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

Experimental dyspnoea interferes with locomotion and cognition: a randomised trial

BACKGROUND

Chronic respiratory diseases are associated with cognitive dysfunction, but whether dyspnoea by itself negatively impacts on cognition has not been demonstrated. Cortical networks engaged in subjects experiencing dyspnoea are also activated during other tasks that require cognitive input and this may provoke a negative impact through interference with each other.

METHODS

This randomised, crossover trial investigated whether experimentally-induced dyspnoea would negatively impact on locomotion and cognitive function among 40 healthy adults. Crossover conditions were unloaded breathing or loaded breathing using an inspiratory threshold load. To evaluate locomotion, participants were assessed by the Timed Up and Go (TUG) test. Cognitive function was assessed by categorical and phonemic verbal fluency tests, the Trail Making Tests (TMTs) A and B (executive function), the CODE test from the Wechsler Adult Intelligence Scale (WAIS)-IV (processing speed) and by direct and indirect digit span (working memory).

RESULTS

The mean time difference to perform the TUG test between unloaded and loaded breathing was -0.752 s (95% CI -1.012 to -0.492 s) (p<0.001). Executive function, processing speed and working memory performed better during unloaded breathing, particularly for subjects starting first with the loaded breathing condition.

CONCLUSION

Our data suggest that respiratory threshold loading to elicit dyspnoea had a major impact on locomotion and cognitive function in healthy adults.

Changes in the EEG spectral power during dual-task walking with aging and Parkinson's disease: initial findings using Event-Related Spectral Perturbation analysis

BACKGROUND

The ability to maintain adequate motor-cognitive performance under increasing task demands depends on the regulation and coordination of neural resources. Studies have shown that such resources diminish with aging and disease. EEG spectral analysis is a method that has the potential to provide insight into neural alterations affecting motor-cognitive performance. The aim of this study was to assess changes in spectral analysis during dual-task walking in aging and disease METHODS: 10 young adults, ten older adults, and ten patients with Parkinson's disease (PD) completed an auditory oddball task while standing and while walking on a treadmill. Spectral power within four frequency bandwidths, delta (< 4 Hz), theta (4-8 Hz), alpha (8-12 Hz), and beta (12-30 Hz), was calculated using Event-Related Spectral Perturbation (ERSP) analyses and compared between single task and dual task and between groups.

RESULTS

Differences in ERSP were found in all groups between the single and dual-task conditions. In response to dual-task walking, beta increased in all groups (p < 0.026), delta decreased in young adults (p = 0.03) and patients with PD (0.015) while theta increased in young adults (p = 0.028) but decreased in older adults (p = 0.02) and patients with PD (p = 0.015). Differences were seen between the young, the older adults, and the patients with PD.

CONCLUSIONS

These findings are the first to show changes in the power of different frequency bands during dual-task walking with aging and disease. These specific brain modulations may reflect deficits in readiness and allocation of attention that may be responsible for the deficits in dual-task performance.

Hip joint kinematics and segment coordination variability according to pain and structural disease severity in hip osteoarthritis

This study aimed to evaluate hip joint kinematic variability and segment coordination variability during walking according to pain and radiographic disease severity in people with hip osteoarthritis. Fifty-five participants with hip osteoarthritis had pain severity assessed during walking using an item on the Western Ontario and McMasters Universities Osteoarthritis Index (no pain = 10; mild pain = 28; moderate pain = 17). Radiographic disease severity was graded by Kellgren and Lawrence scale (KL2 = 29; KL3 = 21; KL4 = 5). Hip kinematics variability was estimated as the curve coefficient of variation. Vector coding was used to calculate coordination variability for select joint couplings. One-way analysis of variances with planned adjusted post hoc comparisons were used to compare hip kinematics variability and coordination variability of select segment couplings (pelvis sagittal vs thigh sagittal; pelvis frontal vs thigh frontal; pelvis transverse vs thigh transverse; thigh sagittal vs shank sagittal; thigh frontal vs shank sagittal; thigh transverse vs shank sagittal) according to pain and radiographic disease severity. No main effect of pain severity was observed for sagittal or transverse plane hip kinematic variability (P ≥ .266), and although there was a main effect for frontal plane hip kinematic variability (P = .035), there were no significant differences when comparing between levels of pain severity (P > .006). There was no main effect of radiographic disease severity on hip kinematic variability in the sagittal (P = .539) or frontal (P = .307) plane. No significant differences in coordination of variability of segment couplings were observed (all P ≥ .229). Movement variability as assessed in this study did not differ according to pain severity during walking or radiographic disease severity.

Walking Speed Affects Gait Coordination and Variability Among Older Adults With and Without Mobility Limitations

OBJECTIVE

To determine if poorer gait variability and gait coordination among mobility-limited older adults is related to their slower walking speed.

DESIGN

Cross-sectional analysis.

SETTING

University research laboratory.

PARTICIPANTS

Community-dwelling adults (N=69) 68 years or older with (Short Physical Performance Battery score ≤9; n=37) and without (n=32) mobility limitations.

INTERVENTIONS

Not applicable.

MAIN OUTCOME MEASURES

The variability of step length, swing time percent, and step width. Gait coordination was assessed along with the Phase Coordination Index.

RESULTS

The usual pace gait speed of those without mobility limitations was faster (1.22±0.14m/s vs 0.71±0.14m/s; P<.001) and less variable in all gait characteristics (all P<.001), with the exception of step width (P=.185), than those with limitations. When those without limitations slowed their walking pace (0.71m/s±0.14), their gait coordination became poorer (P<.001), and the variability of all gait characteristics increased (all P<.001) except for step width, which decreased (P=.002). When those without mobility limitations walked at a slow pace, they had better gait coordination (P=.008) and less variable step length (P=.014) and swing time percent (P=.036). The variability of stride time (P=.260) and step width (P=.385) were not significantly different than that of their peers with limitations.

CONCLUSIONS

Increased variability in some gait characteristics of mobility-limited older adults appears to be related to their slower walking speed. Gait coordination and the variability of step length and swing time percent may reflect intrinsic differences in mobility-limited older adults that are independent of walking speed.

Detrended fluctuation analysis of gait dynamics when entraining to music and metronomes at different tempi in persons with multiple sclerosis

In persons with multiple sclerosis (PwMS), synchronizing walking to auditory stimuli such as to music and metronomes have been shown to be feasible, and positive clinical effects have been reported on step frequency and perception of fatigue. Yet, the dynamic interaction during the process of synchronization, such as the coupling of the steps to the beat intervals in music and metronomes, and at different tempi remain unknown. Understanding these interactions are clinically relevant, as it reflects the pattern of step intervals over time, known as gait dynamics. 28 PwMS and 29 healthy controls were instructed to walk to music and metronomes at 6 tempi (0–10% in increments of 2%). Detrended fluctuation analysis was applied to calculate the fractal statistical properties of the gait time-series to quantify gait dynamics by the outcome measure alpha. The results showed no group differences, but significantly higher alpha when walking to music compared to metronomes, and when walking to both stimuli at tempi + 8, + 10% compared to lower tempi. These observations suggest that the precision and adaptation gain differ during the coupling of the steps to beats in music compared to metronomes (continuous compared to discrete auditory structures) and at different tempi (different inter-beat-intervals).

A Novel Functional Link Network Stacking Ensemble with Fractal Features for Multichannel Fall Detection

Falls are a major health concern and result in high morbidity and mortality rates in older adults with high costs to health services. Automatic fall classification and detection systems can provide early detection of falls and timely medical aid. This paper proposes a novel Random Vector Functional Link (RVFL) stacking ensemble classifier with fractal features for classification of falls. The fractal Hurst exponent is used as a representative of fractal dimensionality for capturing irregularity of accelerometer signals for falls and other activities of daily life. The generalised Hurst exponents along with wavelet transform coefficients are leveraged as input feature space for a novel stacking ensemble of RVFLs composed with an RVFL neural network meta-learner. Novel fast selection criteria are presented for base classifiers founded on the proposed diversity indicator, obtained from the overall performance values during the training phase. The proposed features and the stacking ensemble provide the highest classification accuracy of 95.71% compared with other machine learning techniques, such as Random Forest (RF), Artificial Neural Network (ANN) and Support Vector Machine. The proposed ensemble classifier is 2.3× faster than a single Decision Tree and achieves the highest speedup in training time of 317.7× and 198.56× compared with a highly optimised ANN and RF ensemble, respectively. The significant improvements in training times of the order of 100× and high accuracy demonstrate that the proposed RVFL ensemble is a prime candidate for real-time, embedded wearable device–based fall detection systems.

