Time-frequency analysis of heart sound signals based on Hilbert-Huang Transformation

Tzu Hsun Hung*, Chia Ching Chou, Wai-Chi Fang, Arvin Huang Te Li, Yu Ching Chang, Bai Kuang Hwang, Yio Wha Shau

*Corresponding author for this work

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

8 Scopus citations

Abstract

In this study, a method based on Hilbert-Huang Transformation (HHT) for time-frequency analysis of heart sound signals is presented. HHT is employed because most biomedical signals such as Electroencephalogram (EEG), Electrocardiogram (ECG) and heart sound signals are non-stationary signals. Heart sound signals recordings are often contaminated with the spike noise caused by the front-end circuits or measurement instruments in the real situations. A digital median filter is firstly employed to remove the spike noise of the heart sound signals. Then, the time series data are decomposed into several IMFs (Intrinsic Mode Function) using Empirical Mode Decomposition (EMD) algorithm. Hilbert transformation algorithm is utilized to acquire the instantaneous frequency for every IMF. Simulation results show that time-frequency domain analysis of heart sounds signals based on HHT algorithm is able to offer higher frequency resolution.

Original languageEnglish
Title of host publication2012 IEEE 16th International Symposium on Consumer Electronics, ISCE 2012
DOIs
StatePublished - 26 Sep 2012
Event2012 IEEE 16th International Symposium on Consumer Electronics, ISCE 2012 - Harrisburg, PA, United States
Duration: 4 Jun 20126 Jun 2012

Publication series

NameDigest of Technical Papers - IEEE International Conference on Consumer Electronics
ISSN (Print)0747-668X

Conference

Conference2012 IEEE 16th International Symposium on Consumer Electronics, ISCE 2012
CountryUnited States
CityHarrisburg, PA
Period4/06/126/06/12

Keywords

  • Empirical Mode Decomposition (EMD)
  • Hilbert-Huang Transformation (HHT)
  • heart sound

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