The "butterfly diagram": A gait marker for neurological and cerebellar impairment in people with multiple sclerosis

Centre of pressure changes during stance but not during gait in young women after alcohol intoxication

Background

Women are underrepresented in research focused on alcohol (e.g., Brighton, Moxham & Traynor, 2016; DOI 10.1097/JAN.0000000000000136) despite the changing patterns of alcohol consumption, which has been increasing in women in recent decades. The purpose of this study was to analyse the relationship between habitual alcohol consumption and centre of pressure (CoP) parameters during stance and gait while intoxicated by alcohol.

Methods

Thirty women (24.39 ± 2.93 years) participated in this study. All participants were asked to answer the AUDIT questionnaire. Stance and gait analysis were repeated under two conditions on a Zebris platform (FDM GmbH; Munich, Germany): when the participants were sober (0.00% breath alcohol concentration, BrAC) and when they were in an intoxicated state (0.11% BrAC). Participants were divided by their AUDIT score into a low-risk alcohol consumption group (n = 15; AUDIT score: 3 to 6) and a hazardous alcohol consumption group (n = 15; AUDIT score: 7 to 13).

Results

No statistical difference was observed in stance and gait parameters when comparing the low-risk and hazardous groups under 0.00% BrAC and 0.11% BrAC conditions. A statistically significant difference was observed when comparing 0.00% BrAC and 0.11% BrAC conditions within each group. This significant difference was found in CoP path length and CoP average velocity during quiet stance. However, no statistically significant differences were observed in CoP parameters during gait. An alcohol intoxication of 0.11% BrAC was not sufficient to cause statistically significant impairments in butterfly parameters of gait.

Deep Learning for Multiple Sclerosis Differentiation Using Multi-Stride Dynamics in Gait

OBJECTIVE

Multiple sclerosis (MS) is a chronic neurological condition of the central nervous system leading to various physical, mental and psychiatric complexities. Mobility limitations are amongst the most frequent and early markers of MS. We evaluated the effectiveness of a DeepMS2G (deep learning (DL) for MS differentiation using multistride dynamics in gait) framework, which is a DL-based methodology to classify multi-stride sequences of persons with MS (PwMS) from healthy controls (HC), in order to generalize over newer walking tasks and subjects.

METHODS

We collected single-task Walking and dual-task Walking-while-Talking gait data using an instrumented treadmill from a balanced collection of 20 HC and 20 PwMS. We utilized domain knowledge-based spatiotemporal and kinetic gait features along with two normalization schemes, namely standard size-based and multiple regression normalization strategies. To differentiate between multi-stride sequences of HC and PwMS, we compared 16 traditional machine learning and DL algorithms. Further, we studied the interpretability of our highest-performing models; and discussed the association between the lower extremity function of participants and our model predictions.

RESULTS

We observed that residual neural network (ResNet) based models with regression-based normalization were the top performers across both task and subject generalization classification designs. Considering regression-based normalization, a multi-scale ResNet attained a subject classification accuracy and F 1-score of 1.0 when generalizing from single-task Walking to dual-task Walking-while-Talking; and a ResNet resulted in the top subject-wise accuracy and F 1 of 0.83 and 0.81 (resp.), when generalizing over unseen participants.

CONCLUSION

We used advanced DL and dynamics across domain knowledge-based spatiotemporal and kinetic gait parameters to successfully classify MS gait across distinct walking trials and unseen participants.

SIGNIFICANCE

Our proposed DL algorithms might contribute to efforts to automate MS diagnoses.

Spatiotemporal gait patterns in individuals with unilateral transfemoral amputation: A hierarchical cluster analysis

Gait pattern classification in individuals with lower-limb amputation could help in developing personalized prosthetic prescriptions and tailored gait rehabilitation. However, systematic classifications of gait patterns in this population have been scarcely explored. This study aimed to determine whether the gait patterns in individuals with unilateral transfemoral amputation (UTFA) can be clustered into homogeneous subgroups using spatiotemporal parameters across a range of walking speeds. We examined spatiotemporal gait parameters, including step length and cadence, in 25 individuals with UTFA (functional level K3 or K4, all non-vascular amputations) while they walked on a split-belt instrumented treadmill at eight speeds. Hierarchical cluster analysis (HCA) was used to identify clusters with homogeneous gait patterns based on the relationships between step length and cadence. Furthermore, after cluster formation, post-hoc analyses were performed to compare the spatiotemporal parameters and demographic data among the clusters. HCA identified three homogeneous gait pattern clusters, suggesting that individuals with UTFA have several gait patterns. Further, we found significant differences in the participants' body height, sex ratio, and their prosthetic knee component among the clusters. Therefore, gait rehabilitation should be individualized based on body size and prosthetic prescription.

