Changes in synergy of transtibial amputee during gait: A pilot study
Bibliographic record
Abstract
The number of lower limb amputations is increasing significantly in developed countries. The knowledge of muscle synergy in subjects with loss of muscles could help to understand the general neural strategy underlying muscle coordination in walking. The aim of this study was to investigate the differences in healthy subject's dominant leg, amputee's intact leg (IL) and the amputee's prosthetic leg (PL) muscles using synergy analysis. Concatenated non-negative matrix factorization (CNMF) was performed to divide the surface electromyography (sEMG) data obtained from 6 upper knee and 4 shank muscles into muscle synergy (S) and activation coefficient profile (C) during walking. The difference in S showed low to high correlations inter-subjectively. The high correlation suggests that the central nervous system (CNS) activates the same groups of muscles synergistically. Amputee's muscle alterations due to inadequate proprioceptive feedback, weight bearing deficiency in PL and prosthesis type could lead to a low correlation in S between groups. The C showed to be statistically significantly different in some regions of the gait cycle (GC). These findings could provide valuable information for rehabilitation purposes and development of a synergy-based controller from sEMG for future generations of prostheses.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.002 | 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 source (direct Gemma or distilled Codex), 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".