基于指尖视频图像的自适应脉搏信号提取算法研究

Research on adaptive pulse signal extraction algorithm based on fingertip video image

针对手指视频图像R分量饱和失真现象,本文提出了一种基于迭代的阈值分割算法,自适应生成R分量待检测区域,通过计算待检测区域灰度均值,从而提取出人体脉搏信号。原始脉搏信号存在基线漂移及高频噪声,结合脉搏信号特征,设计了零相位数字滤波器来滤除噪声干扰。在不同智能手机上采集了指尖视频图像,利用本文提出的算法提取出了待检测区域。考虑到每次测量时指尖压力会有所不同,本文对不同压力下提取的脉搏信号做了对比分析。为了验证本文提出的算法在心率检测方面的准确性,做了心率检测对比实验。结果表明,本文提出的算法能准确提取出人体心率信息,同时具备一定的可移植性,为进一步在智能手机平台上开发生理监测应用提供了一定的理论帮助。

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.