Centre of pressure during walking after unilateral transfemoral amputation

Lower-limb amputation imposes a health burden on amputees; thus, gait assessments are required prophylactically and clinically, particularly for individuals with unilateral transfemoral amputation (UTFA). The centre of pressure (COP) during walking is one of the most useful parameters for evaluating gait. Although superimposed COP trajectories reflect the gait characteristics of individuals with neurological disorders, the quantitative characteristics based on the COP trajectories of individuals with UTFA remain unclear. Thus, these COP trajectories were investigated across a range of walking speeds in this study. The COP trajectories were recorded on a split-belt force-instrumented treadmill at eight walking speeds. Asymmetry and variability parameters were compared based on the COP trajectories of 25 individuals with UTFA and 25 able-bodied controls. The COP trajectories of the individuals with UTFA were significantly larger in lateral asymmetry and variability but did not show significant differences in anterior-posterior variability compared with those of the able-bodied controls. Further, the individuals with UTFA demonstrated larger lateral asymmetry at lower speeds. These results suggest that (1) individuals with UTFA adopt orientation-specific balance control strategies during gait and (2) individuals with UTFA could also be exposed to a higher risk of falling at lower walk speeds.

An Update on the Measurement of Motor Cerebellar Dysfunction in Multiple Sclerosis

Multiple sclerosis (MS) is a progressive disease that often affects the cerebellum. It is characterised by demyelination, inflammation, and neurodegeneration within the central nervous system. Damage to the cerebellum in MS is associated with increased disability and decreased quality of life. Symptoms include gait and balance problems, motor speech disorder, upper limb dysfunction, and oculomotor difficulties. Monitoring symptoms is crucial for effective management of MS. A combination of clinical, neuroimaging, and task-based measures is generally used to diagnose and monitor MS. This paper reviews the present and new tools used by clinicians and researchers to assess cerebellar impairment in people with MS (pwMS). It also describes recent advances in digital and home-based monitoring for people with MS.

Fall Risk Assessment for the Elderly Based on Weak Foot Features of Wearable Plantar Pressure

The high fall rate of the elderly brings enormous challenges to families and the medical system; therefore, early risk assessment and intervention are quite necessary. Compared to other sensor-based technologies, in-shoe plantar pressure sensors, effectiveness and low obtrusiveness are widely used for long-term fall risk assessments because of their portability. While frequently-used bipedal center-of-pressure (COP) features are derived from a pressure sensing platform, they are not suitable for the shoe system or pressure insole owing to the lack of relative position information. Therefore, in this study, a definition of "weak foot" was proposed to solve the sensitivity problem of single foot features and facilitate the extraction of temporal consistency related features. Forty-four multi-dimensional weak foot features based on single foot COP were correspondingly extracted; notably, the relationship between the fall risk and temporal inconsistency in the weak foot were discussed in this study, and probability distribution method was used to analyze the symmetry and temporal consistency of gait lines. Though experiments, foot pressure data were collected from 48 subjects with 24 high risk (HR) and 24 low risk (LR) ones obtained by the smart footwear system. The final models with 87.5% accuracy and 100% sensitivity on test data outperformed the base line models using bipedal COP. The results and feature space shown the novel features of wearable plantar pressure could comprehensively evaluate the difference between HR and LR groups. Our fall risk assessment models based on these features had good generalization performance, and showed practicability and reliability in real-life monitoring situations.

Using a Portable Pressure-Sensing Walkway to Detect Age-Related Alternations in Foot Integrated Pressure During Multiple Obstacle Negotiation

Multiple obstacle avoidance induces a higher potential of falls among older adults. This study attempted to add other important measurements by investigating the pressure-related gait parameters when stepping over multiple obstacles on a portable pressure-sensing walkway. Twenty-six young and 26 older participants were recruited in this study. A portable pressure-sensing Zeno walkway and cyclogram intersection point analysis method was introduced to collect both spatial-temporal and pressure-related gait parameters. Older adults significantly reduced foot integrated pressure of the leading leg when stepping over the second obstacle compared with young adults (p = .0078). A significantly larger cyclogram intersection point shift in medial-lateral direction was found in older adults than in young adults (p = .024) when stepping over the second obstacle, especially in the lateral direction. The results of this study showed that a pressure-sensing walking combined with cyclogram intersection point method could detect foot pressure distribution differences caused by aging.

