Sensor systems for lower limb functional electircal stimulation (FES) control
Bibliographic record
Abstract
Two sensor systems comprising clusters of accelerometers, magnetic sensors, a rate gyroscope, and a strain gauge were designed. For one system, the clusters were located at the belt and AFO. In the other system, the clusters were located at the AFO and the thigh. The maximum cluster size was 14 cm(3) and 75 g. The clusters of each sensor system were interconnected by a single flexible wire bus, which minimized the effects of cabling. The sensors detected five phases of normal gait to a resolution of 40 ms in an able bodied test. Using a threshold method, the sensor system repeatedly predicted an incipient knee buckle in a paraplegic individual by a minimum of 30 ms. One system detected knee flexion angle analytically to an accuracy of 3.2 degrees during sit to stand trials. The second system determined knee and hip flexion angle to an accuracy of 3.8 degrees during sit to stand trials through neural networks. The signal processing of the acquired sensor signals in each system was performed on a MC68332 microcomputer in conjunction with the data sampling, and suggested the possibility for each sensor system to be used in real time control of FES.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 0.002 |
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".