Fast Walking Condition Research Articles

Development of Surface EMG for Gait Analysis and Rehabilitation of Hemiparetic Patients.

The quantification of electromyographic activity using surface electrodes is invaluable for understanding gait disorders in patients with central nervous system lesions. We propose to evaluate a commercially available low-cost system compared to a reference system in participants with stroke-related movement disorders in functional situations. Three hemiparetic participants performed three functional tasks: two treadmill walks at different speeds and a sit-to-stand test. The vastus lateralis and gastrocnemius medialis muscles were equipped with two EMG sensors. The comparison between the two EMG systems was based on 883 identified cycles. Spearman's correlation coefficients (SCs), linear correlation coefficients (LCCs), and cross-correlation coefficients (CCCs) were calculated. The main results indicate good to very good similarity of the EMG signals collected from the two tested sEMG systems. In the comfortable-walking condition, an SC of 0.894 ± 0.091 and an LCC of 0.909 ± 0.094 were noted. In the fast-walking condition, an SC of 0.918 ± 0.064 and an LCC of 0.935 ± 0.056 were observed. For the 1 min sit-to-stand test, an SC of 0.880 ± 0.058 and an LCC of 0.881 ± 0.065 were noted. This study demonstrates good to very good similarity between the two sEMG systems, enabling the analysis of muscle activity during functional tasks.

Dynamic gait stability in children with and without Down syndrome during overground walking

BackgroundChallenging children with Down syndrome to walk fast and with external ankle load has demonstrated acute adjustments, such as increased step length and decreased step width, and improved joint stability. However, it is unknown to what extent these task constraints affect gait stability. Assessing dynamic gait stability through margin-of-stability not only quantifies adjustments related to balance control, but also informs safety considerations. MethodsTwenty-four children with and without Down syndrome participated in this study. Subjects walked overground at two speed conditions: self-selected (normal) and as fast as possible (fast); and two ankle load conditions: no load and ankle load of 2% body mass. We assessed margin-of-stability in the anteroposterior and mediolateral directions, separately, at three gait events of toe-off, mid-swing, and heel strike. FindingsChildren with Down syndrome walked with greater mediolateral margin-of-stability than typically developing children. Children with Down syndrome demonstrated less anteroposterior margin-of-stability than typically developing children only before heel-strike at normal speed but increased anteroposterior margin-of-stability at fast speed. The ankle load increased the mediolateral margin-of-stability in both groups but did not impact the anteroposterior margin-of-stability. In addition, children with Down syndrome took shorter and wider steps for more lateral placement of mediolateral margin-of-stability. InterpretationChildren with Down syndrome were capable of adjusting their margin-of-stability for fast walking and ankle-load conditions. However, children with Down syndrome walked with less mediolateral stability and anteroposterior mobility than typically developing children. Children with Down syndrome overcompensate the mediolateral foot placement to recapture their margin-of-stability and maintain gait stability.

Consistency of muscle activation signatures across different walking speeds

BackgroundUsing a machine learning algorithm, individuals can be accurately identified from their muscle activation patterns during gait, leading to the concept of individual muscle activation signatures. Research questionAre muscle activation signatures robust across different walking speeds? MethodsWe used an open dataset containing electromyographic (EMG) signals from 8 lower limb muscles in 50 asymptomatic adults walking at 5 speeds (extremely slow, very slow, slow, spontaneous, and fast). A machine learning approach classified the EMG profiles based on similar (intra-speed classification) or different (inter-speed classification) walking speeds as training and testing conditions. ResultsIntra-speed median classification rates of muscle activation profiles increased with walking speed, from 92 % for extremely slow, to 100 % for self-selected fast walking conditions. Inter-speed median classification rates increased when the speed of the training condition was closer to that of the testing condition. Higher median classification rates were found across slow, spontaneous, and fast walking speed conditions, from 56 % to 96 %, compared with classification rates involving extremely and very slow walking speed conditions, from 6 % to 62 %. SignificanceOur findings reveal that i) muscle activation signatures are detectable for a large range of walking speeds, even those involving different gait strategies (intra-speed median classification rates from 92 % to 100 %), and ii) muscle activation signatures observed during very low walking speeds are not consistent with those observed at higher speeds, suggesting a difference in motor control strategy. Caution should therefore be exercised when assessing gait deviations of a slow walking patient against a normative database obtained at higher speed. Identifying the robustness of individual muscle activation signatures across different movements could help in detecting changes in motor control, otherwise difficult to detect on classical time-varying EMG patterns.