Comparisons of Gait Variability and Symmetry in Healthy Runners, Runners with a History of Lower Limb Injuries, and Runners with a Current Lower Limb Injury

Background: Running is a cyclic movement requiring bilateral symmetry between the lower limbs to reduce injury risk. The assessment of side-to-side differences is often performed to detect functional deficits. Objectives: The purpose was to study side-to-side differences using clinical and running performance assessments in healthy runners (HR), runners with a history of lower limb injuries (RHI), and runners with a current lower limb injury (RLI). Methods: Forty-three runners were recruited, with 14 participants being allocated to the HR group, 13 to the RHI group, and 16 to the RLI group. Peak vertical ground reaction force (GRF), midfoot pressure, foot rotation, and gait variability were recorded using a Zebris FDM-T treadmill analysis system. Participants were also assessed using the navicular drop test. Dependent t-tests were used to determine if any differences existed between the lower limbs within each group. One-way ANOVAs were then used to investigate the side-to-side differences between the three groups. Results: Significant differences were seen in navicular drop height between lower limbs within both the HR (P = 0.02) and RHI (P = 0.009) groups, and side-to-side differences in foot rotation were greatest in the RLI group (~34%) compared to both the RHI (~30.5%) and HR (~24%) groups. The lateral variability of the center of pressure was greatest in the RLI group (37.1 mm) compared to the RHI (28.9 mm) and HR (22.2 mm) groups. Conclusions: Variability of butterfly center of pressure diagram may help identify runners at a greater risk of lower limb injury. Side-to-side differences should be expected to progressively decrease from the injured stage, through the recovery and return to sport phases. Target goals of less than 34% side-to-side difference for foot rotation and 37.1 mm for the lateral center of pressure variability may be used to help the decision-making process when considering a return to running practice.

Effect of Executive Dysfunction on Posture Control and Gait after Stroke

Objective

The purpose of the study was to observe the effects of executive dysfunction (ED) on gait and postural control during walking after stroke.

Methods

In this study, 34 subjects with stroke and ED (8 women and 26 men; age, 55.41 ± 7.89 years; time since stroke onset, 1.3 ± 0.12 months) were recruited. Stroop color-word test (SCWT), 10-meter walk test (10MWT), timed-up-and-go test (TUGT), and gait analysis were evaluated. The correlation among the correct number of Stroop tasks (SCWT-C), the number of time-consuming tasks (SCWT-T), the amount of interference (SIE-M and SIE-T) and posture control, and gait-related parameters was analyzed.

Results

The results indicated that SCWT-C was negatively correlated with 10MWT, TUGT, and bilateral symmetry (P < 0.05). However, there was no significant correlation between SCWT-C and stride (P > 0.05). A significant negative correlation was seen between SCWT-C and bilateral symmetry (P < 0.05). There was no significant correlation between SCWT-T and stride (P > 0.05). SCWT-T was positively correlated with TUGT, 10MWT, and bilateral symmetry (P < 0.05). SIE-T was positively correlated with TUGT and bilateral symmetry (P < 0.05). There was no significant correlation between SIE-T and 10MWT or stride (P > 0.05). SIE-M was positively correlated with TUGT and bilateral symmetry (P < 0.05). There was no significant correlation between SIE-T and 10MWT or stride (P > 0.05).

Conclusions

ED is closely related to the decline in postural control and the occurrence of falls. In the early phases of stroke rehabilitation, physiotherapists should focus on the patients' executive function to accelerate the recovery of postural control.

Effekt von Gangjustierhilfen auf die Stabilisierung und Symmetrisierung des Gehens

Hintergrund

Der Mensch hat im Laufe der Evolution den bipedalen Gang, verbunden mit entsprechenden funktionellen und morphologischen Anpassungsprozessen, entwickelt. Eine dieser Entwicklungen ist die Vergrößerung des Calcaneus, der bei korrekter Positionierung zur Verbesserung der Statik des gesamten Fußes beiträgt und in der Folge zu einer Symmetrisierung des Gangbilds führen kann.

