The accuracy of perception of a pinch grip force in older adults
Bibliographic record
Abstract
The fact that humans can execute accurate movements and generate precise muscle forces is very important for hand function. Target-tracking tasks or target-matching tasks are often executed under combined visual and somatosensory feedback. When visual feedback is removed, subjects have to depend on their perception of force. The objective of the present study was to estimate the effects of aging on the perception of a pinch force produced by the thumb and index finger. In a first set of trials, young (n = 12, age = 25.3 +/- 2.4 years) and elderly (n = 12, age = 71.5 +/- 3.3 years) healthy individuals were asked to reproduce pinch forces which were equivalent to 5%, 20%, and 40% of their maximal pinch force (MPF). Prior to the execution of these trials, the subjects were familiarized with the force levels by matching targets displayed on a screen. They were then asked to reproduce each of these forces without any visual or verbal feedback. The results showed a larger error in the reproduced force for the elderly subjects when compared with the young adults. However, this larger error was mainly due to an initial overshoot in the force to be reproduced, followed by a gradual decrease towards the appropriate force. This transient overshoot was rarely seen in the performance of the younger subjects. In a second set of trials, the same subjects were asked to produce a pinch force of 5%, 20%, and 40% of MPF with 1 hand using visual feedback. They were also instructed to simultaneously apply a comparable pinch force with the other hand (without any feedback). For both young and older adults, the pinch forces produced by the 2 hands were the same. In addition, in both blocks of trials, hand dominance had no effects on the performance for all subjects. These results suggest that normal aging affects the production of force based on sensorimotor memory rather more than it affects comparative outputs from central descending commands.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".