otherwise, offers the best methodologies to integrate a great amount of various data to create a predictive model and identify appropriate and individualized interventions. Based on these assumptions the present perspective aims to propose the development of a new approach to an integrated, multimethod, multidimensional training in order to enhance cognition and physical aspects based on behavioral data, incorporating consolidated technologies in an innovative approach to neurology.

Does cognitive loading interfere with walking control?

BACKGROUND

Cognitive-motor interference is a common method used to investigate the cognitive demands of human walking. Using this methodology, consistent effects emerge: under cognitive load, walking velocity decreases, while spatio-temporal variability of walking increases. These effects are often interpreted as indicative of an interference in the ability to control gait. However, walking velocity is highly correlated with most gait parameters; thus, the increase in variability does not necessarily reflect reduced control, but rather a constant signal-to-noise ratio.

METHODS

To investigate the effect of cognitive loading on gait variability, we retrospectively analysed 3721 records of healthy young adults, walking with and without a concurrent cognitive task, on a treadmill.

RESULTS

Stride duration and length increased under cognitive load, while the variability of these parameters decreased. Further, these effects were different between participants starting to walk without cognitive loading and those starting to walk with cognitive loading.

CONCLUSIONS

Dual tasking is more likely to divert the focus of attention away from the walking task, causing a shift of balance between automatic and conscious control, as opposed to interference per-se.

The effect of peripheral arterial disease and intermittent claudication on gait regularity and symmetry

Peripheral arterial disease (PAD) affects 20-30% of older adults and is associated with intermittent claudication (IC), which is walking-induced pain. This study compared the regularity and symmetry of gait between healthy older adults and adults with PAD, and between IC and non-IC conditions in the PAD group. Eighteen control (70.7 ± 6.3 years) and 11 PAD participants (67.0 ± 10.1 years) walked overground at a continuous, self-selected speed. A waist-mounted accelerometer determined step time, stride time, gait speed and mediolateral (ML), vertical (V) and anteroposterior (AP) gait regularity (step/stride) and symmetry. Correlations between ankle-brachial index (ABI) scores and PAD gait regularity/symmetry were also investigated. PAD step and stride times were greater (p < 0.01), while gait speed, ML and AP step regularity and ML and V stride regularity were significantly less than the controls (p < 0.05). There were no significant differences in gait symmetry. Within the PAD group, post-IC step/stride time and speed increased and decreased, respectively, (p < 0.05), while post-IC step and stride regularity were significantly less in all three directions (p < 0.01). Similarly, ML and V post-IC gait asymmetry increased significantly (p < 0.05). ABI was significantly correlated with pre-and post-IC vertical stride regularity (p < 0.01), and with pre- and post-IC ML gait symmetry (p < 0.05). The results demonstrate that gait regularity decreases as a result of PAD and IC. The association between gait regularity/symmetry and ABI should be investigated further, as it may have clinical application to the assessment of PAD severity.

Attentional focus effect on dual-task walking in Parkinson's disease with and without freezing of gait

In Parkinson's disease, the optimal attentional focus strategy for dual-task walking may vary with freezing of gait (FOG), due to different severities of impaired automaticity. The study aimed to investigate (i) the immediate effect of attentional focus on dual-task walking in participants with and without FOG, and (ii) the training effect of attentional focus on walking, FOG, and falls. In experiment 1, FOG and non-FOG groups (16 participants each) performed a dual-task of holding two interlocking rings apart while walking, either without attention instruction or with instructions to focus attention internally or externally. Gait parameters and ring-touching times were measured. In experiment 2, 30 participants with FOG were randomized to 6 weeks of dual-task training with internal-focus or external-focus instruction. Before and after training, we recorded timed up-and-go (TUG) and TUG dual-task (TUGdt) in on-medication and off-medication states, and the numbers of FOG episodes and falls. The non-FOG group showed less step length variability and shorter ring-touching times with external-focus. The FOG group showed less step length variability, less cadence, increased gait velocity, and longer step lengths with internal-focus compared to external-focus and no-focus instructions. Both internal-focus and external-focus training reduced FOG and falls after intervention, but only internal-focus training reduced TUG and TUGdt in both on-medication and off-medication states. Our findings suggest external-focus would enhance walking automaticity and the concurrent task accuracy for non-freezers, whereas for freezers, internal-focus could increase gait stability and lead to a more positive effect on improving locomotion control and reducing falling risk.

