中国组织工程研究

中国组织工程研究 ›› 2012, Vol. 16 ›› Issue (17): 3173-3177.doi: 10.3969/j.issn.1673-8225.2012.17.031

• 数字化骨科 digital orthopedics • 上一篇    下一篇

基于矩阵实验室的无线传输脉象处理系统★

曹晓燕1，雷  勇2，李良刚3   

  1. 1四川大学电气信息学院，四川省成都市  610065；  2成都体育学院运动医学系，四川省成都市  610041
  • 收稿日期:2011-11-10 修回日期:2012-03-10 出版日期:2012-04-22 发布日期:2012-04-22
  • 通讯作者: 雷勇，博士，教授，硕士研生导师，四川大学电气信息学院，四川省成都市 610065 Yonglei@163.com 并列通讯作者：李良刚，博士，教授，硕士生导师，成都体育学院运动医学系，四川省成都市 610041 554905620@qq.com
  • 作者简介:曹晓燕★，女，1986年生，四川省内江市人，汉族，四川大学在读硕士，主要从事医学电子学方面的研究。 caoxiaoyan2012yahoo.cn

Wireless pulse condition identification based on the matrix laboratory  

Cao Xiao-yan1, Lei Yong2, Li Liang-gang3   

  1. 1School of Electrical Engineering and Information, Sichuan University, Chengdu  610065, Sichuan Province, China; 2Department of Sports Medicine, Chengdu Sport University, Chengdu  610041, Sichuan Province, China
  • Received:2011-11-10 Revised:2012-03-10 Online:2012-04-22 Published:2012-04-22
  • Contact: Corresponding author: Lei Yong, Doctor, Professor, Master’s supervisor, School of Electrical Engineering and Information, Sichuan University, Chengdu 610065, Sichuan Province, China Yonglei@163.com Corresponding author: Li Liang-gang, Doctor, Professor, Master’s supervisor, Department of Sports Medicine, Chengdu Sport University, Chengdu 610041, Sichuan Province, China 554905620@qq.com
  • About author:Cao Xiao-yan★, Studying for master’s degree, School of Electrical Engineering and Information, Sichuan University, Chengdu 610065，Sichuan Province, China caoxiaoyan2012yahoo.cn

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摘要：

背景：脉搏波的采集一般都是基于有线的方式，这给测量带来不易移动、不易扩展等不便，同时传统的脉象识别也受到人为经验的限制。
目的：为了弥补有线方式采集脉搏波带来的不便以及传统脉象识别受医生知识及经验的限制，文章提出一种应用无线采集脉搏信号，再应用正态二叉树支持向量机算法对脉象进行分类，以达到脉象无线传输、智能识别的目的。
方法：首先通过HK2000B+集成脉搏传感器采集到脉搏波，经过信号调理电路的处理，采用无线收发模块，将其传输到计算机中，然后应用矩阵实验室软件对采集到脉搏波进行处理后提取脉搏波的时域和频域特征，最后对采集到的160例脉搏信号应用正态二叉树支持向量机算法对平、滑、弦、细4种脉象进行分类识别。
结果与结论：该方法在目前的脉象分类方法中具有较高的分类速率、较低的计算复杂度以及较高的分类正确率，有利于推进脉诊的远程和客观化的实现。
 

关键词: 脉象, 脉搏, 无线模块, 时域和频域, 支持向量机, 智能分类

Abstract:

BACKGROUND: The collection of pulse wave is usually based on cable way, this measure brings inconvenience with what is not easy to move and expand. At the same time, the traditional pulse condition identification also restricted by artificial experience.
OBJECTIVE: In order to make up the inconvenience of the cable acquisition pulse wave and the limitation of traditional pulse condition identification by the doctor’s knowledge and experience, this paper put forward a wireless pulse acquisition and use the improved support vector machine algorithm to classify the pulse condition, in order to achieve the purposes of pulse condition wireless transmission and intelligent identification.
METHODS: Firstly, we used the HK2000B+ integrated pulse sensor to collect the pulse wave, then after the pulse signal disposal circuit processed, transferred it to the computer through the wireless transceiver module, then after the pretreatment by the matrix laboratory software, the time domain and frequency domain feature were picked up. Finally, the 160 cases of pulse were classified into four kinds of pulse condition by improved support vector machine algorithm. The kinds of pulse condition were flat, smooth, string and fine.
RESULTS AND CONCLUSION: The experimental results show that this method has the high classification rate, low complexity and higher classification accuracy in present classification methods. It has an important significance to realize the remote and reveal of the pulse-taking.

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