Initiation gait variability is higher in the morning in elderly inpatients

OBJECTIVE

Although elderly inpatients are known to experience decreased physical activity in the morning, falls occur frequently during this time. Gait variability is an evaluation of gait instability and a risk factor for falls. Gait initiation requires complex processes, and it is important to evaluate gait variability not only during steady-state gait but also during gait initiation. However, the effect of the diurnal pattern on variability in gait characteristics is still unknown. The aim of this study was to investigate the effect of the diurnal pattern on initiation and steady-state gait variability in elderly inpatients.

METHOD

Thirty-seven elderly inpatients (28 women; mean age, 79.7 ± 9.5 years) who could walk without support were sampled in this study. The quantitative measure of gait variability was evaluated using the coefficient of variation (CV) based on four consecutive stride durations determined using triaxial accelerometers. Gait characteristics were evaluated during initiation and steady-state gait and defined as initiation CV and steady-state CV, respectively. This measurement was performed at two time points, morning and daytime.

RESULTS

There was no significant difference between initiation and steady-state gait characteristics in the daytime condition. However, in the morning condition, the initiation CV was higher than the steady-state CV. Furthermore, the initiation CV was higher in the morning than during daytime (p < 0.01).

CONCLUSION

Our study revealed that the variability of initiation gait is higher in the morning. It may be important to assess the risk of falls, including initiation gait, in the morning.

Effects of a 16-week multimodal exercise program on gait performance in individuals with dementia: a multicenter randomized controlled trial

Background

There is a high prevalence of gait impairments in individuals with dementia (IWD). Gait impairments are associated with increased risk of falls, disability, and economic burden for health care systems. Only few studies have investigated the effectiveness of physical activity on gait performance in IWD, reporting promising but inconsistent results. Thus, this study aimed to investigate the effectiveness of a multimodal exercise program (MEP) on gait performance in IWD.

Methods

In this parallel-group randomized controlled trial, we enrolled 319 IWD of mild to moderate severity, living in care facilities, aged ≥ 65 years, and being able to walk at least 10 m. The control group (n = 118) received conventional treatment, whereas the intervention group (n = 201) additionally participated in a 16-week MEP specifically tailored to IWD. We examined the effects of the MEP on spatiotemporal gait parameters and dual task costs by using the gait analysis system GAITRite. Additionally, we compared characteristics between positive, non-, and negative responders, and investigated the impact of changes in underlying motor and cognitive performance in the intervention group by conducting multiple regression analyses.

Results

Two-factor analyses of variance with repeated measurements did not reveal any statistically significant time*group effects on either spatiotemporal gait parameters or dual task costs. Differences in baseline gait performance, mobility, lower limb strength, and severity of cognitive impairments were observed between positive, non-, and negative responders. Positive responders were characterized by lower motor performance compared to negative and non-responders, while non-responders showed better cognitive performance than negative responders. Changes in lower limb strength and function, mobility, executive function, attention, and working memory explained up to 39.4% of the variance of changes in gait performance.

Conclusions

The effectiveness of a standardized MEP on gait performance in IWD was limited, probably due to insufficient intensity and amount of specific walking tasks as well as the large heterogeneity of the sample. However, additional analyses revealed prerequisites of individual characteristics and impacts of changes in underlying motor and cognitive performance. Considering such factors may improve the effectiveness of a physical activity intervention among IWD.

Trial registration

DRKS00010538 (German Clinical Trial Register, date of registration: 01 June 2016, retrospectively registered, https://www.drks.de/drks_web/setLocale_EN.do).

Novel, clinically applicable method to measure step-width during the swing phase of gait

OBJECTIVE

Step-width during walking is an indicator of stability and balance in patients with neurological disorders, and development of objective tools to measure this clinically would be a great advantage. The aim of this study was to validate an in-house-developed gait analysis system (Striton), based on optical and inertial sensors and a novel method for stride detection, for measuring step-width during the swing phase of gait and temporal parameters.

APPROACH

The step-width and stride-time measurements were validated in an experimental setup, against a 3D motion capture system and on an instrumented walkway. Further, test-retest and day-to-day variability were evaluated, and gait parameters were collected from 87 elderly persons (EP) and four individuals with idiopathic normal pressure hydrocephalus (iNPH) before/after surgery.

MAIN RESULTS

Accuracy of the step-width measurement was high: in the experimental setup mean error was 0.08 ± 0.25 cm (R = 1.00) and against the 3D motion capture system 0.04 ± 1.12 cm (R = 0.98). Test-retest and day-to-day measurements were equal within ±0.5 cm. Mean difference in stride time was -0.003 ± 0.008 s between Striton and the instrumented walkway. The Striton system was successfully applied in the clinical setting on individuals with iNPH, which had larger step-width (6.88 cm, n = 4) compared to EP (5.22 cm, n = 87).

SIGNIFICANCE

We conclude that Striton is a valid, reliable and wearable system for quantitative assessment of step-width and temporal parameters during gait. Initial measurements indicate that the newly defined step-width parameter differs between EP and patients with iNPH and before/after surgery. Thus, there is potential for clinical applicability in patients with reduced gait stability.

Fractal auditory stimulation has greater benefit for people with Parkinson's disease showing more random gait pattern

BACKGROUND

Healthy gait dynamics are characterized by the presence of fractal, persistent stride-to-stride variations, which become more random with Parkinson's disease (PD). Rhythmic auditory stimulation with fractal beat-to-beat variations can change gait dynamics in people with PD toward more persistence.

RESEARCH QUESTION

How does gait in people with PD change when synchronizing steps with fractal melodic metronomes with different step-to-beat ratios, and which stimulus do they prefer?

METHODS

In this cross-sectional study, 15 people with PD and 15 healthy older adults walked over-ground in three conditions: self-paced, paced by a fractal auditory stimulus with a 1:1 step-to-beat ratio ('metronome'), and fractal auditory stimulus with a 1:2 step-to-beat ratio ('music'). Gait dynamics were recorded with instrumented insoles, and detrended fluctuation analysis (DFA) was applied to the series of stride time intervals. Stimuli preference was assessed using Likert-like scales and open-ended questions. ANOVAs were used to compare mean, coefficient of variation, α-DFA, and the responses from the continuous Likert scales. Pearson correlations were used to assess the relationship between 'music' and 'metronome' enjoyment or difficulty with gait outcomes, and to determine the association between baseline α-DFA and changes due to the stimuli.

RESULTS

Our major findings are that (i) stride-to-stride variations were more persistent with the 'metronome' compared to baseline for both groups, (ii) the effect was greater for people with lower α-DFA at baseline (i.e., more random stride-to-stride variations), and (iii) both groups found the 'metronome' less difficult to synchronize with.

SIGNIFICANCE

This study showed that people with PD and healthy older adults walk with higher statistical persistence in their stride-to-stride variations when instructed to synchronize their steps with a fractal stimulus. Participants with lower persistence at baseline benefited the most from the fractal 'metronome', highlighting the importance to develop patient-centered tests and interventions.

Assessing the Temporal Organization of Walking Variability: A Systematic Review and Consensus Guidelines on Detrended Fluctuation Analysis

Human physiological signals are inherently rhythmic and have a hallmark feature in that even distant intrasignal measurements are related to each other. This relationship is termed long-range correlation and has been recognized as an indicator of the optimal state of the observed physiological systems, among which the locomotor system. Loss of long-range correlations has been found as a result of aging as well as disease, which can be evaluated with detrended fluctuation analysis (DFA). Recently, DFA and the scaling exponent α have been employed for understanding the degeneration of temporal regulation of human walking biorhythms in, for example, Parkinson disease (PD). However, heterogeneous evidence on scaling exponent α values reported in the literature across different population groups has put into question what constitutes a healthy physiological pattern. Therefore, the purpose of this systematic review was to investigate the functional thresholds of scaling exponent α in young vs. older adults, as well as between patients with PD and age-matched asymptomatic controls. Aging and PD exhibited a negative effect size (i.e., led to decreased long-range correlations) of -0.20 and -0.53, respectively. Our meta-analysis based on 14 studies provides evidence that a mean scaling exponent α threshold of 0.86 [2 standard error (0.76, 0.96)] is able to optimally discriminate temporal organization of stride interval between young and old, whereas 0.82 (0.72, 0.92) differentiates patients with PD and age-matched asymptomatic controls. The optimal thresholds presented in this review together with the consensus guidelines for using DFA might allow a more sensitive and reliable application of this metric for understanding human walking physiology than has been achieved to date.

