An Integrated PPG and ECG Signal Processing Hardware Architecture Design of EEMD Processor

Wai-Chi Fang, I. Wei Chen

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

2 Scopus citations

Abstract

This study proposed an integrated Photoplethysmogram (PPG) and Electrocardiography (ECG) signal processing hardware architecture design based on Ensemble Empirical Mode Decomposition (EEMD) The proposed integrated dual signals EEMD processor is implemented in an on-board FPGA for on-line signal processing of the non-linear and non-stationary signal. The EEMD method is appropriate to analyze the non-linear PPG and ECG signals with assisting white noise and decompose the signal into 8 sets of Intrinsic Mode Functions (IMFs). The experimental results show that the hardware architecture proposed in this study can be applied to PPG and ECG signals, and can clearly analyze and separate high-frequency and low-frequency noise, and keep clear signals without any noise.

Original languageEnglish
Title of host publication2019 IEEE International Conference on Consumer Electronics, ICCE 2019
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781538679104
DOIs
StatePublished - 6 Mar 2019
Event2019 IEEE International Conference on Consumer Electronics, ICCE 2019 - Las Vegas, United States
Duration: 11 Jan 201913 Jan 2019

Publication series

Name2019 IEEE International Conference on Consumer Electronics, ICCE 2019

Conference

Conference2019 IEEE International Conference on Consumer Electronics, ICCE 2019
Country/TerritoryUnited States
CityLas Vegas
Period11/01/1913/01/19

Keywords

  • Electrocardiography
  • Ensemble Empirical Mode Decomposition (EEMD)
  • Field Programmable Gate Array (FPGA)
  • Photoplethysmogram

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