Methodik

Um die Hypothese des Einflusses einer ausgelösten Kipprotation auf die Gangstatik zu überprüfen, wurden 29 gesunde, männliche Probanden randomisiert der Kontroll- (K) bzw. Interventionsgruppe (I) zugeordnet und während des Gehens auf einer instrumentierten Gehstrecke untersucht. Beide Gruppen wurden mit baugleichen Schuhen ausgestattet, in die bei der Interventionsgruppe eine seitengleich positionierte Gangjustierhilfe im medialen Rückfußbereich zur Auslösung einer Kipprotation des unteren Sprunggelenks eingebracht wurde. Alle Probanden wurden zu zwei Zeitpunkten im Abstand von 14 Tagen vor (U1, U3) und nach ihrer Arbeitsschicht (Spätschicht; U2, U4) untersucht. Es wurden ausgewählte, bewährte ganganalytische Parameter und die muskuläre Aktivität eines antagonistischen Muskelpaars am Unterschenkel beidseitig erfasst. Die Analyse der Muskelaktivität erfolgte im Seitenvergleich mithilfe von Kokontraktions- und Symmetrieindizes während der mittleren Standphase des Gangzyklus.

Ergebnisse

Die Ganganalyseparameter wiesen für die laterale Verlagerung tendenziell geringere Werte in der Interventionsgruppe auf (U4 K: 4,4, I: 2,3). Für die analysierte Muskelaktivität (Elektromyographie) konnte eine signifikant geringere Seitendifferenz in der Interventionsgruppe nach der Arbeitsschicht identifiziert werden (U4 K: 26,2, I: 13,7, p = 0,02).

Schlussfolgerung

Es ergeben sich deutliche Hinweise darauf, dass die durch die verwendete Gangjustierhilfe erfolgte Beeinflussung des unteren Sprunggelenks zu einer Harmonisierung des Gangbilds beiträgt. Damit können die Stand- und Gangsicherheit verbessert werden.

Predicting Multiple Sclerosis From Gait Dynamics Using an Instrumented Treadmill: A Machine Learning Approach

OBJECTIVE

Multiple Sclerosis (MS) is a neurological condition which widely affects people 50-60 years of age. While clinical presentations of MS are highly heterogeneous, mobility limitations are one of the most frequent symptoms. This study examines a machine learning (ML) framework for identifying MS through spatiotemporal and kinetic gait features.

METHODS

In this study, gait data during self-paced walking on an instrumented treadmill from 20 persons with MS and 20 age, weight, height, and gender-matched healthy older adults (HOA) were obtained. We explored two strategies to normalize data and minimize dependence on subject demographics; size-normalization (standard body size-based normalization) and regress-normalization (regression-based normalization using scaling factors derived by regressing gait features on multiple subject demographics); and proposed an ML based methodology to classify individual strides of older persons with MS (PwMS) from healthy controls. We generalized both across different walking tasks and subjects.

RESULTS

We observed that regress-normalization improved the accuracy of identifying pathological gait using ML when compared to size-normalization. When generalizing from comfortable walking to walking while talking, gradient boosting machine achieved the optimal subject classification accuracy and AUC of 94.3 and 1.0, respectively and for subject generalization, a multilayer perceptron resulted in the best accuracy and AUC of 80% and 0.86, respectively, both with regression-normalized data.

CONCLUSION

The integration of gait data and ML may provide a viable patient-centric approach to aid clinicians in monitoring MS.

SIGNIFICANCE

The results of this study have future implications for the way regression normalized gait features may be clinically used to design ML-based disease prediction strategies and monitor disease progression in PwMS.

A Pressure-Pad-Embedded Treadmill Yields Time-Dependent Errors in Estimating Ground Reaction Force during Walking

Accurate and reliable vertical ground reaction force (VGRF) measurement is essential in various biomechanical and clinical studies. Recently, pressure-pad-embedded treadmills have been widely used for VGRF measurement as a relatively less expensive option than the force platform-mounted treadmills. Prior studies have shown that the popular Zebris treadmill is reliable when used to measure peak VGRF for short walking sessions. However, comprehensive evaluation of human walking requires information of gait parameters over sufficient gait cycles. In this study, we quantify the long-term temporal changes in VGRF values measured by the Zebris treadmill. Twenty participants walked on the treadmill for 10 min twice, with 10 min rest between trials. We found an evident decline in the measured VGRF and impulse over time for both trials. The Zebris system also consistently yielded the lower VGRF values during the second trials. These results indicate that the Zebris treadmill is unreliable in measuring VGRF during walking, and a 10 min break is not enough for the embedded sensors to recover their sensitivity. We provided a way to resolve these time-dependent errors; using the impulse-momentum theorem and collected kinematics of the participants, we formulated a curve-fitting model encapsulating the growing VGRF estimation error.