Impaired Sensorimotor Processing During Complex Gait Precedes Behavioral Changes in Middle-aged Adults

Gait impairment during complex walking in older adults is thought to result from a progressive failure to compensate for deteriorating peripheral inputs by central neural processes. It is the primary hypothesis of this article that failure of higher cerebral adaptations may already be present in middle-aged adults who do not present observable gait impairments. We, therefore, compared metabolic brain activity during steering of gait (ie, complex locomotion) and straight walking (ie, simple locomotion) in young and middle-aged individuals. Cerebral distribution of [18F]-fluorodeoxyglucose, a marker of brain synaptic activity, was assessed during over ground straight walking and steering of gait using positron emission tomography in seven young adults (aged 24 ± 3) and seven middle-aged adults (aged 59 ± 3). Brain regions involved in steering of gait (posterior parietal cortex, superior frontal gyrus, and cerebellum) are retained in middle age. However, despite similar walking performance, there are age-related differences in the distribution of [18F]-fluorodeoxyglucose during steering: middle-aged adults have (i) increased activation of precentral and fusiform gyri, (ii) reduced deactivation of multisensory cortices (inferior frontal, postcentral, and fusiform gyri), and (iii) reduced activation of the middle frontal gyrus and cuneus. Our results suggest that preclinical decline in central sensorimotor processing in middle age is observable during complex walking.

Assessment of diurnal variation of stride time variability during continuous, overground walking in healthy young adults

BACKGROUND

There is emerging evidence that gait variability outcomes provide unique insights regarding the status of an individual's locomotor control system; however, there is currently limited evidence on the within-day reliability of stride time variability (STV) outcomes, or whether they demonstrate diurnal variation, when measured during continuous, overground walking in healthy young adults.

RESEARCH QUESTIONS

1) Are STV outcomes measured in the morning and afternoon during continuous, overground walking significantly different in healthy young adults? 2) What is the within-day reliability of STV outcomes measured during continuous, overground walking in healthy young adults?.

METHODS

Thirty-one healthy young adults (20.8 ± 3.7 years) completed two 10-minute continuous, overground walking trials on the same day (9:00-11:00am and 3:00-5:00pm) at their preferred walking speed. Data from a waist-mounted tri-axial accelerometer were used to determine the series of consecutive stride times for each trial.

RESULTS

There were no significant differences between sessions for average walking speed, average stride time, or STV. The within-day reliability was excellent for average walking speed and stride time, and generally poor to fair for STV.

SIGNIFICANCE

Healthy young adults do not appear to demonstrate diurnal variation in STV outcomes during continuous, overground walking; however, the development of a protocol to improve their reliability, as well as the establishment of normative ranges for such outcomes, would be beneficial to improve their application and interpretation in research and clinical settings.

Signatures of knee osteoarthritis in women in the temporal and fractal dynamics of human gait

BACKGROUND

Osteoarthritis of the knee is characterized by progressive cartilage deterioration causing pain and function loss. Symptoms develop late with limited disease-modifying opportunities. Osteoarthritis is a major cause of immobility, with a higher prevalence above 60 years. This age-related increase in prevalence is further amplified by the female gender. Imaging and biochemical analyses for detection of osteoarthritis of the knee are expensive and labor-intensive. Continuous movement tracking could aid in detecting onset and/or worsening of symptoms.

METHODS

We used portable technology to investigate kinematic differences in female patients with knee osteoarthritis, weight-matched healthy female volunteers and obese female patients with osteoarthritis of the knee. Knee osteoarthritis was established radiographically and corroborated using magnetic resonance imaging.

FINDINGS

The total amount, type and level of activity did not differ significantly between groups. The temporal activity pattern during the day was however significantly different with a bimodal signature in healthy volunteers only. Sequence analyses revealed more time to recuperate after dynamic activity in both patient groups. Analysis of walking bouts revealed significant differences in stride interval dynamics, indicative of gait naturalness, only in healthy volunteers. Temporal activity, sequence and walking patterns were independent of body weight.

INTERPRETATION

We thus provide for the first-time evidence of temporal specific kinematic signatures in amount and quality of movement also in stride interval dynamics between people with and without osteoarthritis of the knee independent of body weight. These findings could allow early and non-intrusive diagnosis of osteoarthritis enabling concordant treatment.

Digital natives and dual task: Handling it but not immune against cognitive-locomotor interferences

Digital natives developed in an electronic dual tasking world. This paper addresses two questions. Do digital natives respond differently under a cognitive load realized during a locomotor task in a dual-tasking paradigm and how does this address the concept of safety? We investigate the interplay between cognitive (talking and solving Raven’s matrices) and locomotor (walking on a treadmill) tasks in a sample of 17 graduate level participants. The costs of dual-tasking on gait were assessed by studying changes in stride interval time and its variability at long-range. A safety index was designed and computed from total relative change between the variability indices in the single walking and dual-task conditions. As expected, results indicate high Raven’s scores with gait changes found between the dual task conditions compared to the single walking task. Greater changes are observed in the talking condition compared to solving Raven’s matrices, resulting in high safety index values observed in 5 participants. We conclude that, although digital natives are efficient in performing the dual tasks when they are not emotional-based, modification of gait are observable. Due to the variation within participants and the observation of high safety index values in several of them, individuals that responded poorly to low cognitive loads should be encouraged to not perform dual task when executing a primate task of safety to themselves or others.

An investigation of the spatio-temporal parameters of gait and margins of stability throughout adulthood

Age-related changes in the way of walking may induce changes in dynamic stability. Therefore, the relationship between age, spatio-temporal characteristics and margins of stability was examined. One hundred and five healthy adults aged between 20 and 89 years old were analysed on spatio-temporal characteristics and margins of stability using three-dimensional motion analysis. Subjects walked barefoot over a 12-m-long walkway at their preferred walking speed. Covariance among gait characteristics was reduced using a factor analysis, identifying domains of gait. The influence of age, gender, body mass index (BMI) and leg length on domains of gait and margins of stability was investigated using linear mixed models. A stepwise linear regression identified domains of gait predicting the variance in margins of stability. Four domains of gait explaining 74.17% of the variance were identified. Age had a significant influence on the medio-lateral margin of stability and the 'variability', 'pace' and 'base of support' domain. BMI significantly influenced the medio-lateral margin of stability; gender and leg length had no influence on either of the margins of stability. The 'base of support' domain predicted 26% of the variance in the medio-lateral margin of stability. When considering the margins of stability, especially when comparing multiple groups, age, BMI and spatio-temporal parameters should be taken into account.

Regional Associations of Cortical Thickness With Gait Variability—The Tasmanian Study of Cognition and Gait

Background

Gait variability is a marker of cognitive decline. However, there is limited understanding of the cortical regions associated with gait variability. We examined associations between regional cortical thickness and gait variability in a population-based sample of older people without dementia.

Method

Participants (n = 350, mean age 71.9 ± 7.1) were randomly selected from the electoral roll. Variability in step time, step length, step width, and double support time (DST) were calculated as the standard deviation of each measure, obtained from the GAITRite walkway. Magnetic resonance imaging (MRI) scans were processed through FreeSurfer to obtain cortical thickness of 68 regions. Bayesian regression was used to determine regional associations of mean cortical thickness and thickness ratio (regional thickness/overall mean thickness) with gait variability.

Results

Smaller global cortical thickness was only associated with greater step width and step time variability. Smaller mean thickness in widespread regions important for sensory, cognitive, and motor functions were associated with greater step width and step time variability. In contrast, smaller thickness in a few frontal and temporal regions were associated with DST variability and the right cuneus was associated with step length variability. Smaller thickness ratio in frontal and temporal regions important for motor planning, execution, and sensory function and greater thickness ratio in the anterior cingulate was associated with greater variability in all measures.

Conclusions

Examining individual cortical regions is important in understanding the relationship between gray matter and gait variability. Cortical thickness ratio highlights that smaller regional thickness relative to global thickness may be important for the consistency of gait.

Sensor-based characterization of daily walking: a new paradigm in pre-frailty/frailty assessment

BACKGROUND

Frailty is a highly recognized geriatric syndrome resulting in decline in reserve across multiple physiological systems. Impaired physical function is one of the major indicators of frailty. The goal of this study was to evaluate an algorithm that discriminates between frailty groups (non-frail and pre-frail/frail) based on gait performance parameters derived from unsupervised daily physical activity (DPA).

METHODS

DPA was acquired for 48 h from older adults (≥65 years) using a tri-axial accelerometer motion-sensor. Continuous bouts of walking for 20s, 30s, 40s, 50s and 60s without pauses were identified from acceleration data. These were then used to extract qualitative measures (gait variability, gait asymmetry, and gait irregularity) and quantitative measures (total continuous walking duration and maximum number of continuous steps) to characterize gait performance. Association between frailty and gait performance parameters was assessed using multinomial logistic models with frailty as the dependent variable, and gait performance parameters along with demographic parameters as independent variables.