Effects of Insole with Toe-Grip Bar on Barefoot Balance and Walking Function in Patients with Parkinson's Disease: A Randomized Controlled Trial.

The maintenance and improvement of balance and walking function in patients with Parkinson's disease (PD) is essential. Toe dysfunction in patients with PD is related to balance and walking. Recently, insoles have been developed to improve toe function, but their effects on the physical functions of patients with PD remain unclear. In this randomized controlled study, we investigated the effects of insoles with a toe-grip bar on balance and walking function in such patients. Twenty-nine patients with PD in Hoehn and Yahr stages II-IV were randomly assigned to an intervention or control group. Patients in the intervention and control groups wore shoes having insoles with and without a toe-grip bar for 4 weeks, respectively. The center of gravity sway of standing posture (total trajectory length, envelope area, and maximum anterior-posterior center of pressure [AP-COP] distance) and walking parameters at normal and fast speeds were measured pre- and post-intervention in the rehabilitation room. All measurements were performed with the participants being barefoot. The maximum AP-COP distance and step length of the fast-walking condition were significantly improved in the intervention compared to the control group (p < 0.05). Thus, insoles with a toe-grip bar may improve balance and walking function in patients with PD.

Network-Based Transcranial Direct Current Stimulation May Modulate Gait Variability in Young Healthy Adults.

PurposePrevious studies have linked gait variability to resting-state functional connectivity between the dorsal attention network (DAN) and the default network (DN) in the brain. The purpose of this study was to examine the effects of a novel transcranial direct current stimulation (tDCS) paradigm designed to simultaneously facilitate the excitability of the DAN and suppress the excitability of the DN (i.e., DAN+/DN-tDCS) on gait variability and other gait characteristics in young healthy adults.MethodsIn this double-blinded randomized and sham-controlled study, 48 healthy adults aged 22 ± 2 years received one 20-min session of DAN+/DN-tDCS (n = 24) or no stimulation (the Sham group, n = 24). Immediately before and after stimulation, participants completed a gait assessment under three conditions: walking at self-selected speed (i.e., normal walking), walking as fast as possible (i.e., fast walking), and walking while counting backward (i.e., dual-task walking). Primary outcomes included gait stride time variability and gait stride length variability in normal walking conditions. Secondary outcomes include gait stride time and length variability in fast and dual-task conditions, and other gait metrics derived from the three walking conditions.ResultsCompared to the Sham group, DAN+/DN-tDCS reduced stride length variability in normal and fast walking conditions, double-limb support time variability in fast and dual-task walking conditions, and step width variability in fast walking conditions. In contrast, DAN+/DN-tDCS did not alter average gait speed or the average value of any other gait metrics as compared to the sham group.ConclusionIn healthy young adults, a single exposure to tDCS designed to simultaneously modulate DAN and DN excitability reduced gait variability, yet did not alter gait speed or other average gait metrics, when tested just after stimulation. These results suggest that gait variability may be uniquely regulated by these spatially-distinct yet functionally-connected cortical networks. These results warrant additional research on the short- and longer-term effects of this type of network-based tDCS on the cortical control of walking in younger and older populations.

