Design priorities for an at-home upper limb stroke rehabilitation robot
Bibliographic record
Abstract
OBJECTIVE: The design of at-home stroke rehabilitation robots must be closely linked to the needs of users, especially stroke survivors and therapists, to ensure that such designs are effective in the home environment, which is less controlled than clinical environments. Translating user needs into the technical descriptors of a design is essential to this design process. This paper analyses user needs identified from interviews with stroke survivors and therapists in previous work. METHODS: The relationship between user needs and the broad technical properties of rehabilitation robot design are related using the House of Quality, an approach from Quality Function Deployment. Technical benchmarks are identified from previous rehabilitation robot designs and technical priorities are determined from the House of Quality. An at-home upper limb stroke rehabilitation robot concept for supporting therapy activities in a vertical planar workspace is described and evaluated using the identified technical priorities. IMPACT: The proposed design, a constrained cable robot, is determined to be appropriate for the desired application based on the technical priorities from the House of Quality.
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How this classification was reachedexpand
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 | 0.001 | 0.007 |
| 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 | 0.003 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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 teacher head, 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".