An Effective Photoplethysmography Signals Processing System Based on Ensemble Empirical Mode Decomposition Method for Acquiring the Multiple Physiological Parameters

• Main Authors: Liao, Jia-Ju, 廖家駒
• Other Authors: Fang, Wai-Chi
• Format: Others
• Language: zh-TW
• Published: 2015
• Online Access: http://ndltd.ncl.edu.tw/handle/a5wbqb

碩士 === 國立交通大學 === 電子工程學系 電子研究所 === 104 === The heavily medical burden caused by population ageing will become a serious challenge for the current and next generation medical care system. There is an urgent need of low-cost disease prevention and home care programs to lower the possible medical burden in the future. The cardiovascular diseases have been on the list of leading cause of death for years in Taiwan. There is about seventeen million people pass away because of cardiovascular around the world. There is urgent need to get the early prevention tool to reduce the risk of cardiovascular disease all over the world. An effective photoplethysmography (PPG) signal processing system based on ensemble empirical mode decomposition (EEMD) method for acquiring the multiple physiological parameters is proposed in this project. The information of arterial pulse can be obtained by near-infrared. A high quality signal can be extracted through the proposed EEMD algorithm. Based on the most advanced semiconductor industry in Taiwan, the regulation of autonomic nervous system (ANS), RI and SI can be derived in real-time and monitored continuously. It makes the at-home care possible and lowers the rate of cardiovascular diseases and medical expenses through long-term monitoring. PPG signal acquired by the PPG capture circuit is sampled through the ADC at sample frequency of 200Hz after being filtered by the band pass filter. The digitized data are decomposed into IMFs with physiological meanings by the EEMD IC. The output IMFs are wirelessly sent to a computer via a Bluetooth module. Then the regulation of autonomic nervous system , RI and SI can be derived and display on the GUI. To overcome the noise and aliasing effect caused by nonstationary signals, many innovative and effective modules were developed in this thesis. The proposed HHT SoC design could be implemented in hardware with limited resources and fabricated under TSMC 90 nm CMOS technology. To assess the potential risk of cardiovascular, the IMFs with physiological meanings can be extracted from PPG. The RI, SI, LF, HF and VHF can be derived as the parameters to help the diagnosis of cardiovascular disease.