Gait variability between younger and older adults: An equality of variance analysis

BACKGROUND

To estimate gait variability, several methods have been routinely used which provide a measure of global variability. A recent study introduced a group waveform variability method which provides a point-by-point measurement of data variance equality. This can identify where in the gait cycle the significant differences in variability exist.

RESEARCH QUESTION

Do waveform differences exist in equality of variance and group means in lower limb biomechanical variables between healthy younger and older adults during a gait task?

METHODS

Twenty healthy younger (19-44 years old, age=29.9(7.0) years, body mass index= 24.6(3.2)kg/m², females= 10) and 20 healthy older (55-79 years old, age=63.6(5.5) years, body mass index= 25.9(2.7)kg/m², females= 10) adults who were free from lower limb injuries and had no musculoskeletal or neurological disorders. Temporospatial outcomes, sagittal and frontal lower limb joint angles and moments, along with joint powers were examined as participants walked at a self-selected pace. Waveform patterns were normalized to the gait cycle and compared using equality of variance and statistical parametric mapping techniques.

RESULTS

No difference in walking speed existed between the younger or older groups (P > .05). The older group had greater variability (P < .05) in sagittal hip angles, as well as greater frontal ankle angle and moment variability. The younger group had significantly greater mean (P < .05) ankle power generation prior to toe-off.

SIGNIFICANCE

This study provided a baseline of temporal differences in variance between healthy younger and older individuals. Its findings warrant the use of the equality of variance test to compare temporal differences for a variety of populations and tasks. Older adults generally had more variability than the younger adults, with many differences occurring near the transition from double- to single-limb support. The statistical parametric mapping analysis showed that the older adults could not generate as much ankle power as the younger adults prior to toe-off.

Comparing adaptive fractal and detrended fluctuation analyses of stride time variability: Tests of equivalence

BACKGROUND

Fractal analyses quantify self-similarities in stride-to-stride fluctuations over different time scales. Fractal exponents can be measured with adaptive fractal analysis (AFA) or detrended fluctuation analysis (DFA), though measurements obtained with the algorithms have not been directly compared.

RESEARCH QUESTION

Are stride time fractal exponents measured with AFA and DFA algorithms equivalent?

METHODS

Data from 50 participants with Parkinson's Disease (n = 15), age-similar healthy adults (n = 15) and healthy young adults (n = 20) were analyzed in this cross-sectional, observational study. Participants completed 6-min walks at self-selected speeds overground on a straight walkway and on a treadmill. Stride times were measured with inertial measurement units. Fractal exponents in stride time data were processed using AFA and DFA algorithms and compared with two one-sided tests of equivalence. Mixed ANOVAs were used to compare exponents between groups and conditions.

RESULTS

Fractal exponents computed with AFA and DFA were equivalent neither in the overground (0.796 & 0.830, respectively, p = .587) nor treadmill conditions (0.806 & 0.882, respectively, p = .122). Fractal exponents measured with DFA were higher than when measured with AFA. Standard errors were 22% lower when measured with AFA. Additionally, a group × condition interaction was statistically significant when fractal exponents were processed with the AFA algorithm (F(2,47) = 11.696, p < .001), whereas the group × condition interaction was not statistically significant when DFA exponents were compared (F(2, 47) = 2.144, p = .129).

SIGNIFICANCE

AFA and DFA do not produce equivalent estimates of the fractal exponent α in stride time dynamics. Estimates of the fractal exponent α obtained with AFA or DFA algorithms therefore should not be used interchangeably. Standard errors were lower when derived with AFA. Fractal exponents calculated with AFA may be more sensitive to conditions that influence stride time fractal dynamics than are measures calculated with DFA.

