Force Discrimination Ability of the Human Hand near Absolute Threshold for the Design of Force Feedback Systems in Teleoperations
Bibliographic record
Abstract
Force discrimination ability is an important surgical skill for micro or minimally invasive surgeries. This article analyzes the force perception of the human hand for lowintensity stimuli. Psychophysical experiments were conducted to measure just noticeable differences (JNDs) at four reference forces below 1 N. Reference forces are chosen to be in the range of forces in minimally invasive surgery that do not follow Weber's law. The force discrimination ability of two groups of subjects, surgeons and non-surgeons, is compared. Results demonstrate a superior ability of surgeons in discriminating small forces. The relationship between the JND and stimulus near absolute threshold is modeled. The application of the model in the design of force feedback systems for surgical teleoperation is discussed. In a force augmenting teleoperation system, the force feedback signal is amplified based on the characteristics of the human perception system. Therefore, the degraded human sense of touch at low-intensity forces would be compensated.
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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 | 0.001 |
| 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) | 0.001 | 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".