RESULTS

One hundred twenty-six older adults (44 non-frail, 60 pre-frail, and 22 frail, based on the Fried index) were recruited. Step- and stride-times, frequency domain gait variability, and continuous walking quantitative measures were significantly different between non-frail and pre-frail/frail groups (p < 0.05). Among the five different durations (20s, 30s, 40s, 50s and 60s), gait performance parameters extracted from 60s continuous walks provided the best frailty assessment results. Using the 60s gait performance parameters in the logistic model, pre-frail/frail group (vs. non-frail) was identified with 76.8% sensitivity and 80% specificity.

DISCUSSION

Everyday walking characteristics were found to be associated with frailty. Along with quantitative measures of physical activity, qualitative measures are critical elements representing the early stages of frailty. In-home gait assessment offers an opportunity to screen for and monitor frailty.

TRIAL REGISTRATION

The clinical trial was retrospectively registered on June 18th, 2013 with ClinicalTrials.gov, identifier NCT01880229.

Wearable Inertial Sensors to Assess Gait during the 6-Minute Walk Test: A Systematic Review

Wearable sensors are becoming increasingly popular for complementing classical clinical assessments of gait deficits. The aim of this review is to examine the existing knowledge by systematically reviewing a large number of papers focusing on the use of wearable inertial sensors for the assessment of gait during the 6-minute walk test (6MWT), a widely recognized, simple, non-invasive, low-cost and reproducible exercise test. After a systematic search on PubMed and Scopus databases, two raters evaluated the quality of 28 full-text articles. Then, the available knowledge was summarized regarding study design, subjects enrolled (number of patients and pathological condition, if any, age, male/female ratio), sensor characteristics (type, number, sampling frequency, range) and body placement, 6MWT protocol and extracted parameters. Results were critically discussed to suggest future directions for the use of inertial sensor devices in the clinics.

Differences in reproducibility of gait variability and fractal dynamics according to walking duration

BACKGROUND

Gait variability and fractal dynamics may be affected by the walking duration.

OBJECTIVE

The purpose of this study is to examine the reproducibility of stride time while walking on a self-paced treadmill.

METHODS

Fifteen young and healthy subjects walked on the treadmill for 10 minutes. Three to eight minutes duration of the data were used to compare the trial-to-trial and day-to-day reproducibility of the average, variability, and fractal dynamics of stride time.

RESULTS

The results show that all variables had high trial-to-trial reproducibility. In the day-to-day results, the average walking speed and mean stride time showed reproducibility without regard for duration, but the variability and gait fractal dynamics showed differences in reproducibility according to duration. The variability and fractal dynamics showed better reproducibility in less than 5 minutes and over time, respectively. However, both variables generally showed improved reproducibility when average data from two to three rounds were used.

CONCLUSION

Based on the results of this study, it is proposed that variability should be examined using data of 5 min or less, and fractal dynamics should be examined using 5 min or more of repeated data when performing walking tests from a gait dynamics perspective.

Estimation of Stride Time Variability in Unobtrusive Long-Term Monitoring Using Inertial Measurement Sensors

Stride time variability is an important indicator for the assessment of gait stability. An accurate extraction of the stride intervals is essential for determining stride time variability. Peak detection is a commonly used method for gait segmentation and stride time estimation. Standard peak detection algorithms often fail due to additional movement components and measurement noise. A novel algorithm for robust peak detection in inertial sensor signals was proposed in a previous contribution. In this work, we present a novel approach for estimation of stride time variability based on the formerly proposed peak detection algorithm applied to an unobtrusive sensor setup for motion monitoring. The unobtrusive sensor setup includes a wrist sensor, a pocket or belt sensor, and a necklace sensor, all equipped with both accelerometer and gyroscope. The goal of this work is to implement a generalized approach for accurate and robust stride interval determining algorithm for different sensor locations. Therefore, treadmill and level ground walking experiments were conducted with ten healthy subjects at increasing walking speeds and an age-simulating suit. With the proposed algorithm, we achieved a RMSE of 0.07 s for the stride interval estimation during treadmill walking experiments. The results give promising indications that detection of variation of stride time variability is possible using the proposed unobtrusive sensor setup.

Gait Speed Characteristics and Their Spatiotemporal Determinants in Nursing Home Residents: A Cross-Sectional Study

BACKGROUND AND PURPOSE

Low and slowing gait speeds among nursing home residents are linked to a higher risk of disability, cognitive impairment, falls, and mortality. A better understanding of the spatiotemporal parameters of gait that influence declining mobility could lead to effective rehabilitation and preventative intervention. The aims of this study were to objectively quantify the spatiotemporal characteristics of gait in the nursing home setting and define the relationship between these parameters and gait speed.

METHODS

One hundred nursing home residents were enrolled into the study and completed 3 habitual gait speed trials over a distance of 3.66 m. Trials were performed using an instrumented gait analysis. The manner in which the spatiotemporal parameters predicted gait speed was examined by univariate and multivariable regression modeling.

RESULTS

The nursing home residents had a habitual mean (SD) gait speed of 0.63 (0.19) m/s, a stride length of 0.83 (0.15) m, a support base of 0.15 (0.06) m, and step time of 0.66 (0.12) seconds. Multivariable linear regression revealed stride length, support base, and step time predicted gait speed (R = 0.89, P < .05). Step time had the greatest influence on gait speed, with each 0.1-second decrease in step time resulting in a 0.09 m/s (95% confidence interval, 0.08-0.10) increase in habitual gait speed.

CONCLUSIONS

This study revealed step time, stride length, and support base are the strongest predictors of gait speed among nursing home residents. Future research should concentrate on developing and evaluating intervention programs that were specifically designed to focus on the strong predictors of gait speed in nursing home residents. We would also suggest that routine assessments of gait speed, and if possible their spatiotemporal characteristics, be done on all nursing home residents in an attempt to identify residents with low or slowing gait speed.

Perturbation Treadmill Training Improves Clinical Characteristics of Gait and Balance in Parkinson's Disease

BACKGROUND

Impaired gait and postural stability are cardinal motor symptoms in Parkinson's disease (PD). Treadmill training improves gait characteristics in PD.

OBJECTIVE

This study investigates if postural perturbations during treadmill training improve motor performance and particularly gait and postural stability in PD.

METHODS

This work presents secondary outcome measures of a pilot randomized controlled trial. PD patients (n = 43) recruited at the University Hospital Erlangen were randomly allocated to the experimental (perturbation treadmill training, PTT, n = 21) or control group (conventional treadmill training, CTT, n = 22). Outcome measures were collected at baseline, after 8 weeks of intervention, and 3 months follow-up. Motor impairment was assessed by the Unified Parkinson Disease Rating Scale part-III (UPDRS-III), Postural Instability and Gait Difficulty score (PIGD), and subitems 'Gait' and 'Postural stability' by an observer blinded to the randomization. Intervention effects were additionally compared to progression rates of a matched PD cohort (n = 20) receiving best medical treatment (BMT).

RESULTS

Treadmill training significantly improved UPDRS-III motor symptoms in both groups with larger effect sizes for PTT (-38%) compared to CTT (-20%). In the PTT group solely, PIGD -34%, and items 'Gait' -50%, and 'Postural stability' -40% improved significantly in comparison to CTT (PIGD -24%, 'Gait' -22%, 'Postural stability' -33%). Positive effects persisted in PTT after 3 months and appeared to be beneficial compared to BMT.

CONCLUSIONS

Eight weeks of PTT showed superior improvements of motor symptoms, particularly gait and postural stability. Sustainable effects indicate that PTT may be an additive therapy option for gait and balance deficits in PD.

Motor style at rest and during locomotion in human

Humans exhibit various motor styles that reflect their intra- and interindividual variability when implementing sensorimotor transformations. This opens important questions, such as, At what point should they be readjusted to maintain optimal motor control? Do changes in motor style reveal the onset of a pathological process and can these changes help rehabilitation and recovery? To further investigate the concept of motor style, tests were carried out to quantify posture at rest and motor control in 18 healthy subjects under four conditions: walking at three velocities (comfortable walking, walking at 4 km/h, and race walking) and running at maximum velocity. The results suggest that motor control can be conveniently decomposed into a static component (a stable configuration of the head and column with respect to the gravitational vertical) and dynamic components (head, trunk, and limb movements) in humans, as in quadrupeds, and both at rest and during locomotion. These skeletal configurations provide static markers to quantify the motor style of individuals because they exhibit large variability among subjects. Also, using four measurements (jerk, root mean square, sample entropy, and the two-thirds power law), it was shown that the dynamics were variable at both intra- and interindividual levels during locomotion. Variability increased following a head-to -toe gradient. These findings led us to select dynamic markers that could define, together with static markers, the motor style of a subject. Finally, our results support the view that postural and motor control are subserved by different neuronal networks in frontal, sagittal, and transversal planes.NEW & NOTEWORTHY During human locomotion, motor control can be conveniently decomposed into a static and dynamic components. Variable dynamics were observed at both the intra- and interindividual levels during locomotion. Variability increased following a head-to-toe gradient. Finally, our results support the view that postural and motor control are subserved by different neuronal networks in the frontal, sagittal, and transversal planes.