The application of principal component analysis to characterize gait and its association with falls in multiple sclerosis

People with multiple sclerosis (PwMS) demonstrate gait impairments that are related to falls. However, redundancy exists when reporting gait outcomes. This study aimed to develop an MS-specific model of gait and examine differences between fallers and non-fallers. 122 people with relapsing-remitting MS and 45 controls performed 3 timed up-and-go trials wearing inertial sensors. 21 gait parameters were entered into a principal component analysis (PCA). The PCA-derived gait domains were compared between MS fallers (MS-F) and MS non-fallers (MS-NF) and correlated to cognitive, clinical, and quality-of-life outcomes. Six distinct gait domains were identified: pace, rhythm, variability, asymmetry, anterior-posterior dynamic stability, and medial-lateral dynamic stability, explaining 79.15% of gait variance. PwMS exhibited a slower pace, larger variability, and increased medial-lateral trunk motion compared to controls (p < 0.05). The pace and asymmetry domains were significantly worse (i.e., slower and asymmetrical) in MS-F than MS-NF (p < 0.001 and p = 0.03, respectively). Fear of falling, cognitive performance, and functional mobility were associated with a slower gait (p < 0.05). This study identified a six-component, MS-specific gait model, demonstrating that PwMS, particularly fallers, exhibit deficits in pace and asymmetry. Findings may help reduce redundancy when reporting gait outcomes and inform interventions targeting specific gait domains.

Gait asymmetry, and bilateral coordination of gait during a six-minute walk test in persons with multiple sclerosis

Gait impairments in persons with multiple sclerosis (pwMS) leading to decreased ambulation and reduced walking endurance remain poorly understood. Our objective was to assess gait asymmetry (GA) and bilateral coordination of gait (BCG), among pwMS during the six-minute walk test (6MWT), and determine their association with disease severity. We recruited 92 pwMS (age: 46.6 ± 7.9; 83% females) with a range of clinical disability, who completed the 6MWT wearing gait analysis system. GA was assessed by comparing left and right swing times, and BCG was assessed by the phase coordination index (PCI). Several functional and subjective gait assessments were performed. Results show that gait is more asymmetric and less coordinated as the disease progresses (p < 0.0001). Participants with mild MS showed significantly better BCG as reflected by lower PCI values in comparison to the other two MS severity groups (severe: p = 0.001, moderate: p = 0.02). GA and PCI also deteriorated significantly each minute during the 6MWT (p < 0.0001). GA and PCI (i.e., BCG) show weaker associations with clinical MS status than associations observed between functional and subjective gait assessments and MS status. Similar to other neurological cohorts, GA and PCI may be important parameters to assess and target in interventions among pwMS.

Temporo-spatial and kinetic gait parameters in English setter dogs

Walking analysis systems have begun to be used in veterinary medicine in recent years. The pressure-sensitive walkway is one of the systems through which we can obtain temporo-spatial and kinetic variables of walking. Therefore, the aim of this study was to investigate the walking characteristics of English Setter dogs using a pressure-sensitive system. Twenty-five English Setter dogs were included in the study. Temporo-spatial and kinetic gait parameters were obtained with the pressure-sensitive walkway system. Centre of pressure values were taken separately for the forelimbs and hindlimbs and were statistically analysed. The force values in the forelimb were found to be greater than in the hindlimb during walking. According to the results of dynamic pedobarographic evaluation, the highest-pressure values were found at the 2nd and 3rd digital pads for the forelimbs and on the 3rd and 4th digital pads for the hindlimbs. During the stance, 64.58% of the weight was found to be on the forelimbs. No difference was found between the forelimbs and the hindlimbs in centre of pressure analysis. As conclusion, the gait data obtained from the English Setter dogs can be used in future research to identify animals that may have neurological or orthopaedic problems.

Characterizing intersection variability of butterfly diagram in post-stroke gait using Kernel Density Estimation

BACKGROUND

Center of pressure (COP) trajectory during treadmill walking have been commonly presented using the butterfly diagram to describe gait characteristics in neurologically intact and impaired individuals. However, due to the large amount of displayed information, the butterfly diagram is not an efficient solution to visualize locomotor variability.

PURPOSE

The purpose of this study was to evaluate post-stroke locomotor variability by applying Kernel density estimation (KDE) on the intersections of the butterfly diagram, and to compare KDE derived metrics with conventional metrics of gait symmetry and variability.

METHODS

Bilateral toe-off (TO) and initial contact (IC) points of the butterfly diagram were determined to calculate the COP symmetry index and the intersections of bilateral TOIC. Subsequently, the intersections during the walking window were used to evaluate its density and variability by Kernel density estimation. Standard deviations of step width and step length were compared between groups.

