Mechanomyography sensor design and multisensor fusion for upper-limb prosthesis control
Bibliographic record
Abstract
Current electromyography (EMG) sensors have not been successfully combined with more comfortable and functional silicone soft sockets in externally powered prostheses due to contact, wire breakage and daily use issues. To overcome those issues, this thesis proposes a novel control framework based on the measurement of the mechanical activity of remnant muscles (mechanomyography or MMG). This document details the technical implementation, design optimization and practical tests that lay the groundwork for the development of a new generation of MMG-driven upper-limb externally powered prosthesis. Fundamental contributions include a systematic characterization and optimization of silicone-embedded sensors for MMG signal recording, the novel design of a coupled MMG sensor pair for dynamic noise reduction and the first ever reported use of a MMG sensor array for the generation of multiple signals for prosthesis control. Tests with amputees demonstrate that MMG-driven prostheses may advance the frontier of externally powered prostheses research.
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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 | 0.000 | 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 | 0.001 | 0.001 |
| 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 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".