Hardware/Software Co-design of Fractal Features based Fall Detection System

Falls are a leading cause of death in older adults and result in high levels of mortality, morbidity and immobility. Fall Detection Systems (FDS) are imperative for timely medical aid and have been known to reduce death rate by 80%. We propose a novel wearable sensor FDS which exploits fractal dynamics of fall accelerometer signals. Fractal dynamics can be used as an irregularity measure of signals and our work shows that it is a key discriminant for classification of falls from other activities of life. We design, implement and evaluate a hardware feature accelerator for computation of fractal features through multi-level wavelet transform on a reconfigurable embedded System on Chip, Zynq device for evaluating wearable accelerometer sensors. The proposed FDS utilises a hardware/software co-design approach with hardware accelerator for fractal features and software implementation of Linear Discriminant Analysis on an embedded ARM core for high accuracy and energy efficiency. The proposed system achieves 99.38% fall detection accuracy, 7.3× speed-up and 6.53× improvements in power consumption, compared to the software only execution with an overall performance per Watt advantage of 47.6×, while consuming low reconfigurable resources at 28.67%.

How Age, Cognitive Function and Gender Affect Bimanual Force Control

Coordinated bimanual control depends on information processing in different intra- and interhemispheric networks that differ with respect to task symmetry and laterality of execution. Aging and age-related cognitive impairments, but also sex can have detrimental effects on connectivity of these networks. We therefore expected effects of age, cognitive function and sex on bimanual force coordination. We furthermore expected these effects to depend on the characteristics of the task (i.e., difficulty and symmetry). 162 right handed participants (19 younger adults [YA], 21–30 years, 9 females; 52 cognitively healthy older adults [HOA], 80–91 years, 32 females; and 91 older adults with mild cognitive impairments [MCI] 80–91 years, 37 females) performed isometric bimanual force control tasks that required following constant or alternating (cyclic sine-wave) targets and varied in symmetry, i.e., (i) constant symmetric, asymmetric [with constant left and alternating right (ii) or vice versa (iii)], (iv) alternating in- and (v) alternating antiphase (both hands alternating with 0° or 180° relative phase, respectively). We analyzed general performance (time on target), bimanual coordination as coupling between hands (linear correlation coefficient) and structure of variability (i.e., complexity measured through detrended fluctuation analysis). Performance and coupling strongly depended on task symmetry and executing hand, with better performance in symmetric tasks and in asymmetric tasks when the left hand produced a constant and the right hand an alternating force. HOA and MCI, compared to YA, showed poorer performance (time on target) and reduced coupling in in- and antiphase tasks. Furthermore, both groups of OA displayed less complex structure in alternating force production tasks, a marker of reduced control. In addition, we found strong sex effects with females displaying reduced coupling during in- and antiphase coordination and less complex variably structure in constant force production. Results of this study revealed strong effects of age, but also sex on bimanual force control. Effects depended strongly on task symmetry and executing hand, possibly due to different requirements in interhemispheric information processing. So far, we found no clear relationship between behavioral markers of bimanual force control and age-related cognitive decline (compared to healthy aging), making further investigation necessary.

Co-actors Exhibit Similarity in Their Structure of Behavioural Variation That Remains Stable Across Range of Naturalistic Activities

Human behaviour, along with any natural/biological behaviour, has varying degrees of intrinsic 'noise' or variability. Many studies have shown that the structure or patterning of this variability is sensitive to changes in task and constraint. Furthermore, two or more humans interacting together often begin to exhibit similar structures of behavioural variability (i.e., the patterning of their behavioural fluctuations becomes aligned or matched) independent of any moment-to-moment synchronization (termed complexity matching). However, much of the previous work has focused on a subset of simple or contrived behaviours within the context of highly controlled laboratory tasks. In the current study, individuals and pairs performed five self-paced (unsupervised), semi-structured activities around a university campus. Empatica E4 wristbands and iPhones were used to record the participants' behavioural activity via accelerometers and GPS. The results revealed that the structure of variability in naturalistic human behaviour co-varies with the task-goal constraints, and that the patterning of the behavioural fluctuations exhibited by co-acting individuals does become aligned during the performance of everyday activities. The results also revealed that the degree of complexity matching that occurred between pairs remained invariant across activity type, indicating that this measure could be employed as a robust, task-independent index of interpersonal behaviour.

Consensus on Shared Measures of Mobility and Cognition: From the Canadian Consortium on Neurodegeneration in Aging (CCNA)

Background

A new paradigm is emerging in which mobility and cognitive impairments, previously studied, diagnosed, and managed separately in older adults, are in fact regulated by shared brain resources. Deterioration in these shared brain mechanisms by normal aging and neurodegeneration increases the risk of developing dementia, falls, and fractures. This new paradigm requires an integrated approach to measuring both domains. We aim to identify a complementary battery of existing tests of mobility and cognition in community-dwelling older adults that enable assessment of motor-cognitive interactions.

Methods

Experts on mobility and cognition in aging participated in a semistructured consensus based on the Delphi process. After performing a scoping review to select candidate tests, multiple rounds of consultations provided structured feedback on tests that captured shared characteristics of mobility and cognition. These tests needed to be sensitive to changes in both mobility and cognition, applicable across research studies and clinics, sensitive to interventions, feasible to perform in older adults, been previously validated, and have minimal ceiling/floor effects.

Results

From 17 tests appraised, 10 tests fulfilled prespecified criteria and were selected as part of the “Core-battery” of tests. The expert panel also recommended a “Minimum-battery” of tests that included gait speed, dual-task gait speed, the Montreal Cognitive Assessment and Trail Making Test A&B.

Conclusions

A standardized assessment battery that captures shared characteristics of mobility and cognition seen in aging and neurodegeneration may increase comparability across research studies, detection of subtle or common reversible factors, and accelerate research progress in dementia, falls, and aging-related disabilities.

Auditory and Visual External Cues Have Different Effects on Spatial but Similar Effects on Temporal Measures of Gait Variability

Walking synchronized to external cues is a common practice in clinical settings. Several research studies showed that this popular gait rehabilitation tool alters gait variability. There is also recent evidence which suggests that alterations in the temporal structure of the external cues could restore gait variability at healthy levels. It is unknown, however, if such alterations produce similar effects if the cueing modalities used are different; visual or auditory. The modality could affect gait variability differentially, since there is evidence that auditory cues mostly act in the temporal domain of gait, while visual cues act in the spatial domain of gait. This study investigated how synchronizing steps with visual and auditory cues that are presented with different temporal structures could affect gait variability during treadmill walking. Three different temporal structured stimuli were used, invariant, fractal and random, in both modalities. Stride times, length and speed were determined, and their fractal scaling (an indicator of complexity) and coefficient of variation (CV) were calculated. No differences were observed in the CV, regardless of the cueing modality and the temporal structure of the stimuli. In terms of the stride time's fractal scaling, we observed that the fractal stimulus induced higher values compared to random and invariant stimuli. The same was also observed in stride length, but only for the visual cueing modality. No differences were observed for stride speed. The selection of the cueing modality seems to be an important feature of gait rehabilitation. Visual cues are possibly a better choice due to the dependency on vision during walking. This is particularly evident during treadmill walking, a common practice in a clinical setting. Because of the treadmill effect on the temporal domain of gait, the use of auditory cues can be minimal, compared to visual cues.

Gait variability as digital biomarker of disease severity in Huntington's disease

BACKGROUND

Impaired gait plays an important role for quality of life in patients with Huntington's disease (HD). Measuring objective gait parameters in HD might provide an unbiased assessment of motor deficits in order to determine potential beneficial effects of future treatments.

OBJECTIVE

To objectively identify characteristic features of gait in HD patients using sensor-based gait analysis. Particularly, gait parameters were correlated to the Unified Huntington's Disease Rating Scale, total motor score (TMS), and total functional capacity (TFC).

METHODS

Patients with manifest HD at two German sites (n = 43) were included and clinically assessed during their annual ENROLL-HD visit. In addition, patients with HD and a cohort of age- and gender-matched controls performed a defined gait test (4 × 10 m walk). Gait patterns were recorded by inertial sensors attached to both shoes. Machine learning algorithms were applied to calculate spatio-temporal gait parameters and gait variability expressed as coefficient of variance (CV).

