Flexible piezoelectric sensor for pregnant recognition based on the pulse‐taking procedure in traditional Chinese medicine

Abstract

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.

Keywords

• deep learning
• flexible sensor
• piezoelectrical sensor
• pulse taking