An effective arterial blood pressure signal processing system based on EEMD method

Shang Yi Chuang, Jia Ju Liao, Chia Ching Chou, Chia Chi Chang, Wai-Chi  Fang

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

Abstract

This study proposed an effective signal processing system based on Ensemble Empirical Mode Decomposition (EEMD) method for the analysis of arterial blood pressure (ABP). The whole system was implemented on an ARM-based SoC development platform to attain the on-line non-stationary signal processing. A non-invasive blood pressure acquisition device (NIBP100D) was used to record the continuous ABP as the input signal. According to the non-stationary characteristics of ABP, EEMD is useful to achieve accurate decomposition for ABP spectral analysis. The signal was decomposed into several Intrinsic Mode Functions (IMFs) by EEMD, and quantitatively assessed by fast Fourier transform (FFT). The results showed that the proposed EEMD processor can effectively solve the mode mixing problem of Empirical Mode Decomposition (EMD) and the FFT spectrum of IMF5, IMF6, and IMF7 to reveal heart rate and respiration.

Original languageEnglish
Title of host publicationTechnical Papers of 2014 International Symposium on VLSI Design, Automation and Test, VLSI-DAT 2014
PublisherIEEE Computer Society
ISBN (Print)9781479927760
DOIs
StatePublished - 1 Jan 2014
Event2014 International Symposium on VLSI Design, Automation and Test, VLSI-DAT 2014 - Hsinchu, Taiwan
Duration: 28 Apr 201430 Apr 2014

Publication series

NameTechnical Papers of 2014 International Symposium on VLSI Design, Automation and Test, VLSI-DAT 2014

Conference

Conference2014 International Symposium on VLSI Design, Automation and Test, VLSI-DAT 2014
Country/TerritoryTaiwan
CityHsinchu
Period28/04/1430/04/14

Keywords

  • Arterial blood pressure
  • Continuous blood pressure
  • Ensemble empirical mode decomposition
  • FPGA

Fingerprint

Dive into the research topics of 'An effective arterial blood pressure signal processing system based on EEMD method'. Together they form a unique fingerprint.

Cite this