A wireless photoplethysmography signal processing system for long-term monitoring

Chih Chin Wu, Shu Han Fan, Shang Chuang, Jia Ju Liao, Chia Ching Chou, Wai-Chi  Fang

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

3 Scopus citations

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.

Original languageEnglish
Title of host publication2016 IEEE International Conference on Consumer Electronics, ICCE 2016
EditorsFrancisco J. Bellido, Daniel Diaz-Sanchez, Nicholas C. H. Vun, Carsten Dolar, Wing-Kuen Ling
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages480-483
Number of pages4
ISBN (Electronic)9781467383646
DOIs
StatePublished - 10 Mar 2016
EventIEEE International Conference on Consumer Electronics, ICCE 2016 - Las Vegas, United States
Duration: 7 Jan 201611 Jan 2016

Publication series

Name2016 IEEE International Conference on Consumer Electronics, ICCE 2016

Conference

ConferenceIEEE International Conference on Consumer Electronics, ICCE 2016
CountryUnited States
CityLas Vegas
Period7/01/1611/01/16

Keywords

  • Ensemble Empirical Mode Decomposition
  • Health-Care System
  • photoplethysmography

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