Design and evaluation of an independent 4‐week, exosuit‐assisted, post‐stroke community walking program
Bibliographic record
Abstract
Chronic impairment in the paretic ankle following stroke often requires that individuals use compensatory patterns such as asymmetric propulsion to achieve effective walking speeds needed for community engagement. Ankle exosuit assistance can provide ankle biomechanical benefit in the lab, but such environments inherently limit the amount of practice available. Community walking studies without exosuits can provide massed practice and benefit walking speed but are limited in their ability to assist proper mechanics. In this study, we combined the positive aspects of community training with those of exosuit assistance. We developed and evaluated a community Robotic Exosuit Augmented Locomotion (cREAL) program. Four participants in the chronic stage of stroke independently used our community ankle exosuit for walking in the community 3-5 days/week for 4 weeks. We performed lab evaluations before and after the 4-week program. Two participants significantly improved their unassisted paretic propulsion by an average of 27% after the program and walked on average 4001 steps/day more in the week following the program. Despite the small number of participants, this study provides preliminary evidence for the potential of exosuits to augment gait training and rehabilitation in the community.
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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 | 0.006 | 0.004 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".