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

doi:10.1109/ISCE.2012.6241745

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 proceeding › Conference contribution › peer-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 language	English
Title of host publication	2012 IEEE 16th International Symposium on Consumer Electronics, ISCE 2012
DOIs	https://doi.org/10.1109/ISCE.2012.6241745
State	Published - 26 Sep 2012
Event	2012 IEEE 16th International Symposium on Consumer Electronics, ISCE 2012 - Harrisburg, PA, United States Duration: 4 Jun 2012 → 6 Jun 2012

Publication series

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

Conference

Conference	2012 IEEE 16th International Symposium on Consumer Electronics, ISCE 2012
Country/Territory	United States
City	Harrisburg, PA
Period	4/06/12 → 6/06/12

Keywords

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

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10.1109/ISCE.2012.6241745

Cite this

Hung, T. H., Chou, C. C., Fang, W-C., Li, A. H. T., Chang, Y. C., Hwang, B. K., & Shau, Y. W. (2012). Time-frequency analysis of heart sound signals based on Hilbert-Huang Transformation. In 2012 IEEE 16th International Symposium on Consumer Electronics, ISCE 2012 Article 6241745 (Digest of Technical Papers - IEEE International Conference on Consumer Electronics). https://doi.org/10.1109/ISCE.2012.6241745

@inproceedings{6f81f4c61b624e9c8762f4581266266b,

title = "Time-frequency analysis of heart sound signals based on Hilbert-Huang Transformation",

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.",

keywords = "Empirical Mode Decomposition (EMD), Hilbert-Huang Transformation (HHT), heart sound",

author = "Hung, {Tzu Hsun} and Chou, {Chia Ching} and Wai-Chi Fang and Li, {Arvin Huang Te} and Chang, {Yu Ching} and Hwang, {Bai Kuang} and Shau, {Yio Wha}",

year = "2012",

month = sep,

day = "26",

doi = "10.1109/ISCE.2012.6241745",

language = "English",

isbn = "9781467313544",

series = "Digest of Technical Papers - IEEE International Conference on Consumer Electronics",

booktitle = "2012 IEEE 16th International Symposium on Consumer Electronics, ISCE 2012",

note = "2012 IEEE 16th International Symposium on Consumer Electronics, ISCE 2012 ; Conference date: 04-06-2012 Through 06-06-2012",

}

Hung, TH, Chou, CC, Fang, W-C, Li, AHT, Chang, YC, Hwang, BK & Shau, YW 2012, Time-frequency analysis of heart sound signals based on Hilbert-Huang Transformation. in 2012 IEEE 16th International Symposium on Consumer Electronics, ISCE 2012., 6241745, Digest of Technical Papers - IEEE International Conference on Consumer Electronics, 2012 IEEE 16th International Symposium on Consumer Electronics, ISCE 2012, Harrisburg, PA, United States, 4/06/12. https://doi.org/10.1109/ISCE.2012.6241745

Time-frequency analysis of heart sound signals based on Hilbert-Huang Transformation. / Hung, Tzu Hsun; Chou, Chia Ching; Fang, Wai-Chi et al.
2012 IEEE 16th International Symposium on Consumer Electronics, ISCE 2012. 2012. 6241745 (Digest of Technical Papers - IEEE International Conference on Consumer Electronics).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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AU - Hung, Tzu Hsun

AU - Chou, Chia Ching

AU - Fang, Wai-Chi

AU - Li, Arvin Huang Te

AU - Chang, Yu Ching

AU - Hwang, Bai Kuang

AU - Shau, Yio Wha

PY - 2012/9/26

Y1 - 2012/9/26

N2 - 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.

AB - 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.

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

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