A multi-step blind source separation approach for the attenuation of artifacts in mobile high-density electroencephalography data

Objective. Electroencephalography (EEG) is a widely used technique to address research questions about brain functioning, from controlled laboratorial conditions to naturalistic environments. However, EEG data are affected by biological (e.g. ocular, myogenic) and non-biological (e.g. movement-related) artifacts, which—depending on their extent—may limit the interpretability of the study results. Blind source separation (BSS) approaches have demonstrated to be particularly promising for the attenuation of artifacts in high-density EEG (hdEEG) data. Previous EEG artifact removal studies suggested that it may not be optimal to use the same BSS method for different kinds of artifacts. Approach. In this study, we developed a novel multi-step BSS approach to optimize the attenuation of ocular, movement-related and myogenic artifacts from hdEEG data. For validation purposes, we used hdEEG data collected in a group of healthy participants in standing, slow-walking and fast-walking conditions. During part of the experiment, a series of tone bursts were used to evoke auditory responses. We quantified event-related potentials (ERPs) using hdEEG signals collected during an auditory stimulation, as well as the event-related desynchronization (ERD) by contrasting hdEEG signals collected in walking and standing conditions, without auditory stimulation. We compared the results obtained in terms of auditory ERP and motor-related ERD using the proposed multi-step BSS approach, with respect to two classically used single-step BSS approaches. Main results. The use of our approach yielded the lowest residual noise in the hdEEG data, and permitted to retrieve stronger and more reliable modulations of neural activity than alternative solutions. Overall, our study confirmed that the performance of BSS-based artifact removal can be improved by using specific BSS methods and parameters for different kinds of artifacts. Significance. Our technological solution supports a wider use of hdEEG-based source imaging in movement and rehabilitation studies, and contributes to the further development of mobile brain/body imaging applications.

Prefrontal Cortical Activity During Preferred and Fast Walking in Young and Older Adults: An fNIRS Study

Age-related changes may affect the performance during fast walking speed. Although, several studies have been focused on the contribution of the prefrontal cortex (PFC) during challenging walking tasks, the neural mechanism underling fast walking speed in older people remain poorly understood. Therefore, the aim of this study was to investigate the influence of aging on PFC activity during overground walking at preferred and fast speeds. Twenty-five older adults (67.37 ± 5.31 years) and 24 young adults (22.70 ± 1.30 years) walked overground in two conditions: preferred speed and fast walking speed. Five trials were performed for each condition. A wireless functional near-infrared spectroscopy (fNIRS) system measured PFC activity. Gait parameters were evaluated using the GAITRite system. Overall, older adults presented higher PFC activity than young adults in both conditions. Speed-related change in PFC activity was observed for older adults, but not for young adults. Older adults significantly increased activity in the left PFC from the preferred to fast walking condition whereas young adults had similar levels of PFC activity across conditions. Our findings suggest that older adults need to recruit additional prefrontal cognitive resources to control walking, indicating a compensatory mechanism. In addition, left PFC seems to be involved in the modulation of gait speed in older adults.

Pedestrian single-file movement on stairs under different motivations

In this paper, we conduct a single-file experiment on stairs under two motivations, namely normal walking condition and fast walking condition at various densities. Totally four types of movements are analyzed and compared, namely normal walking-ascending movement, normal walking-descending movement, fast walking-ascending movement and fast walking-descending movement. Compared with the normal walking condition, in fast walking condition pedestrians move with higher velocity, which can be clearly observed in color-coded trajectories and time–space diagrams. We further make pairwise comparisons of density–velocity and headway–velocity relations for four types of movement, and critical parameters such as minimum headway, adaptation time, critical headway and free-flow velocity are extracted. It is found that the adaptation time is negatively correlated with free-flow velocity, indicating that pedestrians under higher movement motivation have a stronger ability to adapt their velocities. Besides, the values of time to collision are smaller for ascending movement than descending movement, apart from those at high density. In addition, we also analyze the following behavior through the relation between velocities of two adjacent pedestrians. The correlation analysis indicates that velocities are most correlated in fast walking-descending movement, and least correlated in normal walking-ascending movement. It is hoped that our study can be useful for the modeling of stair motion and the design of building stairway.

