J4 ›› 2014, Vol. 41 ›› Issue (5): 91-97.doi: 10.3969/j.issn.1001-2400.2014.05.016

• 研究论文 • 上一篇    下一篇

一种利用手指图像测量人体心率的方法

杨增印1;马建峰1;孙聪1;黄德俊1;叶春晓1;陆地群2   

  1. (1. 西安电子科技大学 计算机学院,陕西 西安  710071;
    2. 西安电子科技大学 技术物理学院,陕西 西安  710071)
  • 收稿日期:2013-05-20 出版日期:2014-10-20 发布日期:2014-11-27
  • 通讯作者: 杨增印
  • 作者简介:杨增印(1988-),男,E-mail:lohafr@163.com.
  • 基金资助:

    国家自然基金委员会-广东联合基金重点基金资助项目(U1135002);国家科技部重大专项资助项目(2011ZX03005-002);陕西省自然科学基础研究计划资助项目(2013JQ8036);中央高校基本科研业务费资助项目(JY10000903001, JB140309);长江学者和创新团队发展计划资助项目(IRT1078);大学生创新性训练计划资助项目(201210701058);国家自然科学基金资助项目(61303033)

Measurement of human heart rate using finger pictures

YANG Zengyin1;MA Jianfeng1;SUN Cong1;HUANG Dejun1;YE Chunxiao1;LU Diqun2   

  1. (1. School of Computer Science and Technology, Xidian Univ., Xi'an  710071, China;
    2. School of Technical Physics, Xidian Univ., Xi'an  710071, China)
  • Received:2013-05-20 Online:2014-10-20 Published:2014-11-27
  • Contact: YANG Zengyin

摘要:

在智能手机上,仅利用手机摄像头采集手指颜色的变化图像,实现人体心率的测量.采用图像频谱分割法对采集的手指图像进行滤波,结合3种像素包含的信息及包含的信息的差异性, 利用3种像素功率密度谱加权计算出光电容积脉搏波.通过相隔点检测波峰法检测光电容积脉搏波信号,测出人体心率.将测量结果与标准仪器测量结果进行对比,平均误差为1.82%, 与真实值的相关系数大于90%,证明了从手指图像测量出人体心率参数的可靠性.将该测量方法应用到手机上,能极大地方便慢性病人对自己健康状态的监控.

关键词: 数字图像处理, 光电容积脉搏波, 图像频谱分割, 智能手机, 心率

Abstract:

On the smart phone, a phone camera is used to capture finger images to achieve heart rate measurements. First, we apply the spectrum division method to filter the collected finger images,and then use the weighted power density spectrum of the three pixel to calculate the PPG (PhotoPlethysmoGraphy), based on the information and its differences contained in the three pixels. Then we apply the peak detection method based on the detection of the separated PPG signal to measure the heart rate.Comparing the measured results and the standard results, the average error is 1.82%, and the correlation of the true value is greater than 90%, indicating the reliability of heart rate measurement on finger images. The application of the method can greatly facilitate the convenience of chronic disease monitoring.

Key words: digital image processing, photo plethysmo graphy, image spectrum segmentation, smartphone, heart rate