Body‐Integrated Ultrasensitive All‐Textile Pressure Sensors for Skin‐Inspired Artificial Sensory Systems
Why this work is in the frame
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Bibliographic record
Abstract
Tactile sensing plays a vital role in human somatosensory perception as it provides essential touch information necessary for interacting with the environment and accomplishing daily tasks. The progress in textile electronics has opened up opportunities for developing intelligent wearable devices that enable somatosensory perception and interaction. Herein, a skin‐inspired all‐textile pressure sensor (ATP) is presented that emulates the sensing and interaction functions of human skin, offering wearability, comfort, and breathability. The ATP demonstrates impressive features, including ultrahigh sensitivity (1.46 × 10 6 kPa −1 ), fast response time (1 ms), excellent stability and durability (over 2000 compression‐release cycles), a low detection limit of 10 Pa, and remarkable breathability (93.2%). The multipixel array of ATPs has been proven to facilitate static and dynamic mapping of spatial pressure, as well as pressure trajectory monitoring functions. Moreover, by integrating ATP with oscillation circuits, external force stimuli can be directly encoded into digital frequency pulses that resemble human physiological signals. The frequency of output pulses increases with the applied pressure. Consequently, an ATP‐based artificial sensory system is constructed for intelligent tactile perception. This work provides a simple and versatile strategy for practical applications of wearable electronics in the fields of robotics, sports science, and human–machine interfaces technologies.
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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 | 0.000 | 0.000 |
| 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) | 0.000 | 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