Interactive virtual feedback improves gait motor imagery after spinal cord injury: An exploratory study
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
PURPOSE: Motor imagery can improve motor function and reduce pain. This is relevant to individuals with spinal cord injury (SCI) in whom motor dysfunction and neuropathic pain are prevalent. However, therapy efficacy could be dependent on motor imagery ability, and a clear understanding of how motor imagery might be facilitated is currently lacking. Thus, the aim of the present study was to assess the immediate effects of interactive virtual feedback on motor imagery performance after SCI. METHODS: Nine individuals with a traumatic SCI participated in the experiment. Motor imagery tasks consisted of forward (i.e. simpler) and backward (i.e. more complex) walking while receiving interactive versus static virtual feedback. Motor imagery performance (vividness, effort and speed), neuropathic pain intensity and feasibility (immersion, distraction, side-effects) were assessed. RESULTS: During interactive feedback trials, motor imagery vividness and speed were significantly higher and effort was significantly lower as compared static feedback trials. No change in neuropathic pain was observed. Adverse effects were minor, and immersion was reported to be good. CONCLUSIONS: This exploratory study showed that interactive virtual walking was feasible and facilitated motor imagery performance. The response to motor imagery interventions after SCI might be improved by using interactive virtual feedback.
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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 | 0.002 |
| Scholarly communication | 0.000 | 0.001 |
| 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 it