Toward better assistive lower-limb exoskeletons: Insights from stroke survivors through co-design
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Assistive lower-limb exoskeletons (LLEs) have been recognized as promising tools for enhancing physical capacity in stroke survivors. Involving end-users in the early development stages is essential to ensure these technologies meet user needs. Co-design approaches, which actively engage end-users, support this goal. This study aims to (1) evaluate the impact of fatigue on daily living, (2) identify activities that could benefit from LLE assistance, (3) outline design and usability requirements for home-based LLEs, and (4) define physical parameters LLEs should monitor and assess. Discussions were structured using the PERCEPT co-design methodology and thematically analyzed. Four chronic stroke survivors participated in three focus group sessions, each lasting approximately 2 hours. Fatigue was identified as a significant factor in daily life, underscoring the importance of assistive technologies, such as LLEs, to help mitigate exhaustion. Participants recognized LLEs as valuable tools for enhancing physical performance, with benefits for muscle strength, balance, fatigue management, coordination, and general mobility. Design considerations included system modularity, battery efficiency, ease of donning and doffing, and practical needs for daily use. Our findings offer valuable insights into stroke survivors' design and usability concerns regarding LLEs and provide a foundation for advancing the development and adoption of new assistive technologies.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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 it