The Effects of High-Speed Resistance Training on Health Outcomes in Independent Older Adults: A Systematic Review and Meta-Analysis

Human ageing involves several physiological impairments—in particular, a decrease in sensorimotor function and changes in the nervous system reduce muscle strength, power, balance, and functional capacity performance. Preventive strategies are essential to ensure the quality of life of the elderly. High-speed resistance training (HSRT) may be an effective approach to muscle power development in this population, with significant short-term effects on neural adaptations and muscle power production. Therefore, the present study intends to analyze and systematize the studies focused on HSRT interventions and their effects on health outcomes in independent older adults. Four electronic databases (PubMed, Web of Science, EBSCO, and Scielo) were used for the purposes of searching randomized controlled trials that measured at least one key outcome measure focusing on velocity-based training and health outcomes in older adults on 7 March 2022 and identified 1950 studies. At the end of the process, fourteen studies were included in this systematic review and ten studies were included in the quantitative analysis. The main results showed that HSRT interventions would improve health measures, mostly cognitive function (large effects, p = 0.001, SMD = 0.94), neuromuscular function (moderate effects, p = 0.003, SMD = 0.70), and physical function (moderate effects, p = 0.04, SMD = 0.55 and p = 0.009, SMD = −0.59). Additionally, the results suggested that interventions with ten weeks or more, performed three times a week, provide significant improvements in neuromuscular function. In this sense, HSRT is effective for improving overall health outcomes in older adults. Future studies should include proper follow-ups (e.g., minimum six months) to assess the durability of HSRT intervention effects on all health-related variables.

Exploring the role of the left DLPFC in fatigue during unresisted rhythmic movements

Understanding central fatigue during motor activities is important in neuroscience and different medical fields. The central mechanisms of motor fatigue are known in depth for isometric muscle contractions; however, current knowledge about rhythmic movements and central fatigue is rather scarce. In this study, we explored the role of an executive area (left dorsolateral prefrontal cortex [DLPFC]) in fatigue development during rhythmic movement execution, finger tapping (FT) at the maximal rate, and fatigue after effects on the stability of rhythmic patterns. Participants (n = 19) performed six sets of unresisted FT (with a 3 min rest in‐between). Each set included four interleaved 30 s repetitions of self‐selected (two repetitions) and maximal rate FT (two repetitions) without rest in‐between. Left DLPFC involvement in the task was perturbed by transcranial static magnetic stimulation (tSMS) in two sessions (one real and one sham). Moreover, half of the self‐selected FT repetitions were performed concurrently with a demanding cognitive task, the Stroop test. Compared with sham stimulation, real tSMS stimulation prevented waning in tapping frequency at the maximal rate without affecting perceived levels of fatigue. Participants' engagement in the Stroop test just prior to maximal FT reduced the movement amplitude during this mode of execution. Movement variability at self‐selected rates increased during Stroop execution, especially under fatigue previously induced by maximal FT. Our results indicate cognitive‐motor interactions and a prominent role of the prefrontal cortex in fatigue and the motor control of simple repetitive movement patterns. We suggest the need to approach motor fatigue including cognitive perspectives.

We show the fundamental role of executive areas in fatigue caused by very simple repetitive movements. Fatigue developed less during the maximal frequency of movement production, while the left DLPFC received magnetic stimulation (in right‐handers). The role of cognitive‐motor interaction in fine motor control was also clear when participants engaged in cognitive tasks. At the clinical level, our work reinforces the need to treat fatigue from a comprehensive perspective.

Adaptive treadmill walking encourages persistent propulsion

BACKGROUND

Adaptive treadmills allow real-time changes in walking speed by responding to changes in step length, propulsion, or position on the treadmill. The stride-to-stride variability, or persistence, of stride time during overground, fixed-speed, and adaptive treadmill walking has been studied, but persistence of propulsion during adaptive treadmill walking remains unknown. Because increased propulsion is often a goal of post-stroke rehabilitation, knowledge of the stride-to-stride variability may aid rehabilitation protocol design.

RESEARCH QUESTION

How do spatiotemporal and propulsive gait variables vary from stride to stride during adaptive treadmill walking, and how do they compare to fixed-speed treadmill walking?