RESULTS

Stride length (- 15%) and gait velocity (- 19%) were reduced, while stride (+ 7%) and stance time (+ 2%) were increased in patients with HD. However, parameters reflecting gait variability were substantially altered in HD patients (+ 17% stride length CV up to + 41% stride time CV with largest effect size) and showed strong correlations to TMS and TFC (0.416 ≤ r_Sp ≤ 0.690). Objective gait variability parameters correlated with disease stage based upon TFC.

CONCLUSIONS

Sensor-based gait variability parameters were identified as clinically most relevant digital biomarker for gait impairment in HD. Altered gait variability represents characteristic irregularity of gait in HD and reflects disease severity.

Complexity-based decoding of brain-skin relation in response to olfactory stimuli

BACKGROUND AND OBJECTIVE

Human body is covered with skin in different parts. In fact, skin reacts to different changes around human. For instance, when the surrounding temperature changes, human skin will react differently. It is known that the activity of skin is regulated by human brain. In this research, for the first time we investigate the relation between the activities of human skin and brain by mathematical analysis of Galvanic Skin Response (GSR) and Electroencephalography (EEG) signals.

METHOD

For this purpose, we employ fractal theory and analyze the variations of fractal dimension of GSR and EEG signals when subjects are exposed to different olfactory stimuli in the form of pleasant odors.

RESULTS

Based on the obtained results, the complexity of GSR signal changes with the complexity of EEG signal in case of different stimuli, where by increasing the molecular complexity of olfactory stimuli, the complexity of EEG and GSR signals increases. The results of statistical analysis showed the significant effect of stimulation on variations of complexity of GSR signal. In addition, based on effect size analysis, fourth odor with greatest molecular complexity had the greatest effect on variations of complexity of EEG and GSR signals.

CONCLUSION

Therefore, it can be said that human skin reaction changes with the variations in the activity of human brain. The result of analysis in this research can be further used to make a model between the activities of human skin and brain that will enable us to predict skin reaction to different stimuli.

Gait asymmetry and variability in older adults during long-distance walking: Implications for gait instability

BACKGROUND

Physical exercise, such as walking, is imperative to older adults. However, long-distance walking may increase walking instability which exposes them to some fall risks.

OBJECTIVE

To evaluate the influence of long-distance walking on gait asymmetry and variability of older adults.

METHOD

Sixteen physically active older adults were instructed to walk on a treadmill for a total of 60 min. Gait experiments were conducted over-ground at the baseline (before treadmill-walk), after first 30 min (30-min) and second 30 min (60-min) of the walk. In addition to spatiotemporal parameters, median absolute deviation of the joint angular velocity was measured to evaluate gait asymmetry and gait variability.

FINDINGS

There were significant differences in the overall asymmetry index among the three time instances (Partial η² = 0.77, p < .05), predominantly contributed by the ankle (Partial η² = 0.31, p < .017). Long-distance walking significantly increased the average and maximum median absolute deviation of the ankle at both sides (W ≥ 0.19, p < .05), and knee at the non-dominant side (W = 0.44, p < .05).

INTERPRETATION

At 30-min, the older adults demonstrated a significantly higher asymmetry and variability at the ankle, which implied higher instability. Continue walking for an additional 30 min (60-min) further increased variability of the non-dominant limb at the knee joint. Walking for 30 min or more could significantly reduce walking stability.

Phase resetting and intermittent control at the edge of stability in a simple biped model generates 1/f-like gait cycle variability

The 1/f-like gait cycle variability, characterized by temporal changes in stride-time intervals during steady-state human walking, is a well-documented gait characteristic. Such gait fractality is apparent in healthy young adults, but tends to disappear in the elderly and patients with neurological diseases. However, mechanisms that give rise to gait fractality have yet to be fully clarified. We aimed to provide novel insights into neuro-mechanical mechanisms of gait fractality, based on a numerical simulation model of biped walking. A previously developed heel-toe footed, seven-rigid-link biped model with human-like body parameters in the sagittal plane was implemented and expanded. It has been shown that the gait model, stabilized rigidly by means of impedance control with large values of proportional (P) and derivative (D) gains for a linear feedback controller, is destabilized only in a low-dimensional eigenspace, as P and D decrease below and even far below critical values. Such low-dimensional linear instability can be compensated by impulsive, phase-dependent actions of nonlinear controllers (phase resetting and intermittent controllers), leading to the flexible walking with joint impedance in the model being as small as that in humans. Here, we added white noise to the model to examine P-value-dependent stochastic dynamics of the model for small D-values. The simulation results demonstrated that introduction of the nonlinear controllers in the model determined the fractal features of gait for a wide range of the P-values, provided that the model operates near the edge of stability. In other words, neither the model stabilized only by pure impedance control even at the edge of linear stability, nor the model stabilized by specific nonlinear controllers, but with P-values far inside the stability region, could induce gait fractality. Although only limited types of controllers were examined, we suggest that the impulsive nonlinear controllers and criticality could be major mechanisms for the genesis of gait fractality.

Gait Abnormality Detection in People with Cerebral Palsy Using an Uncertainty-Based State-Space Model

Assessment and quantification of feature uncertainty in modeling gait pattern is crucial in clinical decision making. Automatic diagnostic systems for Cerebral Palsy gait often ignored the uncertainty factor while recognizing the gait pattern. In addition, they also suffer from limited clinical interpretability. This study establishes a low-cost data acquisition set up and proposes a state-space model where the temporal evolution of gait pattern was recognized by analyzing the feature uncertainty using Dempster-Shafer theory of evidence. An attempt was also made to quantify the degree of abnormality by proposing gait deviation indexes. Results indicate that our proposed model outperformed state-of-the-art with an overall \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$87.5\%$$\end{document} of detection accuracy (sensitivity \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$80.00\%$$\end{document}, and specificity \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$100\%$$\end{document}). In a gait cycle of a Cerebral Palsy patient, first double limb support and left single limb support were observed to be affected mainly. Incorporation of feature uncertainty in quantifying the degree of abnormality is demonstrated to be promising. Larger value of feature uncertainty was observed for the patients having higher degree of abnormality. Sub-phase wise assessment of gait pattern improves the interpretability of the results which is crucial in clinical decision making.

Increased gait variability during robot-assisted walking is accompanied by increased sensorimotor brain activity in healthy people

BACKGROUND

Gait disorders are major symptoms of neurological diseases affecting the quality of life. Interventions that restore walking and allow patients to maintain safe and independent mobility are essential. Robot-assisted gait training (RAGT) proved to be a promising treatment for restoring and improving the ability to walk. Due to heterogenuous study designs and fragmentary knowlegde about the neural correlates associated with RAGT and the relation to motor recovery, guidelines for an individually optimized therapy can hardly be derived. To optimize robotic rehabilitation, it is crucial to understand how robotic assistance affect locomotor control and its underlying brain activity. Thus, this study aimed to investigate the effects of robotic assistance (RA) during treadmill walking (TW) on cortical activity and the relationship between RA-related changes of cortical activity and biomechanical gait characteristics.

METHODS

Twelve healthy, right-handed volunteers (9 females; M = 25 ± 4 years) performed unassisted walking (UAW) and robot-assisted walking (RAW) trials on a treadmill, at 2.8 km/h, in a randomized, within-subject design. Ground reaction forces (GRFs) provided information regarding the individual gait patterns, while brain activity was examined by measuring cerebral hemodynamic changes in brain regions associated with the cortical locomotor network, including the sensorimotor cortex (SMC), premotor cortex (PMC) and supplementary motor area (SMA), using functional near-infrared spectroscopy (fNIRS).

RESULTS

A statistically significant increase in brain activity was observed in the SMC compared with the PMC and SMA (p < 0.05), and a classical double bump in the vertical GRF was observed during both UAW and RAW throughout the stance phase. However, intraindividual gait variability increased significantly with RA and was correlated with increased brain activity in the SMC (p = 0.05; r = 0.57).

CONCLUSIONS

On the one hand, robotic guidance could generate sensory feedback that promotes active participation, leading to increased gait variability and somatosensory brain activity. On the other hand, changes in brain activity and biomechanical gait characteristics may also be due to the sensory feedback of the robot, which disrupts the cortical network of automated walking in healthy individuals. More comprehensive neurophysiological studies both in laboratory and in clinical settings are necessary to investigate the entire brain network associated with RAW.

