Yu Jiangjun, Zhou Liang, Liu Zhaohui, Li Zhiguo, Shan Qiusha
Xi'an Institute of Optics and Precision Mechanics, Chinese Academy of Sciences, Xi'an 710119, P.R.China;University of Chinese Academy of Sciences, Beijing 100049, P.R.China.
Xi'an Institute of Optics and Precision Mechanics, Chinese Academy of Sciences, Xi'an 710119, P.R.China.
Sheng Wu Yi Xue Gong Cheng Xue Za Zhi. 2020 Feb 25;37(1):150-157. doi: 10.7507/1001-5515.201901038.
In order to solve the saturation distortion phenomenon of R component in fingertip video image, this paper proposes an iterative threshold segmentation algorithm, which adaptively generates the region to be detected for the R component, and extracts the human pulse signal by calculating the gray mean value of the region to be detected. The original pulse signal has baseline drift and high frequency noise. Combining with the characteristics of pulse signal, a zero phase digital filter is designed to filter out noise interference. Fingertip video images are collected on different smartphones, and the region to be detected is extracted by the algorithm proposed in this paper. Considering that the fingertip's pressure will be different during each measurement, this paper makes a comparative analysis of pulse signals extracted under different pressures. In order to verify the accuracy of the algorithm proposed in this paper in heart rate detection, a comparative experiment of heart rate detection was conducted. The results show that the algorithm proposed in this paper can accurately extract human heart rate information and has certain portability, which provides certain theoretical help for further development of physiological monitoring application on smartphone platform.
为了解决指尖视频图像中R分量的饱和失真现象，提出一种迭代阈值分割算法，该算法自适应生成R分量的待检测区域，并通过计算待检测区域的灰度均值来提取人体脉搏信号。原始脉搏信号存在基线漂移和高频噪声，结合脉搏信号特点，设计了零相位数字滤波器滤除噪声干扰。在不同智能手机上采集指尖视频图像，采用本文提出的算法提取待检测区域。考虑到每次测量时指尖压力不同，对不同压力下提取的脉搏信号进行了对比分析。为验证本文提出算法在心率检测中的准确性，进行了心率检测对比实验。结果表明，本文提出的算法能够准确提取人体心率信息，具有一定的便携性，为智能手机平台上生理监测应用的进一步发展提供了一定的理论帮助。
