EasiCPRS: design and implementation of a portable Chinese pulse-wave retrieval system

  • Authors:
  • Jingjing Zhang;Rui Wang;Shilong Lu;Jibing Gong;Ze Zhao;Haiming Chen;Li Cui;Nanyue Wang;Youhua Yu

  • Affiliations:
  • Institute of Computing Technology, Chinese Academy of Sciences, Beijing, China;Institute of Computing Technology, Chinese Academy of Sciences, Beijing, China;Institute of Computing Technology, Chinese Academy of Sciences, Beijing, China;Institute of Computing Technology, Chinese Academy of Sciences, Beijing, China;Institute of Computing Technology, Chinese Academy of Sciences, Beijing, China;Institute of Computing Technology, Chinese Academy of Sciences, Beijing, China;Institute of Computing Technology, Chinese Academy of Sciences, Beijing, China;Experimental Research Center, Chinese Academy of Chinese Medical Science, Beijing, China;Experimental Research Center, Chinese Academy of Chinese Medical Science, Beijing, China

  • Venue:
  • Proceedings of the 9th ACM Conference on Embedded Networked Sensor Systems
  • Year:
  • 2011

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Abstract

Traditional Chinese Pulse Diagnosis is a convenient and noninvasive method for disease diagnosis and healthcare. We have designed and implemented a Chinese wrist-pulse retrieval system based on the principle of Traditional Chinese Pulse Diagnosis (TCPD), called EasiCPRS. It is designed to be small in size, low in cost, with flexibility in deployment, and simplicity in operation. The contributions of this work are: 1. The wrist-pulse at "cun, guan and chi"points over the radial artery are obtained by applying a moderate and adjustable taking pressure during wrist-pulse retrieval. 2. A wrist-pulse signal conditioning circuit and a robust external taking pressure control algorithm are designed to overcome low signal-to-noise ratio (SNR). 3. A lightweight algorithm for wrist-pulse feature extraction is achieved on a resource-constrained platform to economize energy and bandwidth. We developed EasiCPRS prototype, trained and verified the performance of the system by collecting and analyzing thousands of wrist-pulse samples from volunteers in a number of different health conditions such as hypertension, pregnancy and so on which were diagnosed by doctors in hospital. The experimental results showed potential usefulness of the system in disease diagnosis and healthcare.