Performance, complexity and dynamics of force maintenance and modulation in young and older adults

The present study addresses how task constraints and aging influence isometric force control. We used two tasks requiring either force maintenance (straight line target force) or force modulation (sine-wave target force) around different force levels and at different modulation frequencies. Force levels were defined relative the individual maximum voluntary contraction. A group of young adults (mean age ± SD = 25 ± 3.6 years) and a group of elderly (mean age = 77 ± 6.4 years) took part in the study. Age- and task-related effects were assessed through differences in: (i) force control accuracy, (ii) time-structure of force fluctuations, and (iii) the contribution of deterministic (predictable) and stochastic (noise-like) dynamic components to the expressed behavior. Performance-wise, the elderly showed a pervasive lower accuracy and higher variability than the young participants. The analysis of fluctuations showed that the elderly produced force signals that were less complex than those of the young adults during the maintenance task, but the reverse was observed in the modulation task. Behavioral complexity results suggest a reduced adaptability to task-constraints with advanced age. Regarding the dynamics, we found comparable generating mechanisms in both age groups for both tasks and in all conditions, namely a fixed-point for force maintenance and a limit-cycle for force modulation. However, aging increased the stochasticity (noise-driven fluctuations) of force fluctuations in the cyclic force modulation, which could be related to the increased complexity found in elderly for this same task. To our knowledge this is the first time that these different perspectives to motor control are used simultaneously to characterize force control capacities. Our findings show their complementarity in revealing distinct aspects of sensorimotor adaptation to task constraints and age-related declines. Although further research is still needed to identify the physiological underpinnings, the used task and methodology are shown to have both fundamental and clinical applications.

Prenatal light exposure influences gait performance and body composition in bobwhite quail chicks

Maternal nesting behavior, which includes periods of patterned inattention, provides key elements essential for avian embryonic development, including regulation of temperature and light. For example, avian research consistently shows the importance of prenatal light exposure for several developmental processes; however, this research has primarily focused on artificial light regimens (i.e. 24 hr, 0 hr light). Comparatively less is known about how exposure to naturally occurring light patterns during incubation influence motor performance, body composition (i.e. body mass, bone length), and developmental age (incubation length). Here we conducted two experiments which investigated the effects of prenatal light exposure on developmental age, body composition, and gait performance in 1-day-old bobwhite quail. Experiment 1 investigated crepuscular light exposure during the last two days of incubation under two light duration treatments (2 hr & 6 hr) compared to a 12 hr continuous light schedule. Results indicated crepuscular prenatal light experience extended the incubation period for 2 hr exposed embryos, but not for 6 hr exposed embryos and negatively influenced postnatal body composition and postnatal gait performance when compared to 12 hr continuous light embryos. Experiment 2 examined the influence of prenatal light duration (2 hr vs 6 hr) and light presentation (crepuscular vs sporadic). Results demonstrated sporadic light presentation improved gait performance in 2 hr exposed hatchlings, but not 6 hr exposed hatchlings, improved body composition in 6 hr exposed hatchlings, but not 2 hr exposed hatchlings, and did not alter incubation length when compared to crepuscular light counterparts. This study provides further evidence for the importance of maternally regulated sensory stimulation during the prenatal period on early postnatal motor development.

Selecting Clinically Relevant Gait Characteristics for Classification of Early Parkinson's Disease: A Comprehensive Machine Learning Approach

Parkinson's disease (PD) is the second most common neurodegenerative disease; gait impairments are typical and are associated with increased fall risk and poor quality of life. Gait is potentially a useful biomarker to help discriminate PD at an early stage, however the optimal characteristics and combination are unclear. In this study, we used machine learning (ML) techniques to determine the optimal combination of gait characteristics to discriminate people with PD and healthy controls (HC). 303 participants (119 PD, 184 HC) walked continuously around a circuit for 2-minutes at a self-paced walk. Gait was quantified using an instrumented mat (GAITRite) from which 16 gait characteristics were derived and assessed. Gait characteristics were selected using different ML approaches to determine the optimal method (random forest with information gain and recursive features elimination (RFE) technique with support vector machine (SVM) and logistic regression). Five clinical gait characteristics were identified with RFE-SVM (mean step velocity, mean step length, step length variability, mean step width, and step width variability) that accurately classified PD. Model accuracy for classification of early PD ranged between 73-97% with 63-100% sensitivity and 79-94% specificity. In conclusion, we identified a subset of gait characteristics for accurate early classification of PD. These findings pave the way for a better understanding of the utility of ML techniques to support informed clinical decision-making.

Characterization of statistical persistence in joint angle variation during walking

The objective of this study was to characterize joint angle variation across strides. Specifically, the statistical persistence of variations were quantified using the Hurst exponent. If a time series exhibits statistical persistence, then a parameter which is smaller (or larger) than average will tend to be followed by additional values that are also smaller (or larger) than average. Human walking has statistical persistence between stride durations. Variation in stride duration must arise from variation in the motion of the leg segments during walking. It is unclear, however, if the joint angle variation also exhibits statistical persistence. This study examined kinematic data collected from nine healthy adults walking for 10 min at a self-selected comfortable speed on a treadmill. The joint angle variation in the lower limbs was parameterized using first-order Fourier series which in turn were described by frequency and magnitude coefficients for each stride. To determine if the joint angle variation exhibited statistical persistence, the Hurst exponent was found for each coefficient at each joint. The mean Hurst exponents were 0.54 for the frequency coefficients and 0.61 for the magnitude coefficients. Neither the frequency or magnitude coefficients exhibited statistically significant persistence, although some of the magnitude coefficients were close to reaching statistical significance. This suggests that joint angle variability in healthy adults does not directly produce the statistical persistence observed in stride duration fluctuations.

Comparable Stride Time Fractal Dynamics and Gait Adaptability in Active Young and Older Adults Under Normal and Asymmetric Walking

Previous research indicates the correlation structure of gait parameters (i.e., fractal dynamics) decreases with age. This decrease is suggested to reflect a reduced capacity for locomotor adaptation in older adults. The purpose of this study was to investigate potential differences between physical activity-matched young and older adults’ fractal dynamics and gait adaptability during unperturbed and asymmetric walking, and to determine if fractal dynamics predict adaptive capacity. Fifteen young (28.9 ± 5.6 years, nine women) and 15 older (64.7 ± 2.7, nine women) adults with similar habitual physical activity levels walked at preferred speed, half of preferred speed, and asymmetrically whereby their dominant and non-dominant legs moved at preferred and half-preferred speed, respectively. Fractal correlations (scaling exponent α) of stride times were assessed through detrended fluctuation analysis, and gait adaptation to asymmetric walking on the basis of lower limb relative phase. Both cohorts displayed similar fractal dynamics at preferred speed and asymmetric walking, while older adults exhibited greater α during slow walking. Both groups exhibited comparable gait adaptation to split-belt walking based on analysis of lower limb relative phase. Fractal dynamics during preferred speed and asymmetric walking was moderately associated with gait adaptation in the young and older adult cohorts, respectively. In these activity-matched groups, there were no age-based reductions in fractal dynamics or gait adaptation, and fractal scaling α was moderately associated with gait adaptation. These findings suggest that stride time fractal dynamics and gait adaptation may be preserved in older adults who habitually perform moderate intensity physical activity.

Chronic Pain Characteristics and Gait in Older Adults: The MOBILIZE Boston Study II

OBJECTIVE

To investigate a proposed cognitively-mediated pathway whereby pain contributes to gait impairments by acting as a distractor in community-living older adults.

DESIGN

A cross-sectional study of a population-based cohort of older adults.

SETTING

Urban and suburban communities in a large metropolitan area.

PARTICIPANTS

Community-living participants (N=302) 70 years and older recruited from a previous population-based cohort.

INTERVENTIONS

Not applicable.

MAIN OUTCOME MEASURES

Gait parameters including gait speed, stride length, double support and swing characteristics, and variability were assessed under single- and dual-task conditions involving cognitive challenges (eg, counting backward). A joint pain questionnaire assessed pain distribution in the back and major joints. We examined pain-gait relationships using multivariable linear regression and bootstrapping mediation procedures.

RESULTS

Forty-three percent of participants had pain in 2 or more musculoskeletal sites. Pain distribution was related to slower gait speed and other gait characteristics for all gait conditions. Associations persisted after adjustment for age, sex, education, body mass index, medication, and vision. Decrements in gait measures related to pain were comparable with decrements in gait related to dual-task conditions. There were no differences in dual-task cost among the pain distribution groups. Adjusted for confounders, pain-gait relationships appear mediated by selective attention.

CONCLUSIONS

These findings suggest that chronic pain contributes to decrements in gait, including slower gait speed, and that it operates through a cognitively-mediated pathway. Further research is needed to understand the mechanisms via pain alters mobility and to develop interventions to improve mobility among older adults with chronic pain.

