Towards efficient motor imagery interventions after lower-limb amputation
Bibliographic record
Abstract
BACKGROUND: The therapeutic benefits of motor imagery (MI) are now well-established in different populations of persons suffering from central nervous system impairments. However, research on similar efficacy of MI interventions after amputation remains scarce, and experimental studies were primarily designed to explore the effects of MI after upper-limb amputations. OBJECTIVES: The present comparative study therefore aimed to assess the effects of MI on locomotion recovery following unilateral lower-limb amputation. METHODS: Nineteen participants were assigned either to a MI group (n = 9) or a control group (n = 10). In addition to the course of physical therapy, they respectively performed 10 min per day of locomotor MI training or neutral cognitive exercises, five days per week. Participants' locomotion functions were assessed through two functional tasks: 10 m walking and the Timed Up and Go Test. Force of the amputated limb and functional level score reflecting the required assistance for walking were also measured. Evaluations were scheduled at the arrival at the rehabilitation center (right after amputation), after prosthesis fitting (three weeks later), and at the end of the rehabilitation program. A retention test was also programed after 6 weeks. RESULTS: While there was no additional effect of MI on pain management, data revealed an early positive impact of MI for the 10 m walking task during the pre-prosthetic phase, and greater performance during the Timed Up and Go Test during the prosthetic phase. Also, a lower proportion of participants still needed a walking aid after MI training. Finally, the force of the amputated limb was greater at the end of rehabilitation for the MI group. CONCLUSION: Taken together, these data support the integration of MI within the course of physical therapy in persons suffering from lower-limb amputations.
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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 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".