A Comparison of Denoising Methods in Onset Determination in Medial Gastrocnemius Muscle Activations during Stance

One of the most basic pieces of information gained from dynamic electromyography is accurately defining muscle action and phase timing within the gait cycle. The human gait relies on selective timing and the intensity of appropriate muscle activations for stability, loading, and progression over the supporting foot during stance, and further to advance the limb in the swing phase. A common clinical practice is utilizing a low-pass filter to denoise integrated electromyogram (EMG) signals and to determine onset and cessation events using a predefined threshold. However, the accuracy of the defining period of significant muscle activations via EMG varies with the temporal shift involved in filtering the signals; thus, the low-pass filtering method with a fixed order and cut-off frequency will introduce a time delay depending on the frequency of the signal. In order to precisely identify muscle activation and to determine the onset and cessation times of the muscles, we have explored here onset and cessation epochs with denoised EMG signals using different filter banks: the wavelet method, empirical mode decomposition (EMD) method, and ensemble empirical mode decomposition (EEMD) method. In this study, gastrocnemius muscle onset and cessation were determined in sixteen participants within two different age groups and under two different walking conditions. Low-pass filtering of integrated EMG (iEMG) signals resulted in premature onset (28% stance duration) in younger and delayed onset (38% stance duration) in older participants, showing the time-delay problem involved in this filtering method. Comparatively, the wavelet denoising approach detected onset for normal walking events most precisely, whereas the EEMD method showed the smallest onset deviation. In addition, EEMD denoised signals could further detect pre-activation onsets during a fast walking condition. A comprehensive comparison is discussed on denoising EMG signals using EMD, EEMD, and wavelet denoising in order to accurately define an onset of muscle under different walking conditions.

Dual Task Interference During Walking After Ten Days Of Complete Physical Inactivity

Prolonged physical inactivity or immobilization after sports injuries and/or surgery can lead to severe cognitive and motor disorders that prevent rapid recovery and lead to future falls. Previous studies have shown that gait control provides the demand for cognitive centers of the brain and that dual-task assessments may indicate an increased risk of falling or a protection strategy to prevent falls. PURPOSE: To determine to which extent walking and walking while texting ability deteriorates after prolonged physical inactivity. METHODS: Ten healthy young volunteers successfully completed 10 days of horizontal bed rest with 24h video and medical monitoring. Gait speed parameter was obtained with the 2D OptoGait system (Microgate, Italy, EU) under four different conditions in a random order: self-selected and fast paced walking condition with (dual-task) and without (single-task) typing on the smartphone. RESULTS: Ten days of horizontal bed rest had no significant impact on the self-selected gait speed in single- (-5.7%; p=0.190) and dual-task conditions (-4.0%; p=0.339). In contrast, bed rest significantly decreased gait speed in fast paced walking condition in single- (-9.9%; p=0.009) and dual-task conditions (-10.3%; p=0.002). CONCLUSION: Our results show that bed rest reduces gait performance and that the effects are greater for tasks that require more attentional resources - tasks with higher complexity. The results can be used for the future development of effective rehabilitation countermeasures.Supported by ASI, MARS-PRE Project, n. DC-VUM-2017-006.

A Comparison of Denoising Methods in Onset Determination in Medial Gastrocnemius Muscle Activations during Stance

