Development of a Bracelet With Strain-Gauge Matrix for Movement Intention Identification in Traumatic Amputees
Bibliographic record
Abstract
Myoelectric prosthesis is an electronic device designed to mimic human anatomy and to replace a missing body part for an amputee. Today some prostheses can provide the users with several degrees of freedom. But the major challenges in their design remain related to the control of such devices using a variety of sensors. Regarding this aspect, strain gauges are considered of great interest for strain measurements on the human body for their simplicity, availability, and low cost. Therefore, the use of these strain gauges to identify movement intentions could allow one to design innovative myoelectric prostheses, which would be robust, simple, and less expensive in comparison to using electromyography. Nevertheless, to our knowledge, identifying the movement intentions using strain gauge measurements has yet to be explored. The objective of this paper is to develop a sensor and a method capable of identifying the intentions of the upper limb movements. The developed sensor is a silicone bracelet equipped with a matrix of 16 strain gauges. The small skin deformations were measured by the proposed bracelet and then classified to identify the intentions of movements. A test was performed on one adult female, who underwent amputation of the left forearm (traumatic transhumeral amputee), equipped with the bracelet placed on her upper arm while performing upper limb motions (flexion and extension). The results showed that all studied movements were adequately identified. Specifically, the elbow flexion/extension was identified in 96% of the cases.
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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) | 0.000 | 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 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".