Student Competition (Knowledge Generation) ID 1973368
Bibliographic record
Abstract
Background Individuals with an incomplete spinal cord injury (iSCI) have increased risk of falls during walking and standing. Our previous longitudinal pilot study demonstrated that a therapeutic system (FES+VFT system) using functional electrical stimulation (FES) and visual feedback training (VFT) improved the standing balance of individuals with iSCI. Purpose This study investigated the orthotic and acute therapeutic effects of FES in the FES+VFT system. Participants Fifteen individuals with iSCI will be recruited for this study. To date, four participants have completed the study. Methods The four participants completed three different sessions. In the first session, participants were evaluated for their balance, postural control and familiarized with the FES+VFT system. In the second and third sessions, the participant completed training sessions with the FES+VFT system with or without FES. Centre of pressure (COP) data were collected via force platforms. Before and after the training, the motor evoked potentials (MEP) of the soleus and tibialis anterior muscles were recorded. Results There was a greater increase in the total dynamic range of the COP with FES+VFT than VFT (Anterior posterior: increase of 17.5 ± 14.27mm, medial lateral: increase of 17.9 ± 19.45mm). Both the soleus and tibialis anterior muscles showed greater increases in MEP after FES+VFT than VFT (Soleus: 70.4 ± 31.1% vs 5.45 ± 29.1%; Tibialis Anterior: 115.3 ± 234.8% vs 11.0 ± 42.9%). Conclusions These findings suggest that FES improves the performance of VFT (positive orthotic effect) and increases the corticospinal connection (positive acute therapeutic effect) in individuals with iSCI.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.953 | 0.887 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".