A foot drop compensation device based on surface multi-field functional electrical stimulation—Usability study in a clinical environment
Bibliographic record
Abstract
INTRODUCTION: Functional electrical stimulation applies electrical pulses to the peripheral nerves to artificially achieve a sensory/motor function. When applied for the compensation of foot drop it provides both assistive and therapeutic effects. Multi-field electrodes have shown great potential but may increase the complexity of these systems. Usability aspects should be checked to ensure their success in clinical environments. METHODS: We developed the Fesia Walk device, based on a surface multi-field electrode and an automatic calibration algorithm, and carried out a usability study to check the feasibility of integrating this device in therapeutic programs in clinical environments. The study included 4 therapists and 10 acquired brain injury subjects (8 stroke and 2 traumatic brain injury). RESULTS: Therapists and users were "very satisfied" with the device according to the Quebec User Evaluation of Satisfaction with Assistive Technology scale, with average scores of 4.1 and 4.2 out of 5, respectively. Therapists considered the Fesia Walk device as "excellent" according to the System Usability Scale with an average score of 85.6 out of 100. CONCLUSIONS: This study showed us that it is feasible to include surface multi-field technology while keeping a device simple and intuitive for successful integration in common neurorehabilitation programs.
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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 | 0.001 | 0.006 |
| 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 | 0.001 |
| 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".