METHODS

Eighteen young healthy subjects walked on an instrumented split-belt treadmill in the adaptive and fixed-speed modes for 10 minutes at their comfortable speed. Kinetic data was collected from the treadmill. Detrended fluctuation analysis was applied to the time series data. Shapiro-Wilk tests assessed normality and one-way repeated measures ANOVAs compared between adaptive, fixed-speed, and randomly shuffled conditions at a Bonferroni-corrected significance level of 0.0055.

RESULTS

Stride time, stride length, step length, and braking impulse were persistent (α > 0.5) in the adaptive and fixed-speed conditions. Adaptive and fixed-speed were different from each other. Stride speed was persistent in the adaptive condition and anti-persistent (α < 0.5) in the fixed-speed condition. Peak propulsive force, peak braking force, and propulsive impulse were persistent in the adaptive condition but not the fixed-speed condition (α ≈ 0.5). Net impulse was non-persistent in the adaptive and fixed-speed conditions. All variables were non-persistent in the shuffled condition.

SIGNIFICANCE

During adaptive treadmill walking, increases in propulsive force and impulse persist for multiple strides. Persistence was stronger on the adaptive treadmill, where increased propulsion translates into increased walking speed. For post-stroke gait rehabilitation where increasing propulsion and speed are goals, the stronger persistence of adaptive treadmill walking may be beneficial.

Quantifying the effect of sagittal plane joint angle variability on bipedal fall risk

Falls are a major issue for bipeds. For elderly adults, falls can have a negative impact on their quality of life and lead to increased medical costs. Fortunately, interventional methods are effective at reducing falls assuming they are prescribed. For biped robots, falls prevent them from completing required tasks. Thus, it is important to understand what aspects of gait increase fall risk. Gait variability may be associated with increased fall risk; however, previous studies have not investigated the variation in the movement of the legs. The purpose of this study was to determine the effect of joint angle variability on falling to determine which component(s) of variability were statistically significant. In order to investigate joint angle variability, a physics-based simulation model that captured joint angle variability as a function of time through Fourier series was used. This allowed the magnitude, the frequency mean, and the frequency standard deviation of the variability to be altered. For the values tested, results indicated that the magnitude of the variability had the most significant impact on falling, and specifically that the stance knee flexion variability magnitude was the most significant factor. This suggests that increasing the joint variability magnitude may increase fall risk, particularly if the controller is not able to actively compensate. Altering the variability frequency had little to no effect on falling.

Long-range correlations and stride pattern variability in recreational and elite distance runners during a prolonged run

BACKGROUND

Although movement variability and long-range correlations (LRCs) have been assessed in relation to neuropathology and aging during walking, to date only a few studies have investigated these aspects in subjects of different skill levels during prolonged overground running.

RESEARCH QUESTION

What effect does skill level and run duration have on different stride parameters, measures of variability and long-range correlations?

METHODS

Using a between-subject repeated measures design, we assessed stride mechanics, variability and LRCs in recreational and elite runners over the course of a continuous exhaustive run. All subjects ran at a fixed, pre-determined running speed relative to their maximal performance. Stride parameters were continually recorded using a single foot-mounted inertial measurement unit. It was hypothesized that a significant reduction in the strength of the LRCs would occur over the course of the run and that the observed changes would be more pronounced in the group of recreational runners.

RESULTS

Runners maintained a consistent stride length (SL), stride time (ST) and contact time (CT) during the run, while peak impact acceleration increased. Across groups, long-range correlations significantly decreased over the course of the run, while the magnitude of the variability remained constant. LRCs did not differ significantly between groups.

SIGNIFICANCE

This is the first study to simultaneously investigate the effects of prolonged running and skill level on a range of stride parameters as well as stride-to-stride variability. Generally, long-range correlations were shown to be sensitive to run duration, while the magnitude of the variability did not differ between earlier and later stages of the run. The lack of a group effect on LRCs supports the idea that the mechanisms responsible for the emergence of temporal patterns in the stride pattern are not influenced by skill level.

