Microprocessor knee versus non-microprocessor knee for backup device in lower limb prostheses: A qualitative study
Bibliographic record
Abstract
LAY SUMMARY Current policy in the Canadian Armed Forces (CAF) and Veterans Affairs Canada (VAC) is to provide individuals with an amputation through or above the knee with a prosthesis with a microprocessor knee (MPK) unit for daily use and a backup prosthesis with a non-microprocessor knee (N-MPK) unit. These knee units have significant functional differences. The purpose of this study was to gain an understanding of users’ device preference and the impact of switching between the MPK and N-MPK. To study this, six members participated in semi-structured interviews. Analysis found seven major categories driving prosthetic preference: functionality, physical aspects, mental aspects, activity, maintenance, safety, and health-related quality of life. The MPK was superior in all categories, and immediate switching between devices was problematic. As a result, participants who had an N-MPK backup did not use the device and instead received a loaner MPK from their prosthetist when required. These results suggest that for individuals who do not have ready access to their prosthetist to obtain a loaner knee unit, consideration should be given for a backup prosthesis with the same MPK unit as their daily-use prosthesis. Otherwise, no routine need for a backup N-MPK was identified.
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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 | 0.014 | 0.018 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.007 | 0.007 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.002 |
| 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".