Human tactile perception as a standard for artificial tactile sensing—a review
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
In this paper, we examine the most important features of human skin tactile properties with special emphasis on the characteristics which are vital in the design of artificial systems. Contrary to the visual and auditory senses, the touch signal is not a well-defined quantity. As a result, the researchers of this field are still dealing with the basics of collecting the most relevant data. Following this, mimicking the sense of touch by producing artificial tactile skin is a challenging process. Although the sense of touch is widely distributed all over the human body, the tactile perception in the human hand is of great importance in terms of surgical and medical robotics applications. In this study, the role of various mechanoreceptors in the human hand, such as, RA, SA I, SA II, and PC units are discussed in relation to the stimuli like force, position, softness, and surface texture. Taking human hand as a suitable tactile model, the necessary engineering features of an artificial tactile sensor, such as, spatial and temporal resolutions, force sensitivity, and linearity, are being reviewed. In this work, we also report on the current and possible future applications of tactile sensors in various surgical procedures.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 it