@inproceedings{279c335077834ceda92ad8d732bc6b58,
title = "A wireless photoplethysmography signal processing system for long-term monitoring",
abstract = "This paper has presented a photoplethysmography (PPG) signal processing system based on ensemble empirical mode decomposition (EEMD) method. Traditionally, empirical mode decomposition (EMD) suffers from mode mixing problem during the decomposition process. This paper adopts EEMD to solve the mode mixing problem by adding different sets of white noise and decompose signal into meaningful intrinsic mode functions. The system is implemented on self-designed platform combined with front-end circuit, EEMD chip by TSMC 90nm CMOS technology, and commercial display devices. The results showed that the proposed EEMD processor can effectively solve the mode mixing problem of EMD. It was helpful for non-stationary biomedical signal processing and cardiovascular diseases research.",
keywords = "Ensemble Empirical Mode Decomposition, Health-Care System, photoplethysmography",
author = "Wu, {Chih Chin} and Fan, {Shu Han} and Shang Chuang and Liao, {Jia Ju} and Chou, {Chia Ching} and Wai-Chi Fang",
note = "Publisher Copyright: {\textcopyright} 2016 IEEE.; IEEE International Conference on Consumer Electronics, ICCE 2016 ; Conference date: 07-01-2016 Through 11-01-2016",
year = "2016",
month = mar,
day = "10",
doi = "10.1109/ICCE.2016.7430698",
language = "English",
series = "2016 IEEE International Conference on Consumer Electronics, ICCE 2016",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "480--483",
editor = "Bellido, {Francisco J.} and Daniel Diaz-Sanchez and Vun, {Nicholas C. H.} and Carsten Dolar and Wing-Kuen Ling",
booktitle = "2016 IEEE International Conference on Consumer Electronics, ICCE 2016",
address = "United States",
}