RESULTS

Using the KDE surface plots we observed 4 characteristically different patterns with individuals post-stroke, which were associated with functional status quantified using walking speed and lower extremity Fugl-Meyer scores. However, locomotor variability quantified using standard deviations of step width and lengths did not differ between groups. Significance & Novelty: This paper presents a novel approach of using KDE analysis as a better and more sensitive method to characterize locomotor COP variability in individuals with post-stroke hemiparesis, compared to conventional metrics of gait symmetry and variability.

Gait Recognition via Deep Learning of the Center-of-Pressure Trajectory

The fact that every human has a distinctive walking style has prompted a proposal to use gait recognition as an identification criterion. Using end-to-end learning, I investigated whether the center-of-pressure (COP) trajectory is sufficiently unique to identify a person with high certainty. Thirty-six adults walked for 30 min on a treadmill equipped with a force platform that continuously recorded the positions of the COP. The raw two-dimensional signals were sliced into segments of two gait cycles. A set of 20,250 segments from 30 subjects was used to configure and train convolutional neural networks (CNNs). The best CNN classified a separate set containing 2250 segments with an overall accuracy of 99.9%. A second set of 4500 segments from the six remaining subjects was then used for transfer learning. Several small subsamples of this set were selected randomly and used to fine tune the pretrained CNNs. Training with two segments per subject was sufficient to achieve 100% accuracy. The results suggest that every person produces a unique trajectory of underfoot pressures while walking and that CNNs can learn the distinctive features of these trajectories. By applying a pretrained CNN (transfer learning), a couple of strides seem enough to learn and identify new gaits. However, these promising results should be confirmed in a larger sample under realistic conditions.

Asymmetric dynamic center-of-pressure in Parkinson's disease

BACKGROUND

Gait disturbance gradually worsens as Parkinson's disease (PD) progresses, which significantly affects the quality of life of PD patients. Treadmill-based gait analysis systems can measure gait parameters including the dynamic center-of-pressure (COP) trajectory during ambulation. In this study, we hypothesized that altered dynamic COP changes are new gait characteristics for PD patients.

METHODS

Dynamic COP parameters and classic spatiotemporal parameters were obtained for each patient using a treadmill-based system at the maximal comfortable treadmill speed (MCTS). We compared dynamic COP parameters between 44 PD patients and 31 controls, correlated these parameters with clinical and spatiotemporal data, and adjusted for age and MCTS to determine whether the parameters were independent from the treadmill speed. We also evaluated characteristics of COP parameters in relation to the more and less affected sides in PD patients.

RESULTS

During treadmill walking the length of the COP trajectory in the stance phase was decreased, an effect that was more prominent on the more affected side in PD patients. COP parameters related to this change were significantly altered in patients when compared to controls. Asymmetry of the COP trajectories compared between both feet was identified as a significant gait characteristic after adjusting for age and MCTS. The overlaid graphical display of dynamic COP trajectory in PD patients showed "distorted butterfly with asymmetric wing" feature.

CONCLUSION

Dynamic COP asymmetry provides a new and intuitive way to analyze gait abnormalities of PD patients. Further studies with prospective designs will substantiate the clinical usefulness of this feature of gait.

Identification of spatiotemporal gait parameters and pressure-related characteristics in children with Angelman syndrome: A pilot study

BACKGROUND

Angelman syndrome (AS) leads to clinical manifestations that include intellectual impairments, developmental delay and poor motor function. Initiatives to develop therapeutics implie an urgent need to identify methods that accurately measure the motor abilities.

METHODS

Six children with AS (6 to 9 years old) walked on an instrumented walkway to get spatiotemporal parameters (STPs) and center of pressure (CoP). These outcomes were compared to typically developing children (TD): 44 TD 6 to 9 years old and 20 TD 4 to 5 years old.

RESULTS

Analysis revealed differences in all STPs and gait variability index when compared to TD individuals. When AS participants were compared to younger TD individuals, except step length, STPs were different. Analysis of the CoP pathway revealed a less consistent and efficient pathway in AS.

CONCLUSIONS

We could delineate the functional difference between children with AS and TD children. The variability of STP and the CoP were the most valuable components in gait to be considered in AS.

Repeatability of spatiotemporal, plantar pressure and force parameters during treadmill walking and running

BACKGROUND

Instrumented treadmills with integrated pressure mats measure spatiotemporal, pressure and force parameters and are often used to investigate changes in gait patterns due to injury or rehabilitation.

RESEARCH QUESTION

What is the within- and between-day repeatability of such an instrumented treadmill for spatiotemporal parameters, peak pressures and forces during walking and running?

