Gait termination in individuals with multiple sclerosis

The Effect of Arch Stiffness on the Foot-Ankle Temporal Kinematics during Gait Termination: A Statistical Nonparametric Mapping Study

This study compares foot-ankle temporal kinematics characteristics during planned and unplanned gait termination (PGT and UGT) in subjects with different arch stiffnesses (ASs) based on the statistical nonparametric mapping (SnPM) method. By measuring three-dimensional arch morphological parameters under different loading conditions, 28 healthy male subjects were classified and participated in gait termination (GT) tests to collect metatarsophalangeal (MTP) and ankle-joint kinematics data. The two-way repeated-measures ANOVA using SnPM was employed to assess the impacts of AS on foot-ankle kinematics during PGT and UGT. Our results show that joint angles (MTP and ankle joints) were altered owing to AS and GT factors. The flexible arches hahadve periods of significantly greater MTP and ankle joint angles than those of stiff arches during the stance phase of GT, whereas subjects exhibited significantly smaller ankle and MTP joint angles during UGT. These results add additional insights into the morphological arch biomechanical function, and the comprehensive compensatory adjustment of lower-limb joints during gait stopping caused by unplanned stimulation.

A two-stage disto-proximal braking modality to interrupt gait initiation in healthy adults

The purpose of this investigation was to determine the effect of unexpected gait termination in able-bodied participants during gait initiation on spatiotemporal and stance limb biomechanical parameters. Twenty-one healthy adults took part in this study and were divided into two groups based on the natural anterior or posterior incline of their trunk. Each participant performed 15 random trials of gait initiation: 10 trials with a Go signal and 5 with Go-&-Stop signals. Spatiotemporal parameters were assessed between the Go signal and the first heel contact. Ankle, knee, and hip joint moments were calculated in the sagittal plane. Free moment and impulse were also calculated for the stance limb. Spatiotemporal parameters were not influenced by the mean trunk inclination (p > 0.05), but participants with a forwardly-inclined trunk presented higher hip extension moments (p < 0.05). Unexpected stopping required smaller ankle and knee moments compared to the Go condition (p < 0.05). The hip extension moments appeared to be independent of gait initiation conditions (p > 0.05). The capacity of able-bodied people to interrupt their gait initiation relied on a two-stage disto-proximal braking modality involving explosive motor patterns at the ankle and hip joints. Such a pattern could be altered in vulnerable people, and further studies are needed to investigate this. This study determined a clinical method applicable as a functional protocol to assess and improve the postural control of people suffering from a lack of motor modulation during crucial transient tasks. Such tasks are essential in activities of daily living.

Arch-Support Induced Changes in Foot-Ankle Coordination in Young Males with Flatfoot during Unplanned Gait Termination

Objective: The efficacy of arch orthoses in posture adjustment and joint coordination improvement during steady-state gait is well documented; however, the biomechanical changes of gait sub-tasks caused by arch support (AS), especially during gait termination, are poorly understood. Hence, this study aimed to investigate how the acute arch-supporting intervention affects foot–ankle coordination and coordination variability (CV) in individuals with flatfoot during unplanned gait termination (UGT). Methods: Twenty-five male patients with flatfoot were selected as subjects participated in this AS manipulation study. A motion capture system was used for the collection of the metatarsophalangeal joint (MPJ) and ankle kinematics during UGT. MPJ-Ankle coordination and CV were quantified using an optimized vector coding technique during the three sub-phases of UGT. A paired-sample t-test from the one-dimensional statistical parametric mapping of one-dimensional was applied to examine the data significance. Results: Significant differences for the joint kinematics between non-arch-support (NAS) and AS were exhibited only in the MPJ transverse plane during the middle and later periods of UGT (p = 0.04–0.026). Frontal plane MPJ-ankle coordination under AS during stimulus delay significantly decreased from 177.16 ± 27.41° to 157.75 ± 32.54° compared with under NAS (p = 0.026); however, the coordination pattern had not changed. Moreover, no significant difference was found in the coupling angle variability between NAS and AS in three planes during sub-phases of UGT (all p > 0.5). Conclusions: The detailed intrinsic characteristic of AS induced acute changes in lower extremity segment coordination in patients with mild flatfoot has been recorded. This dataset on foot-ankle coordination characteristics during UGT is essential for explaining foot function and injury prediction concerning AS manipulation. Further studies are expected to reflect lower limb inter-joint coordination during gait termination through the long-term effects of AS orthoses.