One of the most basic pieces of information gained from dynamic electromyography is accurately defining muscle action and phase timing within the gait cycle. The human gait relies on selective timing and the intensity of appropriate muscle activations for stability, loading, and progression over the supporting foot during stance, and further to advance the limb in the swing phase. A common clinical practice is utilizing a low-pass filter to denoise integrated electromyogram (EMG) signals and to determine onset and cessation events using a predefined threshold. However, the accuracy of the defining period of significant muscle activations via EMG varies with the temporal shift involved in filtering the signals; thus, the low-pass filtering method with a fixed order and cut-off frequency will introduce a time delay depending on the frequency of the signal. In order to precisely identify muscle activation and to determine the onset and cessation times of the muscles, we have explored here onset and cessation epochs with denoised EMG signals using different filter banks: the wavelet method, empirical mode decomposition (EMD) method, and ensemble empirical mode decomposition (EEMD) method. In this study, gastrocnemius muscle onset and cessation were determined in sixteen participants within two different age groups and under two different walking conditions. Low-pass filtering of integrated EMG (iEMG) signals resulted in premature onset (28% stance duration) in younger and delayed onset (38% stance duration) in older participants, showing the time-delay problem involved in this filtering method. Comparatively, the wavelet denoising approach detected onset for normal walking events most precisely, whereas the EEMD method showed the smallest onset deviation. In addition, EEMD denoised signals could further detect pre-activation onsets during a fast walking condition. A comprehensive comparison is discussed on denoising EMG signals using EMD, EEMD, and wavelet denoising in order to accurately define an onset of muscle under different walking conditions.

Quantitative analysis of the bilateral coordination and gait asymmetry using inertial measurement unit-based gait analysis.

Inertial measurement unit (IMU)-based gait analysis can be used to quantitatively analyze the bilateral coordination and gait asymmetry (GA). The purpose of this study was to investigate changes in bilateral coordination and GA due to gait speed using an IMU based gait analysis and identify spatiotemporal factors affecting bilateral coordination and GA. Eighty healthy adults (40 men and 40 women) participated in the study. The mean age was 26.2 years, and the mean body mass index was 22.8 kg/m2. Three different walking speeds (80%, 100%, and 120% of preferred walking speed) on a treadmill were applied for 1 min of continuous level walking using a shoe-type IMU-based gait analysis system. The phase coordination index (PCI) and GA were calculated on three different walking speeds. Several variables (gait speed, height, body mass index, cadence, and step length) were analyzed as possible factors affecting the PCI and GA. Bilateral coordination and GA improved during fast walking (p = 0.005 and p = 0.019, respectively) and deteriorated during slow walking (p<0.001 and p = 0.008, respectively), compared with the participants’ preferred walking speeds. The correlation analysis revealed that PCI was negatively correlated with step length at each walking condition and lower gait speed was negatively correlated with PCI and GA during slow walking. Both bilateral coordination and GA had a negative linear relationship with gait speed, showing an improvement in the fast walking condition and deterioration in the slow walking condition. Step length was the factor associated with the change in the bilateral coordination.

Spatial task-related brain activity and its association with preferred and fast pace gait speed in older adults

Task-related brain activity is associated with preferred pace gait speed in older adults. Whether similar regional brain activity relates to fast pace gait speed has yet to be determined, but may provide insight into neural substrate important for walking under various conditions. This study measured regional blood-oxygen-level dependent (BOLD) changes using functional magnetic resonance imaging (fMRI) in response to a spatial Simon/Stroop task in community-dwelling older adults (N = 20, 63–80y). Preferred pace, fast pace, and dual-task gait speeds (picking up objects at preferred pace; fast walking over obstacles) were measured across a 7-meter course. Time to complete a fast pace 400 m walk test was also recorded. Partial correlations were used for all analyses after adjusting for age. Accuracy on incongruent trials of the spatial task was positively correlated with all fast walking conditions (all p < 0.01), but not preferred pace walking conditions. BOLD signal change in the left middle frontal gyrus during the spatial task was associated with preferred pace gait speed (r = 0.51, p = 0.02) and fast walking over obstacles (r = 0.53, p = 0.01). Interestingly, BOLD signal change in the bilateral precuneus was associated with fast pace gait speed (r = 0.58, p < 0.01), fast walking over obstacles (r = 0.48, p = 0.03), and 400 m walk time (r=−0.49, p = 0.02). These results find preferred and fast pace gait speed are associated with different regional task-related brain activity, with activation in the precuneus related with greater performance during fast pace walking.

Using supervised learning machine algorithm to identify future fallers based on gait patterns: A two-year longitudinal study.

