The effects of long-term FES-assisted walking on intrinsic and reflex dynamic stiffness in spastic spinal-cord-injured subjects
Bibliographic record
Abstract
The effects of long-term functional electrical stimulation (FES)-assisted walking on ankle dynamic stiffness were examined in spinal cord-injured (SCI) subjects with incomplete motor function loss. A parallel-cascade system identification method was used to identify intrinsic and reflex contributions to dynamic ankle stiffness at different ankle positions while subjects remained relaxed. Intrinsic stiffness dynamics were well modeled by a linear second-order model relating intrinsic torque to joint position. Reflex stiffness dynamics were accurately described by a linear third-order model relating halfwave rectified velocity to reflex torque. We examined four SCI subjects before and after long-term FES-assisted walking (> 16 mo). Another SCI subject, who used FES for only five months was examined 12 mo latter to serve as a non-FES, SCI control. Reflex stiffness decreased in FES subjects by an average of 53% following FES-assisted walking, intrinsic stiffness also dropped by 45%. In contrast, both reflex and intrinsic stiffness increased in the non-FES, SCI control. These findings suggest that FES-assisted walking may have therapeutic effects, helping to reduce abnormal joint stiffness.
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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 | 0.000 | 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 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".