Fall Risk Prediction in Multiple Sclerosis Using Postural Sway Measures: A Machine Learning Approach

Numerous postural sway metrics have been shown to be sensitive to balance impairment and fall risk in individuals with MS. Yet, there are no guidelines concerning the most appropriate postural sway metrics to monitor impairment. This investigation implemented a machine learning approach to assess the accuracy and feature importance of various postural sway metrics to differentiate individuals with MS from healthy controls as a function of physiological fall risk. 153 participants (50 controls and 103 individuals with MS) underwent a static posturography assessment and a physiological fall risk assessment. Participants were further classified into four subgroups based on fall risk: controls, low-risk MS (n = 34), moderate-risk MS (n = 27), high-risk MS (n = 42). Twenty common sway metrics were derived following standard procedures and subsequently used to train a machine learning algorithm (random forest - RF, with 10-fold cross validation) to predict individuals' fall risk grouping. The sway-metric based RF classifier had high accuracy in discriminating controls from MS individuals (>86%). Sway sample entropy was identified as the strongest feature for classification of low-risk MS individuals from healthy controls. Whereas for all other comparisons, mediolateral sway amplitude was identified as the strongest predictor for fall risk groupings.

Forensic Gait Analysis and Recognition: Standards of Evidence Admissibility

Gait is one biological characteristic which has attracted strong research interest due to its potential use in human identification. Although almost two decades have passed since a forensic gait expert has testified to the identity of a perpetrator in court, the methods remain insufficiently robust, considering the recent paradigm shift witnessed in the forensic science community regarding quality of evidence. In contrast, technological advancements have taken the lead, and research into automated gait recognition has greatly surpassed forensic gait analysis in terms of the size of acquired datasets and demographic variability of participants, tested variables, and statistical evaluation of results. Despite these advantages, gait recognition presents with different problems which are yet to be resolved. Therefore, courts should treat gait evidence with caution, as they should any other form of evidence originating from disciplines without fully established codes of practice, error rates, and demonstrable applications in forensic scenarios.

Unplanned gait termination in individuals with multiple sclerosis

Despite the pervasive nature of gait impairment in multiple sclerosis (MS), there is limited information concerning the control of gait termination in individuals with MS. The purpose of this investigation was to examine unplanned gait termination with and without cognitive distractors in individuals with MS compared to healthy controls. Thirty-one individuals with MS and 14 healthy controls completed a series of unplanned gait termination tasks over a pressure sensitive walkway under distracting and non-distracting conditions. Individuals with MS were further broken down into groups based on assistive device use: (no assistive device (MS_noAD) n=18; and assistive device (MS_AD) n=13). Individuals with MS who walked with an assistive device (MS_AD: 67.8±15.1cm/s) walked slower than individuals without an assistive device (MS_noAD: 110.4±32.3cm/s, p<0.01) and controls (120.0±30.0cm/s; p<0.01). There was a significant reduction in velocity in the cognitively distracting condition (93.4±32.1cm/s) compared to the normal condition [108.8±36.2cm/s; F(1,43)=3.4, p=0.04]. All participants took longer to stop during the distracting condition (1.7±0.6s) than the non-distracting condition (1.4±0.4s; U=673.0 p<0.01). After controlling for gait velocity, post-hoc analysis revealed the MS_AD group took significantly longer to stop compared to the control group (p=0.05). Further research investigating the control of unplanned gait termination in MS is warranted.

Cognitive Motor Interference in Multiple Sclerosis: Insights From a Systematic Quantitative Review

OBJECTIVE

To synthesize the evidence for differences in cognitive motor interference (CMI) between persons with multiple sclerosis (MS) and those without MS by using systematic review and meta-analysis.

DATA SOURCES

EMBASE, PubMed, ScienceDirect, Scopus, SPORTDiscus, and Web of Science. Our focused literature search was informed by past systematic reviews of CMI during walking in MS.

STUDY SELECTION

The key terms searched included Multiple sclerosis and synonyms of motor function (eg, Gait disorders, Gait, Walking, Balance, or Fall) and motor and cognitive functions (eg, Cognitive motor interference or Thinking).

DATA EXTRACTION

From the 116 abstract-identified articles, 13 experimental studies were selected for the final analysis and were rated using the Quality Assessment of Diagnostic Accuracy Studies tool. A meta-analysis was performed for all considered outcomes.

DATA SYNTHESIS

The results yielded a small overall effect size (ES) of .08 (SE=.17; 95% confidence interval, -.25 to .40; z=.49; P>.05), which indicated a nonsignificant minimal difference in CMI between persons with MS and those without MS. The moderator analysis for motor task (mobility task: ES, .22; postural task: ES, -.11) was not significantly different between persons with MS and those without MS. The moderator analysis for cognitive task (verbal fluency task: ES, .66; mental tracking task: ES, .04; discrimination and decision-making task: ES, -.30) resulted in a significant difference in CMI between persons with MS and those without MS (P<.05).

CONCLUSIONS

We provide evidence that overall there is a minimal difference in CMI between persons with MS and those without MS.