Fractal-Based Analysis of fMRI BOLD Signal During Naturalistic Viewing Conditions

Background: Temporal fractals are characterized by prominent scale-invariance and self-similarity across time scales. Monofractal analysis quantifies this scaling behavior in a single parameter, the Hurst exponent (H). Higher H reflects greater correlation in the signal structure, which is taken as being more fractal. Previous fMRI studies have observed lower H during conventional tasks relative to resting state conditions, and shown that H is negatively correlated with task difficulty and novelty. To date, no study has investigated the fractal dynamics of BOLD signal during naturalistic conditions. Methods: We performed fractal analysis on Human Connectome Project 7T fMRI data (n = 72, 41 females, mean age 29.46 ± 3.76 years) to compare H across movie-watching and rest. Results: In contrast to previous work using conventional tasks, we found higher H values for movie relative to rest (mean difference = 0.014; p = 5.279 × 10^-7; 95% CI [0.009, 0.019]). H was significantly higher in movie than rest in the visual, somatomotor and dorsal attention networks, but was significantly lower during movie in the frontoparietal and default networks. We found no cross-condition differences in test-retest reliability of H. Finally, we found that H of movie-derived stimulus properties (e.g., luminance changes) were fractal whereas H of head motion estimates were non-fractal. Conclusions: Overall, our findings suggest that movie-watching induces fractal signal dynamics. In line with recent work characterizing connectivity-based brain state dynamics during movie-watching, we speculate that these fractal dynamics reflect the configuring and reconfiguring of brain states that occurs during naturalistic processing, and are markedly different than dynamics observed during conventional tasks.

Improvement of Gait in Patients with Stroke Using Rhythmic Sensory Stimulation: A Case-Control Study

Patients with stroke suffer from impaired locomotion, exhibiting unstable walking with increased gait variability. Effects of rhythmic sensory stimulation on unstable gait of patients with chronic stroke are unclear. This study aims to determine the effects of rhythmic sensory stimulation on the gait of patients with chronic stroke. Twenty older adults with stroke and twenty age- and gender-matched healthy controls walked 60 m under four conditions: normal walking with no stimulation, walking with rhythmic auditory stimulation (RAS) through an earphone in the ear, walking with rhythmic somatosensory stimulation (RSS) through a haptic device on the wrist of each participant, and walking with rhythmic combined stimulation (RCS: RAS + RSS). Gait performance in the stroke group significantly improved during walking with RAS, RSS, and RCS compared to that during normal walking (p < 0.008). Gait variability significantly decreased under the RAS, RSS, and RCS conditions compared to that during normal walking (p < 0.008). Rhythmic sensory stimulation is effective in improving the gait of patients with chronic stroke, regardless of the type of rhythmic stimuli, compared to healthy controls. The effect was greater in patients with reduced mobility, assessed by the Rivermead Mobility Index (RMI).

Relationship between gait complexity and pain attention in chronic low back pain

ABSTRACT

Clinical models of chronic low back pain (cLBP) highlight the role of excessive attention to pain and kinesiophobia on the origin of disability. At the motor control level, various mechanisms are involved in the impairments observed in patients with cLBP. We aimed to assess the role of maladaptative attentional behaviors by using a complex systems approach and a visual display as a distraction during walking. Sixteen patients with cLBP with no previous surgery or significant leg pain and 16 healthy matched controls were included. Patients walked on a treadmill at preferred walking speed with and without distraction. Stride time (ST) fractal complexity was assessed using detrended fluctuation analysis. A two-way analysis of variance with repeated measures on distraction was performed on fractal exponents. We found a significant group × distraction interaction effect on fractal complexity of ST series (F(1,30) = 9.972, P = 0.004). Post hoc analysis showed that, without distraction, patients with cLBP had significantly lower ST complexity than controls, but when distracted, they regained gait complexity, recovering the level of controls. Our results suggest that excessive attention to pain causes loss of complexity and adaptability in cLBP and explain alterations of motor control with pain. Fractal analysis seems to be a promising method to explore movement variability and individual adaptability in musculoskeletal disorders.