Lower limb movement asymmetry measurement with a depth camera
Bibliographic record
Abstract
The gait movement seems simple at first glance, but in reality it is a very complex neural and biomechanical process. In particular, if a person is affected by a disease or an injury, the gait may be modified. The left-right asymmetry of this movement can be related to neurological diseases, segment length differences or joint deficiencies. This paper proposes a novel method to analyze the asymmetry of lower limb movement which aims to be usable in daily clinical practice. This is done by recording the subject walking on a treadmill with a depth camera and then assessing left-right depth differences for the lower limbs during the gait cycle using horizontal flipping and registration of the depth images half a gait cycle apart. Validation on 20 subjects for normal gait and simulated pathologies (with a 5 cm sole), showed that this system is able to distinguish the asymmetry introduced. The major interest of this method is the low cost of the material needed and its easy setup in a clinical environment.
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 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) | 0.001 | 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".