Given their major health consequences in the elderly, identifying people at risk of fall is a major challenge faced by clinicians. A lot of studies have confirmed the relationships between gait parameters and falls incidence. However, accurate tools to predict individual risk among independent older adults without a history of falls are lacking. This study aimed to apply a supervised learning algorithm to a data set recorded in a two-year longitudinal study, in order to build a classification tree that could discern subsequent fallers based on their gait patterns. A total of 105 adults aged >65 years, living independently at home and without a recent fall history were included in a two-year longitudinal study. All underwent physical and functional assessment. Gait speed, stride length, frequency, symmetry and regularity, and minimum toe clearance were recorded in comfortable, fast and dual task walking conditions in a standardized laboratory environment. Fall events were recorded using personal falls diaries. A supervised machine learning algorithm (J48) has been applied to the data recorded at inclusion in order to obtain a classification tree able to identify future fallers. Based on fall information from 96 volunteers, a classification tree correctly identifying 80% of future fallers based on gait patterns, gender, and stiffness, was obtained, with accuracy of 84%, sensitivity of 80%, specificity of 87%, a positive predictive value of 78%, and a negative predictive value of 88%. While the performances of the classification tree warrant further confirmation, it is the first predictive tool based on gait parameters that are identified (not clustered) allowing its use by other research teams. This original longitudinal pilot study using a supervised machine learning algorithm, shows that gait parameters and clinical data can be used to identify future fallers among independent older adults.

Comparison of forward and backward gait characteristics between those with and without a history of breast cancer

BackgroundDecreased muscular strength and poorer postural stability impact the physical function of breast cancer survivors (BCS) and increases their risk of falls. Gait assessment, particularly in the backward direction, is often used as an indicator of fall risk in several populations. However this information is unknown in BCS. Research questionWhat are the differences in forward, backward, and accelerated forward walking in BCS in comparison to individuals without a prior cancer diagnosis? Methods17 postmenopausal BCS (mean age: 58.5 (8.5) years) and 17 age-matched women without a prior cancer diagnosis (mean age: 59.11 (5.55) years) completed 5 trials each of forward, backward, and fast forward walking conditions. Absolute (Means) and variability (Coefficient of variation) estimates were obtained for spatio-temporal gait parameters. Lower body, upper body and handgrip strengths were measured. ResultsFor absolute estimates of gait, significant group main effects indicated that BCS had 7% shorter step length (P = 0.019) and 8% slower gait speed (P = 0.048). For variability estimates of gait, there was a significant interaction for stance time (P = 0.035). BCS had greater stance time variability during forward and fast forward conditions, but lesser variability during backward condition. Averaged across all the conditions, BCS had 38% greater step length variability (P = 0.043), 50% greater gait speed variability (P = 0.028), and 28.5% greater single support time variability (P = 0.004). Averaged across both the groups, all the variables except for swing time variability were significantly different among the conditions (all P< = 0.013). BCS also had significantly reduced upper body strength (P = 0.036). SignificanceSlower and shorter steps while walking both forwards and backwards could be indicative of a more cautious gait strategy by BCS. Also, BCS possibly focused on controlling spatial parameters during forward walking but temporal parameters while backward walking. Whether these alterations are related to an increased fall risk within BCS needs to be determined.

Gait symmetry in the dual task condition as a predictor of future falls among independent older adults: a 2-year longitudinal study.

