Study on conditioning and feature extraction algorithm ofphotoplethysmography signal for physiological parameters detection
Photoplethysmography(PPG) signal can reflect many physiological parameters, such as heart function, blood vessel elasticity, blood viscosity and so on. It was a novel noninvasive method with the advantage of convenience and accuracy. It was important to find efficient pre-processing and feature extraction algorithms to deal with original PPG signal, which was interfered by many other factors. Many practical methods including median filtering and FIR filtering was used. A new algorithm based on wavelet transformation was proposed for eliminating the baseline drift. Feature points extraction was another key issue. An improved differential algorithm was used to solve this problem. All of these practical algorithms provided an effective platform for physiological parameters detection.
PPG physiological parameters wavelet transform baseline differential feature detection
Chen Wei Lei Sheng Guo Lihua Chen Yuquan Pan Min
National Key Laboratory of Biomedical sensor, Zhejiang University Hang Zhou, 310027, China
国际会议
2011 4th International Congress on Image and Signal Processing(第四届图像与信号处理国际学术会议 CISP 2011)
上海
英文
2222-2225
2011-10-15（万方平台首次上网日期，不代表论文的发表时间）