METHODS

Treadmill gait and running analysis were performed at 5.0, 6.5, and 9.0 km/h in 33 healthy adults (age: 31.6 ± 7.4 years; body mass index: 23.8 ± 3.2 kg/m²) once on day 1 and twice on day 7. For all three speeds, intraclass correlation coefficents (ICC) and smallest detectable differences (SDC) corresponding to 95% limits of agreement were calculated for spatiotemporal parameters and peak pressures and forces in the heel, midfoot, and forefoot regions.

RESULTS

All spatiotemporal parameters and peak forces in the heel, midfoot, and forefoot regions showed a good within- and between-day repeatability (ICCs > 0.878) for all gait speeds with within-day repeatability being generally higher. For peak pressures, only the heel and forefoot regions but not the midfoot region, showed good repeatability (ICC > 0.9) at all gait speeds. SDCs ranged from 1.5 to 2.5° for foot rotation, 4.4 to 6.6 cm for stride length, 0.7 to 2.5% for length of stance phases, and 2.8 to 9.2 N/cm² for peak pressures in all foot regions. For walking, SDCs of peak forces in the heel, midfoot and forefoot regions were below 60 N, and for running below 135 N.

SIGNIFICANCE

Except for peak pressures in the midfoot, spatiotemporal and kinetic gait parameters during walking and running showed a good within- and between-day repeatability. Hence, the investigated treadmill is suitable to analyze gait patterns and changes in gait patterns due to interventions.

The relationship between gait variability and cognitive functions differs between fallers and non-fallers in MS

The objective of the study was to determine if cognitive function is associated with step time variability in people with multiple sclerosis (PwMS). The study included 355 PwMS (218 women), average age 41.1 (SD = 13.5), disease duration 5.9 (SD = 7.3) years, and a median expanded disability status scale score of 2.5. We separately analyzed the sample group of fallers and non-fallers based on their fall history. Gait variability was measured by an electronic walkway and all participants completed a computerized cognitive test battery designed to evaluate multiple cognitive domains. Fallers (43.7%) demonstrated elevated step time variability (%CV), 5.0 (SD = 3.4) vs. 3.5 (SD = 1.6), P < 0.001 compared to the non-faller subjects. According to the regression analysis in the non-fallers' group, step time variability was found significantly associated with the global cognitive score (P = 0.001), executive function subcategory (P = 0.038), and motor skills subcategory (P < 0.001). No relationship between step time variability and any cognitive domain was demonstrated in the faller group. This study illustrated that the association between gait variability and cognition occurs only in PwMS without a fall history. From a clinical standpoint, these findings might help medical professionals to create improved assessment tests and rehabilitation strategies in the MS population.

Cognitive-motor interference in multiple sclerosis: What happens when the gait speed is fixed?

During the last decade, numerous studies have confirmed a coupling between walking performance and cognition in people with multiple sclerosis (PwMS). Our aim was to provide new insights into a walking-cognitive dual-task (DT) in PwMS. We tested the DT phenomenon by controlling the walking speed using an instrumented treadmill. Thirty PwMS (20 women) with a mean age 40.1 (SD=12.0) participated in the study. Twenty-one healthy subjects served as controls. Each subject completed a sequence of tests: a) Normal walking (ST) - the participant walked on the instrumented treadmill at a comfortable walking speed for 1min; b) Cognitive evaluation (ST) - subjects performed two cognitive tests while seated; c) DT cognitive tests performed while walking on the treadmill at the identical speed performed during normal walking. Outcome measures were spatio-temporal parameters of gait (mean and variability), the Word List Generation Test (WLG) and the Serial-3 Subtraction Test. MS participants significantly decreased their cadence while increasing their stride length during the DT condition compared to the ST condition. Non-significant differences were observed for the WLG and Serial-3 Subtraction Cognitive Tests between the ST condition and the DT condition in both the MS and healthy groups. In terms of gait variability parameters, MS subjects demonstrated a 2 to 3-fold greater gait variability compared to the healthy controls. Non-significant differences in gait variability parameters were observed between the ST and DT conditions in both the MS and control groups. This study provides new insights into the DT phenomenon in the MS population.

