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

Association between Self-reported Sleep Quality and Single-task Gait in Young Adults: A Study Using Machine Learning

Objective  The objective of the present study was to find biomechanical correlates of single-task gait and self-reported sleep quality in a healthy, young population by replicating a recently published study. Materials and Methods  Young adults ( n  = 123) were recruited and were asked to complete the Pittsburgh Sleep Quality Inventory to assess sleep quality. Gait variables ( n  = 53) were recorded using a wearable inertial measurement sensor system on an indoor track. The data were split into training and test sets and then different machine learning models were applied. A post-hoc analysis of covariance (ANCOVA) was used to find statistically significant differences in gait variables between good and poor sleepers. Results  AdaBoost models reported the highest correlation coefficient (0.77), with Support-Vector classifiers reporting the highest accuracy (62%). The most important features associated with poor sleep quality related to pelvic tilt and gait initiation. This indicates that overall poor sleepers have decreased pelvic tilt angle changes, specifically when initiating gait coming out of turns (first step pelvic tilt angle) and demonstrate difficulty maintaining gait speed. Discussion  The results of the present study indicate that when using traditional gait variables, single-task gait has poor accuracy prediction for subjective sleep quality in young adults. Although the associations in the study are not as strong as those previously reported, they do provide insight into how gait varies in individuals who report poor sleep hygiene. Future studies should use larger samples to determine whether single task-gait may help predict objective measures of sleep quality especially in a repeated measures or longitudinal or intervention framework.

Effects of music therapy intervention on gait disorders in persons with multiple sclerosis: A systematic review of clinical trials

BACKGROUND

Music Therapy (MT) is a unique treatment method for Persons with Multiple Sclerosis (PwMS) that can accelerate their functional recovery. MT has been proven to adjust the gait performance of PwMS in a short period. Its therapeutic effects in gait disorders of PwMS for long-term intervention are also starting to draw interest, but it has yet to be investigated.

AIM

This review aimed to systematically examine the outcomes of PwMS with gait disorders after receiving MT intervention.

METHODS

A systematic review has been performed using several academic databases with keywords such as music therapy, multiple sclerosis, and gait. The study protocol was registered on PROSPERO (CRD42022365668).

RESULTS

A total of 405 studies were initially identified. After applying the inclusion and exclusion criteria, twelve studies were finally included. The results showed that all PwMS received MT intervention with different strategies, and ten studies confirmed that gait disorders of PwMS were effectively improved by MT intervention.

CONCLUSION

Most previous studies focused on the transient effects of MT on the gait performance of PwMS. This review bridges gaps in the long-term intervention of MT on gait disorders of PwMS and offers references for therapists to design treatment plans. According to this review, MT intervention has positive therapeutic effects on gait disorders in PwMS.

The impact of previous musculoskeletal injury on running gait variability: A systematic review

BACKGROUND

Growing evidence suggests that identifying movement variability alterations in pathological vs. healthy gait may further understanding of injury mechanisms related to gait biomechanics; however, in the context of running and musculoskeletal injuries the role of movement variability remains unclear.

RESEARCH QUESTION

What is the impact of a previous musculoskeletal injury on running gait variability?

METHODS

Medline, CINAHL, Embase, Cochrane library and SPORTDiscus were searched from inception until February 2022. Eligibility criteria were (a) included a musculoskeletal injury group, (b) compared running biomechanics data to a control group, (c) measured movement variability for at least one dependent variable, (d) provided a statistical between-group comparison of variability outcomes. Exclusion criteria were neurological conditions impacting gait, upper body musculoskeletal injuries and age < 18 years old. A summative synthesis was performed instead of a meta-analysis due to methodological heterogeneity.

RESULTS

Seventeen case-control studies were included. The most common deviations in variability observed among the injured groups were: (1) high and low knee-ankle/foot coupling variability and (2) low trunk-pelvis coupling variability. Significant (p < 0.05) between-group differences in movement variability were identified in 8 of 11; 73% of studies of runners with injury-related symptoms, and 3 of 7; 43% of studies of recovered or asymptomatic populations.

