Estimation of spatial-temporal hand motion parameters in rehabilitation using a low-cost noncontact measurement system
Why this work is in the frame
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Bibliographic record
Abstract
Data collection and analysis are commonly used in a rehabilitation process to measure performances of the treatment. There is a lack of studies on the rehabilitation process monitored by a user-friendly interface. A low-cost system is developed in this research to assist users and therapists to measure hand motions and analyse important data of hand joints. The system consists of modules of data capturing, data analysis, and user interface. A Leap Motion sensor is used to capture joint positions of hand motions. Signal processing and wavelet de-noising methods are developed to improve accuracy of the data analysis. The user interface is designed using the Unity software to show graphical information of joint positions and motion parameters. The system has features of noncontact measurements, interactive environment, analysing and recording temporal data of motion parameters of hands. The system is validated by a gold standard motion capturing system. Case studies show effectiveness of the proposed system.
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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 | 0.001 | 0.001 |
| 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