Evaluation of the Effects of Prescribing Gait Complexity Using Several Fluctuating Timing Imperatives

Variability in the temporal structure of gait patterns, measured by "Fractal Index" (FI), is thought to represent abundancy of movement patterns facilitating adaptive control of walking. However we do not know how FI changes according to different walking rhythms or if this is repeatable, as needed to exploit the paradigm for rehabilitation. Fourteen healthy young adults synchronised heel contact to an auditory metronome twice each in four conditions (uncued, white noise, pink noise, and red noise) and three sessions. FI differed based on the walking condition while no effect of session was revealed. The results of this study suggest gait fractality changes systematically with different stimuli and can be consistently prescribed in a desired direction within a group of healthy young individuals.

Comparison of selected measures of gait stability derived from center of pressure displacement signal during single and dual-task treadmill walking

Steady state gait dynamics has been examined using the measures of regularity, local dynamic stability, and variability. This study investigates the relationship between these measures under increasing cognitive loads. Participants walked on an instrumented treadmill at 1 m/s under walk only and two dual-task conditions. The secondary tasks were visuomotor cognitive games (VCG) of increasing difficulty level. The center of pressure displacement in the mediolateral direction (ML COP-D) and cognitive game performance were recorded for analysis. The following measures were calculated: (1) sample entropy (SampEn) and quantized dynamical entropy (QDE) of the ML COP-D, (2) short-term largest Lyapunov exponent (LLE) of the ML COP-D, and (3) variability of inter-stride spatio-temporal gait variables. Entropy and variability measures significantly increased from walk only to both dual-task conditions. Whereas, the short-term LLE increased only during the easy VCG task. No measure was sensitive to the difficulty level of the VCG tasks. The variability of heel strike positions in the mediolateral direction was positively correlated with SampEn and QDE. However, there were no significant correlations between the short-term LLE and either variability measures or entropy measures. These findings confirm that each of these measures is representative of a different aspect of human gait dynamics.

Reliability of the fluctuations within the stride time series measured in runners during treadmill running to exhaustion

BACKGROUND

The fluctuations within stride time series (i.e., stride time variability and complexity) during running exhibit long-range correlation. Detecting the breakdown of the long-range correlation was proposed for monitoring the occurrence of running-related injuries during running. However, the stride time fluctuations were only measured from the unilateral side. In addition, the reliability of the stride time fluctuations of within-subject repeated measures remains largely unknown, particularly during exhaustive running.

PURPOSES

This study investigated between-side and between-day reliabilities of the stride time variability and complexity of right and left sides during an exhaustive running.

METHODS

The stride time variability and complexity of bilateral sides were obtained while 24 healthy participants performed a 31-minute treadmill running at their individual anaerobic threshold speed. Seven of the 24 participants performed the treadmill running test twice at two different days 5-7 days apart. Limits of agreement (LoA) and intraclass correlation coefficient (ICC) were respectively used to assess the absolute and relative between-side and between-day reliabilities.

RESULTS

The stride time variability and complexity of right and left sides were highly symmetrical (LoA: (-0.500%, 0.459%) and (-0.052, 0.051), respectively; ICC: 0.94 (0.87, 0.97) and 0.98 (0.95, 0.99), respectively). The overall stride time variability and complexity revealed good between-day reliability (LoA: (-1.044%, 0.724%) and (-0.067, 0.115), respectively; ICC: 0.78 (0.45, 0.92) and 0.81 (0.48, 0.93), respectively). However, the segmented stride time complexity showed poor between-day reliability (ICCs<0.40).

CONCLUSION

The findings demonstrated that the stride time series showed equivalent fluctuations between right and left sides and good between-day reliability in fluctuations during exhaustive running. Given the poor between-day reliability in the segmented stride time series, stride time series during exhaustive running could be collected from either right or left side and should be processed as an overall in the future.

Multiscale Approximate Entropy for Gait Analysis in Patients with Neurodegenerative Diseases

Neurodegenerative diseases such as amyotrophic lateral sclerosis (ALS), Parkinson’s diseases (PD), and Huntington’s disease (HD) are not rare neurological diseases. They affect different neurological systems and present various characteristic gait abnormalities. We retrieved gait signals of the right and left feet from a public domain on the Physionet. There were 13 patients with ALS, 15 patients with PD, 20 patients with HD and 16 healthy controls (HC). We used multiscale approximate entropy (MAE) to analyze ground reaction force on both feet. Our study shows that MAE increases with scales in all tested subjects. The group HD has the highest MAE and group ALS has the lowest MAE. We can differentiate ALS from HC by MAE, while scale factors >10 in the left foot. There are few significant differences of MAE between the HC and HD. We found a good correlation of MAE between both feet in group ALS. In conclusion, our results indicate that MAE analysis of gait signals can be used for diagnosis and long-term assessment for ALS and probably HD. Similarity of MAE between both feet can also be a diagnostic marker for ALS.

Fractal properties and short-term correlations in motor control in cycling: influence of a cognitive challenge

Fluctuations in cyclic tasks periods is a known characteristic of human motor control. Specifically, long-range fractal fluctuations have been evidenced in the temporal structure of these variations in human locomotion and thought to be the outcome of a multicomponent physiologic system in which control is distributed across intricate cortical, spinal and neuromuscular regulation loops. Combined with long-range correlation analyses, short-range autocorrelations have proven their use to describe control distribution across central and motor components. We used relevant tools to characterize long- and short-range correlations in revolution time series during cycling on an ergometer in 19 healthy young adults. We evaluated the impact of introducing a cognitive task (PASAT) to assess the role of central structures in control organization. Autocorrelation function and detrending fluctuation analysis (DFA) demonstrated the presence of fractal scaling. PSD in the short range revealed a singular behavior which cannot be explained by the usual models of even-based and emergent timing. The main outcomes are that (1) timing in cycling is a fractal process, (2) this long-range fractal behavior increases in persistence with dual-task condition, which has not been previously observed, (3) short-range behavior is highly persistent and unaffected by dual-task. Relying on the inertia of the oscillator may be a way to distribute more control to the periphery, thereby allocating less resources to central process and better managing additional cognitive demands. This original behavior in cycling may explain the high short-range persistence unaffected by dual-task, and the increase in long-range persistence with dual-task.

Permutation Entropy and Irreversibility in Gait Kinematic Time Series from Patients with Mild Cognitive Decline and Early Alzheimer’s Dementia

Gait is a basic cognitive purposeful action that has been shown to be altered in late stages of neurodegenerative dementias. Nevertheless, alterations are less clear in mild forms of dementia, and the potential use of gait analysis as a biomarker of initial cognitive decline has hitherto mostly been neglected. Herein, we report the results of a study of gait kinematic time series for two groups of patients (mild cognitive impairment and mild Alzheimer’s disease) and a group of matched control subjects. Two metrics based on permutation patterns are considered, respectively measuring the complexity and irreversibility of the time series. Results indicate that kinematic disorganisation is present in early phases of cognitive impairment; in addition, they depict a rich scenario, in which some joint movements display an increased complexity and irreversibility, while others a marked decrease. Beyond their potential use as biomarkers, complexity and irreversibility metrics can open a new door to the understanding of the role of the nervous system in gait, as well as its adaptation and compensatory mechanisms.

Knee muscle co-contractions are greater in old compared to young adults during walking and stair use

BACKGROUND

Muscle co-contraction is an accepted clinical measure to quantify the effects of aging on neuromuscular control and movement efficiency. However, evidence of increased muscle co-contraction in old compared to young adults remains inconclusive.

RESEARCH QUESTION

Are there differences in lower-limb agonist/antagonist muscle co-contractions in young and old adults, and males and females, during walking and stair use?

METHODS

In a retrospective study, we analyzed data from 20 healthy young and 19 healthy old adults during walking, stair ascent, and stair descent at self-selected speeds, including marker trajectories, ground reaction force, and electromyography activity. We calculated muscle co-contraction at the knee (vastus lateralis vs. biceps femoris) and ankle (tibialis anterior vs. medial gastrocnemius) using the ratio of the common area under a muscle pairs' filtered and normalized electromyography curves to the sum of the areas under each muscle in that pair.

RESULTS

Old compared to young adults displayed 18%-22% greater knee muscle co-contractions during the entire cycle of stair use activities. We found greater (17%-29%) knee muscle co-contractions in old compared to young adults during the swing phase of walking and stair use. We found no difference in ankle muscle co-contractions between the two age groups during all three activities. We found no difference in muscle co-contraction between males and females at the knee and ankle joints for all three activities.

SIGNIFICANCE

Based on our findings, we recommend clinical evaluation to quantify the effects of aging through muscle co-contraction to include the knee joint during dynamic activities like walking and stair use, and independent evaluation of the stance and swing phases.