SIGNIFICANCE

This review identified limited to strong evidence that running variability is altered in adults with a recent history of injury for specific joint couplings only. Individuals with ankle instability or pain employed altered running strategies more often than those who have recovered from injury. Altered variability strategies have been proposed to contribute to future running-related injuries, therefore these findings are relevant to clinicians managing active populations.

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

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

Rhythm and Music-Based Interventions in Motor Rehabilitation: Current Evidence and Future Perspectives

Research in basic and clinical neuroscience of music conducted over the past decades has begun to uncover music’s high potential as a tool for rehabilitation. Advances in our understanding of how music engages parallel brain networks underpinning sensory and motor processes, arousal, reward, and affective regulation, have laid a sound neuroscientific foundation for the development of theory-driven music interventions that have been systematically tested in clinical settings. Of particular significance in the context of motor rehabilitation is the notion that musical rhythms can entrain movement patterns in patients with movement-related disorders, serving as a continuous time reference that can help regulate movement timing and pace. To date, a significant number of clinical and experimental studies have tested the application of rhythm- and music-based interventions to improve motor functions following central nervous injury and/or degeneration. The goal of this review is to appraise the current state of knowledge on the effectiveness of music and rhythm to modulate movement spatiotemporal patterns and restore motor function. By organizing and providing a critical appraisal of a large body of research, we hope to provide a revised framework for future research on the effectiveness of rhythm- and music-based interventions to restore and (re)train motor function.

Application of step and beat alignment approaches and its effect on gait in progressive multiple sclerosis with severe cerebellar ataxia: A proof of concept case study

BACKGROUND

In a case report of a progressive multiple sclerosis with cerebellar impairments, we reported that synchronisation of steps to beats was possible only at -12% of usual walking cadence during 1 minute of walking.

OBJECTIVES AND METHODS

Here, we investigate the effect of synchronisation using two different alignment approaches on the patient's gait pattern over 2 minutes of walking, compared to walking in silence.

RESULTS AND CONCLUSION

This proof of concept showed that the adaptive approach was successful resulting in an improved gait pattern compared to the other conditions, providing preliminary evidence to support a full-scale intervention study.

Neural Entrainment Meets Behavior: The Stability Index as a Neural Outcome Measure of Auditory-Motor Coupling

Understanding rhythmic behavior in the context of coupled auditory and motor systems has been of interest to neurological rehabilitation, in particular, to facilitate walking. Recent work based on behavioral measures revealed an entrainment effect of auditory rhythms on motor rhythms. In this study, we propose a method to compute the neural component of such a process from an electroencephalographic (EEG) signal. A simple auditory-motor synchronization paradigm was used, where 28 healthy participants were instructed to synchronize their finger-tapping with a metronome. The computation of the neural outcome measure was carried out in two blocks. In the first block, we used Generalized Eigendecomposition (GED) to reduce the data dimensionality to the component which maximally entrained to the metronome frequency. The scalp topography pointed at brain activity over contralateral sensorimotor regions. In the second block, we computed instantaneous frequency from the analytic signal of the extracted component. This returned a time-varying measure of frequency fluctuations, whose standard deviation provided our "stability index" as a neural outcome measure of auditory-motor coupling. Finally, the proposed neural measure was validated by conducting a correlation analysis with a set of behavioral outcomes from the synchronization task: resultant vector length, relative phase angle, mean asynchrony, and tempo matching. Significant moderate negative correlations were found with the first three measures, suggesting that the stability index provided a quantifiable neural outcome measure of entrainment, with selectivity towards phase-correction mechanisms. We address further adoption of the proposed approach, especially with populations where sensorimotor abilities are compromised by an underlying pathological condition. The impact of using stability index can potentially be used as an outcome measure to assess rehabilitation protocols, and possibly provide further insight into neuropathological models of auditory-motor coupling.