Effect of kinesthetic force feedback and visual sensory input on writer's cramp
Bibliographic record
Abstract
Writer's cramp, a task specific dystonia is felt to be a disorder of sensorimotor integration involving the basal ganglia and cortex. Motivated by this fact, in the present study we investigated the effects of haptic and visual sensory inputs on cramp severity and frequency during a trial. For this goal seven subjects with writer's cramp disease were asked to perform the trial, which included writing, hovering, and spiral/sinusoidal drawing subtasks. The trial had three major steps namely: A) normal writing, when the patients write without sensory manipulation, B) robotics-assisted writing, when a haptic device supports the pen and provides a compliant writing surface with the goal of manipulating the kinesthetic haptic input, and C) blindfolded writing, when the patients were asked to write while being blindfolded, with the goal of analyzing the potential effects of vision feedback in sensorimotor integration pathway. The number of cramps that occurred and subjective measures of patient feedback about cramp severity were analyzed. The results show that reducing the writing surface rigidity, and blocking vision feedback while writing, changes the cramp pattern and decreases the overall cramp severity.
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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 | 0.002 |
| 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) | 0.002 | 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".