Given the potential consequences of falls among older adults, a major challenge is to identify people at risk before the first event. In this context, gait parameters have been suggested as markers of fall risk. To examine, among older people, the prospective relationship between gait patterns assessed in comfortable and challenging walking conditions, and future fall(s). A total of 105 adults older than 65years, living independently at home and without a recent fall history were included in a 2-year, longitudinal, observational study. All underwent physical and functional assessment. Gait speed, stride length, frequency, symmetry and regularity and Minimum Toe Clearance (MTC) were recorded in comfortable (CW), fast (FW) and dual task walking (DTW) conditions. Gait parameter changes occurring between CW and FW and between CW and DTW were calculated and expressed in percent. DTW cost was calculated as the change of DTW relative to CW. Fall events were recorded using fall diaries. Comparisons according to fall occurrence were performed by means of univariate analysis and multivariate binary logistic regression analysis. Two-year follow-up was available for 96 participants, of whom 35 (36.5%) fell at least once. Comparative analysis showed that future fallers had shorter FW stride length and higher symmetry DTW cost than non-fallers (p < 0.05). Binary logistic regression analysis showed that each additional percent of stride symmetry cost was associated with an increase in future fall risk (odds ratio 1.018, 95% Confidence Interval (CI) 1.002-1.033; p = 0.027). Our results confirm the association between a symmetry decrease in DTW and future fall(s). Indeed in this study, the mean symmetry DTW cost in fallers is almost 20% higher than in non-fallers, meaning a fall risk that is around 36% higher than among non-fallers. This exploratory study shows the usefulness of considering gait parameters, particularly symmetry in challenging walking conditions, for early identification of future fallers.

Hip kinematics and kinetics in total hip replacement patients stratified by age and functional capacity

To examine functional differences in total hip replacement patients (THR) when stratified either by age or by functional ability as defined by self-selected walking speed. THR patients and a control group underwent three-dimensional motion analysis under self-selected normal and fast walking conditions. Patients were stratified into five age groups for comparison with existing literature. The THR cohort was also stratified into three functional groups determined by their self-selected gait speed (low function <1SD of total cohort’s mean walking speed; high function >1SD; normal function within 1SD). Hip kinematics, ground reaction forces, joint moments and joint powers in all three planes (x-y-z) were analysed. 137 THR and 27 healthy control patients participated. When stratified by age, during normal walking the youngest two age groups walked quicker than the oldest two groups (p < 0.0001) but between-group differences were not consistent across age strata. The differences were diminished under the fast walking condition. When stratified by function, under normal walking conditions, the low function and normal function THR groups had a reduced extension angle (mean = 1.75°, SD = ±7.75, 1.26° ± 7.42, respectively) compared to the control group (−6.07° ± 6.43; p < 0.0001). The low function group had a reduced sagittal plane hip power (0.75 W/kg ± 0.24), reduced flexor (0.60 Nm/kg ± 0.85) and extensor moment (0.51 Nm/kg ± 0.17) compared to controls (p < 0.0001). These differences persisted under the fast walking condition. There were systematic differences between patients when stratified by function, in both walking conditions. Age-related differences were less systematic. Stratifying by biomechanical factors such as gait speed, rather than age, might be more robust for investigating functional differences.

Physical activity in mild multiple sclerosis: contribution of perceived fatigue, energy cost, and speed of walking

Purpose: To clarify the relationship between leisure-time physical activity, perceived fatigue, and energy expenditure while walking in people with multiple sclerosis.Methods: Sixty-six people afflicted with multiple sclerosis (MS) (32 women) with a mild neurological disability, participated in this study. Energy expenditure was separately measured at rest, during comfortable walking and during fast walking via a portable metabolic device using breath-by-breath technology (COSMED K5, COSMED Srl, Rome, Italy). The Godin leisure-time exercise questionnaire assessed leisure-time physical activity. The Modified Fatigue Impact Scale determined the level of perceived fatigue.Results: Seventeen people with MS were classified as physically active; 49 were insufficiently active. Scores recorded on the Godin Leisure-Time Exercise Questionnaire were 47.8 (SD = 18.4), 7.0 (SD = 8.2), respectively. Insufficiently physically active people with MS walked slower at both normal and fast walking conditions. However, no differences between groups were observed in energy expenditure measures in both walking speeds. O2 cost was 0.20 (SD = 0.13) and 0.21 (SD = 0.06) in the active and insufficiently active group, respectively. The insufficiently active group reported more perceived fatigue compared with the active patients; 33.3 (SD = 18.6) vs. 15.0 (SD = 19.0), p value = 0.002. Perceived fatigue was a significant variable maintaining a 10.4% variance related to leisure-time physical activity.Conclusions: Leisure-time physical activity was inversely associated with perceived fatigue and walking speed in persons with mild MS. Rehabilitation professionals should be aware of these relationships when planning rehabilitation strategies.Implication for rehabilitationThis study found that perceived fatigue is a barrier to physical activity participation even in people with mild multiple sclerosis and minimal disability.Insufficiently active people with multiple sclerosis expend the same amount of energy while walking as active multiple sclerosis individuals, though walking slower.The relationship between perceived fatigue and physical activity participation requires further exploration in the multiple sclerosis population.