On Gait Analysis Estimation Errors Using Force Sensors on a Smart Rollator

Gait analysis can provide valuable information on a person's condition and rehabilitation progress. Gait is typically captured using external equipment and/or wearable sensors. These tests are largely constrained to specific controlled environments. In addition, gait analysis often requires experts for calibration, operation and/or to place sensors on volunteers. Alternatively, mobility support devices like rollators can be equipped with onboard sensors to monitor gait parameters, while users perform their Activities of Daily Living. Gait analysis in rollators may use odometry and force sensors in the handlebars. However, force based estimation of gait parameters is less accurate than traditional methods, especially when rollators are not properly used. This paper presents an evaluation of force based gait analysis using a smart rollator on different groups of users to determine when this methodology is applicable. In a second stage, the rollator is used in combination with two lab-based gait analysis systems to assess the rollator estimation error. Our results show that: (i) there is an inverse relation between the variance in the force difference between handlebars and support on the handlebars-related to the user condition-and the estimation error; and (ii) this error is lower than 10% when the variation in the force difference is above 7 N. This lower limit was exceeded by the 95.83% of our challenged volunteers. In conclusion, rollators are useful for gait characterization as long as users really need the device for ambulation.

The use of laboratory gait analysis for understanding gait deterioration in people with multiple sclerosis

Laboratory gait analysis or three-dimensional gait analysis (3DGA), which uses motion capture, force plates and electromyography (EMG), has allowed a better understanding of the underlying mechanisms of gait deterioration in patients with multiple sclerosis (PwMS). This review will summarize the current knowledge on multiple sclerosis (MS)-related changes in kinematics (angles), kinetics (forces) and electromyographic (muscle activation) patterns and how these measures can be used as markers of disease progression. We will also discuss the potential causes of slower walking in PwMS and the implications for 3DGA. Finally, we will describe new technologies and methods that will increase precision and clinical utilization of 3DGA in PwMS. Overall, 3DGA studies have shown that functionality of the ankle joint is the most affected during walking and that compensatory actions to maintain a functional speed may be insufficient in PwMS. However, altered gait patterns may be a strategy to increase stability as balance is also affected in PwMS.

Gait characteristics according to pyramidal, sensory and cerebellar EDSS subcategories in people with multiple sclerosis

Walking deterioration is a common problem in people with multiple sclerosis (PwMS). However, there are only scarce data examining the contribution of specific neurological functional systems on gait performance in multiple sclerosis (MS). Therefore, the objective of the current study was to examine the differences in spatio-temporal parameters of gait according to the pyramidal, cerebellar and sensory functional systems. The cross-sectional study included 289 PwMS with mean disease duration of 8.0 (SD = 8.2) years. Spatio-temporal parameters of gait were studied using an electronic walkway. The sample pool was divided into six groups according to the scores of the pyramidal, cerebellar and sensory functional systems, derived from the expanded disability status scale data. Findings indicated that asymmetry of the step time and asymmetry of the single support were significantly elevated in the pyramidal group compared to the sensory group; 9.4 (SD = 10.6) vs. 3.1 (SD = 6.7), P value = 0.004; 9.3 (SD = 10.4) vs. 2.7 (2.1), P value = 0.001, respectively. Additionally, patients in the pure sensory group walked significantly faster with longer strides and less asymmetry compared to the pyramidal-cerebellar-sensory group. Moreover, patients in the sensory group walked with longer steps/strides and symmetry compared to the patients in the pyramidal-cerebellar group. This study confirms that pyramidal disorders are main contributors of gait impairments in the MS population. Furthermore, patients with sensory impairments have a relatively preserved gait pattern compared to patients affected by the pyramidal system.

The influence of gait speed on the stability of walking among the elderly

Walking speed is a basic factor to consider when walking exercises are prescribed as part of a training programme. Although associations between walking speed, step length and falling risk have been identified, the relationship between spontaneous walking pattern and falling risk remains unclear. The present study, therefore, examined the stability of spontaneous walking at normal, fast and slow speed among elderly (67.5±3.23) and young (21.4±1.31) individuals. In all, 55 participants undertook a test that involved walking on a plantar pressure platform. Foot-ground contact data were used to calculate walking speed, step length, pressure impulse along the plantar-impulse principal axis and pressure record of time series along the plantar-impulse principal axis. A forward dynamics method was used to calculate acceleration, velocity and displacement of the centre of mass in the vertical direction. The results showed that when the elderly walked at different speeds, their average step length was smaller than that observed among the young (p=0.000), whereas their anterior/posterior variability and lateral variability had no significant difference. When walking was performed at normal or slow speed, no significant between-group difference in cadence was found. When walking at a fast speed, the elderly increased their stride length moderately and their cadence greatly (p=0.012). In summary, the present study found no correlation between fast walking speed and instability among the elderly, which indicates that healthy elderly individuals might safely perform fast-speed walking exercises.