Abstract
Traditional Chinese medicine (TCM) is an experienced-based discipline and plays an important role in the current medical system. Digitalizing key features is the best way to con-duct an in-depth analysis of TCM. However, due to its complex generation mechanism, the crucial pulse-taking procedure is hard to be digitalized and analyzed. This article fabricated a flexible piezoelectric sensor to gather data for the pulse-taking procedure. The sensitivity of the proposed flexible sensor reached 0.34 V/kPa, so we adopted peripheral circuits to make its output signals stay in a reasonable range (± 0.5 V) for convenient data collection. We used the sensor to recognize whether a woman is pregnant since it has solid golden standards. The pulse signal was fused via mapping the signal spectrogram into a 3-dimension tensor. The fused matrix was then processed by GoogleNet and reached a 90.48% correction rate. This result shows that the pulse condition has statistical differences, which solidified the objectivity of pulse diagnosis and escalated the TCM's digitalization level. © 2023 The Authors. Engineering Reports published by John Wiley & Sons Ltd.
| Original language | English |
|---|---|
| Article number | e12645 |
| Journal | Engineering Reports |
| Volume | 5 |
| Issue number | 11 |
| Online published | 6 Mar 2023 |
| DOIs | |
| Publication status | Published - Nov 2023 |
Research Keywords
- deep learning
- flexible sensor
- piezoelectrical sensor
- pulse taking
Publisher's Copyright Statement
- This full text is made available under CC-BY 4.0. https://creativecommons.org/licenses/by/4.0/
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