Mobility function of a prosthetic knee joint with an automatic stance phase lock
Bibliographic record
Abstract
BACKGROUND: There is a need for a prosthetic knee joint design that is technologically and functionally appropriate for use in developing countries. OBJECTIVES: To develop and clinically evaluate a new type of stance phase controlled prosthetic knee joint that provides stance phase stability without inhibiting swing phase flexion. STUDY DESIGN: A crossover repeated measures study design comparing the new knee joint to the participant's conventional low- or high-end prosthetic knee joint. METHODS: The new knee joint was fitted to fourteen individuals aged 15 to 67 years with unilateral lower limb amputations. Walk tests were performed to measure walking speed. Energy expenditure was estimated using the physiological cost index (PCI). RESULTS: Walking speeds with the new knee joint were on average 0.14 m/s faster than conventional low-end knees (p < 0.0001), but 0.07 m/s slower than conventional high-end prosthetic knees (p = 0.008). The PCI was similar across all three knee joint technologies (p = 0.276). CONCLUSIONS: Mobility function with the new knee joint, in terms of walking speed, was more closely matched to high-end than low-end prosthetic knee joints. Therefore, given its relatively simple design, the new stance phase control mechanism may offer a functional and cost effective solution for active transfemoral amputees. CLINICAL RELEVANCE: This paper describes a new type of prosthetic knee joint mechanism that is intended to be cost-effective while providing high-level stance phase function to active individuals with a transfemoral amputation. Initial clinical testing suggests that the new knee joint may have some functional advantages over existing technologies in this category.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.002 |
| 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) | 0.003 | 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".