Mechanical design of a new device to assist eating in people with movement disorders
Bibliographic record
Abstract
Many people living with neurological disorders, such as cerebral palsy, stroke, muscular dystrophy or dystonia, experience upper limb impairments (muscle spasticity, loss of selective motor control, muscle weakness or tremors) and are unable to eat independently. This article presents the development of a new device to assist with eating, aimed at stabilizing the movement of people who have movement disorders. The design was guided by insights gathered through focus groups, with occupational therapists and engineers, about the challenges faced by individuals who have movement disorders and difficulty in eating autonomously. The proposed assistive device prototype is designed to be fixed on a table and to support a spoon. The mechanism is designed so that the spoon maintains a position parallel to the ground for the user. Dampers and inertia allow stabilizing the user's motion. A preliminary trial with five individuals living with cerebral palsy is presented to assess the prototype's performance and to guide future iterations of the prototype. Task completion time generally decreased and movement fluidity generally improved when using the assistive device prototype. The prototype showed good potential in stabilizing the spoon for the user and improving movement fluidity.
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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) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".