An Intelligent Wristband for Simultaneous Multiparameter Measurement during Fumigation and Washing Therapy of Traditional Chinese Medicine
Why this work is in the frame
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Bibliographic record
Abstract
Traditional Chinese medicine (TCM) is one of the oldest healing systems, which plays an essential role in daily health management. However, TCM is frequently controversial due to its subjectivity and lack of scientific quantification. Modern sensing technologies, enabling the detection of various physiological signals, have the remarkable performance of multifunctionality, superintegration, and ultraminiaturization. Combining with modern sensing technology is a good opportunity for the modernization, objectification, and scientization of TCM. This article proposes an intelligent wristband for simultaneous multiparameter measurement of pulse, skin temperature, and perspiration, essential physiological signals in TCM. As a significant functional material, a carbon nanotube/poly(dimethylsiloxane) nanocomposite with 3D interpenetrating network structures exhibits great electrical conductivity, stress effect, and thermoresistive effect, ensuring intelligent wristband's high accuracy, high sensitivity, and good stability for pulse and temperature measurements. Furthermore, the perspiration sensing unit is also integrated. The as‐prepared intelligent wristband is applied during fumigation and washing therapy, and artificial intelligence is introduced to judge whether the user is during fumigation and washing therapy or in the resting state by classifying the user's physiological state, with an accuracy of up to 100%. This work offers a unique strategy for TCM and wearable sensing technology with an important practical significance.
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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 | 0.001 |
| 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) | 0.000 | 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