Defining the design requirements for an assistive powered hand exoskeleton: A pilot explorative interview study and case series
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
BACKGROUND: Powered hand exoskeletons are an emerging technology that have shown promise in assisting individuals with impaired hand function. A number of hand exoskeleton designs have been described in the literature; however, the majority have not been supported by patient-oriented criteria. OBJECTIVE: The aim of this study was to define preliminary end-user needs and expectations for an assistive hand exoskeleton. STUDY DESIGN: Explorative interview and case series. METHODS: Six clinicians and eight individuals with impaired hand function were interviewed in small groups or individually. A standardized list of questions was used to elicit feedback on specific design criteria or promote the discovery of new criteria. In addition, three participants with impaired hand function returned for a second session where hand characteristics, such as range of motion and force required to flex/extend fingers, were recorded to further quantify design requirements. RESULTS: Interview responses indicated that there was general consensus among participants on criteria relating to important grasp patterns, grip strength, wear time, and acceptable bulk/weight. However, interview responses and hand characteristics also revealed important differences between individuals with impaired hand function. CONCLUSION: Qualitative and quantitative data were collected to develop an understanding of end-user design requirements for assistive hand exoskeletons. Although the data collected were helpful in identifying some preliminary criteria, differences between participants exist and identifying a universal set of criteria applicable across individuals with impaired hand function is challenging. This work reinforces the importance of involving users of rehabilitation technology in the device development process.
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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 | 0.000 |
| 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 it