A Strengthened and Sensorised Custom Silicone Glove for use with an Intelligent Prosthetic Hand
Bibliographic record
Abstract
External gloves for anthropomorphic prosthetic hands protect the mechanisms from damage and ingress of contaminants and can be used to create a pleasing, life-like appearance. The properties of the glove material are the result of a compromise between the resistance to damage and flexibility. Silicone gloves are easier to flex and keep clean, but also more easily damaged. This paper details the use of nanoclay fillers to enhance the properties of silicone, successfully increasing strength whilst maintaining flexibility. The performance of the enhanced silicone is as robust and resistant to tear and puncture as commercial gloves, while being more flexible. This flexibility makes the incorporation of a piezo-electric pressure sensor based on the EEonyx conductive fabric, practical. A sandwich of the cloth and copper fabric creates the sensor, which decreases in resistance with increasing pressure. The sensors are characterised and production variability within the silicone are tested. Three sensors are incorporated into a glove made to fit around a Southampton Intelligent Hand. The hand adapts its grip shape and force depending on the object held. The technology is adaptable and it can be incorporated in a glove produced to fit any prosthetic hand.
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) | 0.000 | 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".