Effect of Training Exercises Incorporating Mechanical Devices on Fatigue and Gait Pattern in Persons with Relapsing-Remitting Multiple Sclerosis
Bibliographic record
Abstract
Purpose: The aim of this study was to evaluate the effects of regular exercise incorporating mechanical devices on fatigue, gait pattern, mood, and quality of life in persons with relapsing-remitting multiple sclerosis (RRMS). Method: A total of 55 individuals with RRMS with an Expanded Disability Status Scale (EDSS) score of 0–4.5 and a Fatigue Severity Scale (FSS) score of 4.0 or more were randomly assigned to one of two exercise groups or a control group (n=18). Exercise programmes used aerobic, body weight, coordination, and balance exercises with either whole-body vibration (WBV; n=19; drop-outs, n=3) or the Balance Trainer system (n=18; drop-outs, n=4). Outcome measures included the FSS, Modified Fatigue Impact Scale (MFIS), Beck Depression Inventory (BDI-II), and Multiple Sclerosis International Quality of Life (MusiQoL). Spatiotemporal gait parameters were assessed using the GAITRite electronic walkway. Pre- and post-intervention assessments were performed by a blinded assessor. Intra- and inter-group analysis was performed, using the paired-samples t-test, by calculating the effect size with Cohen's d analysis and one-way analysis of variance, respectively. Results: Significant improvements in fatigue and mood were identified for both intervention groups (p<0.05). Gait parameters also improved significantly in the WBV group: velocity and step length increased (12.8% and 6.5%, respectively; p<0.005), and step time, stance time, double support time, and step length asymmetry decreased (–5.3%, –1.4%, –5.9%, and –43.7%, respectively; p<0.005). Conclusions: The results of this study support the hypothesis that combined training programmes help to reduce fatigue and improve mood in persons with mild to moderate RRMS. WBV combined with a standard exercise programme significantly improves spatiotemporal gait parameters.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".