Lower limb extension is improved in fast walking condition in children who walk in crouch gait

Background and purpose: The strategies for walking fast have never been reported in children with cerebral palsy who walk in crouch gait. This study aimed to assess to what extent children who walk in crouch gait are able to increase their gait speed and to report the corresponding three-dimensional kinematic adaptations.Methods: Eleven children and adolescents (aged between 7 and 17 years) with bilateral cerebral palsy, who walk in crouch gait, were asked to walk at their self-selected comfortable speed and then as fast as possible without running. The spatio-temporal and kinematic parameters, as well as the center of mass displacements were compared between walking conditions.Results: Children were able to walk 30% faster than their comfortable speed (+0.30 m/s, p = 0.000) by increasing both cadence (+21 step/min, p = 0.000) and step length (+0.05 m, p = 0.001). During the stance phase, pelvis anteversion (+3 Deg, p = 0.010), hip flexion-extension range of motion (+4 Deg, p = 0.002), and knee extension (+5 Deg, p = 0.000) were increased in fast walking. During fast walking, the center of mass showed larger range of vertical displacements (p < 0.05).Conclusions: Children with cerebral palsy who walk in crouch gait increased their walking speed by adopting a less crouched posture. Compared to comfortable walking speed condition, fast walking could be beneficial in rehabilitation to solicit higher lower limbs range of motion.Implications for rehabilitation:Children who walk in crouch gait can walk 30% fasterFast walking required higher hip and knee extensions during stance phaseFast walking could be an interesting training modality to improve the lower limb range of motion of children who walk in crouch gait

The walk ratio: Investigation of invariance across walking conditions and gender in community-dwelling older people

BackgroundThe step length-cadence ratio, also called the walk ratio (WR; cm/steps/min) is a measure of cautious gait, poor balance control or impaired gait, but has not been investigated for both genders in a general population of older adults across different speeds and conditions. MethodThe participants were community-dwelling volunteers between 70 and 81 years. They walked 6.5 m under four different conditions: At preferred speed, fast speed, during a dual task condition and on an uneven surface. Step length (cm) and cadence (steps/minute) was captured using a body-worn sensor. Both cadence and step lengths were adjusted for body height. Results70 older adults participated (mean age 75.5 (SD 3.4), 60 percent women). The WR was 0.60 cm/steps/min (SD 0.07) during preferred speed walking, 0.58 cm/steps/min (SD 0.07) during fast walking, 0.68 cm/steps/min (SD 0.18) during dual task-walking and 0.59 cm/steps/min (0.07) during uneven surface-walking. In planned pairwise comparisons, the WR during dual task was significantly different from preferred speed walking (mean difference −0.087 cm/steps/min, 95% CI −0.140, −0.033), from fast speed walking (mean difference −0.098 cm/steps/min, 95% CI −0.154, −0.041) and uneven surface walking (mean difference 0.092 cm/steps/min, 95% CI 0.040, 0.145). There were no gender differences except during the fast walking condition, where women had a significantly lower WR than the men (0.56 cm/steps/min vs 0.61 cm/steps/min, p = 0.002). DiscussionWe found that the WR is invariant during different speeds, and during an uneven surface condition, but is affected during a dual task-condition, when attention must be divided between a cognitive and a motor task.