Time-frequency analysis of wheezing sound to differentiate asthmatic and non-asthmatic condition

Tengku Ahmad Iskandar T. Alang; Om Prakash Singh; M. B. Malarvili

doi:10.1109/ICCSCE.2016.7893570

Time-frequency analysis of wheezing sound to differentiate asthmatic and non-asthmatic condition

Tengku Ahmad Iskandar T. Alang^*
, Om Prakash Singh
, M. B. Malarvili

^*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceeding › Conference proceedings published in a book › peer-review

Abstract

In this paper, a new method to analyze wheezing sound to differentiate asthmatic and non-asthmatic condition is proposed. To achieve this, data acquisition was done on asthmatic and non-asthmatic patients. The data was then filtered by using the high pass-Butterworth filter to obtain a smooth signal. Segmentation of expiration phase emphasized wheezing signal characteristic of the total of 60 epochs. The next step was the selection of time-frequency distribution (TFD) which enabled the feature extraction of frequency, maximum energy, and average energy. Based on comparison done, Modified-B distribution exhibited the best time-frequency resolution for this application. Extracted wheezing features from the time-frequency distribution of asthmatic and non-asthmatic conditions were subsequently analyzed using statistical analysis of t-test. The result indicates that the frequency can be used to differentiate asthmatic and non-asthmatic condition. In conclusion, the Modified-B distribution can distinguish asthmatic and non-asthmatic condition, based on frequency extraction.

Original language	English
Title of host publication	Proceedings - 6th IEEE International Conference on Control System, Computing and Engineering, ICCSCE 2016
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	193-198
Number of pages	6
ISBN (Electronic)	9781509011780
DOIs	https://doi.org/10.1109/ICCSCE.2016.7893570
Publication status	Published - 5 Apr 2017
Externally published	Yes
Event	6th IEEE International Conference on Control System, Computing and Engineering, ICCSCE 2016 - Batu Ferringhi, Penang, Malaysia Duration: 25 Nov 2016 → 27 Nov 2016

Publication series

Name	Proceedings - 6th IEEE International Conference on Control System, Computing and Engineering, ICCSCE 2016

Conference

Conference	6th IEEE International Conference on Control System, Computing and Engineering, ICCSCE 2016
Country/Territory	Malaysia
City	Batu Ferringhi, Penang
Period	25/11/16 → 27/11/16

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 3 Good Health and Well-being

ASJC Scopus subject areas

Artificial Intelligence
Computer Science Applications
Control and Systems Engineering
Mechanical Engineering
Control and Optimization

Keywords

asthma and non-asthma
Features
Modified B-distribution
t-test
time-frequency distribution

Access to Document

10.1109/ICCSCE.2016.7893570

Cite this

Alang, T. A. I. T., Singh, O. P., & Malarvili, M. B. (2017). Time-frequency analysis of wheezing sound to differentiate asthmatic and non-asthmatic condition. In Proceedings - 6th IEEE International Conference on Control System, Computing and Engineering, ICCSCE 2016 (pp. 193-198). Article 7893570 (Proceedings - 6th IEEE International Conference on Control System, Computing and Engineering, ICCSCE 2016). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICCSCE.2016.7893570

Alang, Tengku Ahmad Iskandar T. ; Singh, Om Prakash ; Malarvili, M. B. / Time-frequency analysis of wheezing sound to differentiate asthmatic and non-asthmatic condition. Proceedings - 6th IEEE International Conference on Control System, Computing and Engineering, ICCSCE 2016. Institute of Electrical and Electronics Engineers Inc., 2017. pp. 193-198 (Proceedings - 6th IEEE International Conference on Control System, Computing and Engineering, ICCSCE 2016).

@inproceedings{3ba2ee8bc89d47a39cb7b9a2211765c3,

title = "Time-frequency analysis of wheezing sound to differentiate asthmatic and non-asthmatic condition",

abstract = "In this paper, a new method to analyze wheezing sound to differentiate asthmatic and non-asthmatic condition is proposed. To achieve this, data acquisition was done on asthmatic and non-asthmatic patients. The data was then filtered by using the high pass-Butterworth filter to obtain a smooth signal. Segmentation of expiration phase emphasized wheezing signal characteristic of the total of 60 epochs. The next step was the selection of time-frequency distribution (TFD) which enabled the feature extraction of frequency, maximum energy, and average energy. Based on comparison done, Modified-B distribution exhibited the best time-frequency resolution for this application. Extracted wheezing features from the time-frequency distribution of asthmatic and non-asthmatic conditions were subsequently analyzed using statistical analysis of t-test. The result indicates that the frequency can be used to differentiate asthmatic and non-asthmatic condition. In conclusion, the Modified-B distribution can distinguish asthmatic and non-asthmatic condition, based on frequency extraction.",

keywords = "asthma and non-asthma, Features, Modified B-distribution, t-test, time-frequency distribution",

author = "Alang, \{Tengku Ahmad Iskandar T.\} and Singh, \{Om Prakash\} and Malarvili, \{M. B.\}",

note = "Publisher Copyright: {\textcopyright} 2016 IEEE.; 6th IEEE International Conference on Control System, Computing and Engineering, ICCSCE 2016 ; Conference date: 25-11-2016 Through 27-11-2016",

year = "2017",

month = apr,

day = "5",

doi = "10.1109/ICCSCE.2016.7893570",

language = "English",

series = "Proceedings - 6th IEEE International Conference on Control System, Computing and Engineering, ICCSCE 2016",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

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booktitle = "Proceedings - 6th IEEE International Conference on Control System, Computing and Engineering, ICCSCE 2016",

address = "United States",

}

Alang, TAIT, Singh, OP & Malarvili, MB 2017, Time-frequency analysis of wheezing sound to differentiate asthmatic and non-asthmatic condition. in Proceedings - 6th IEEE International Conference on Control System, Computing and Engineering, ICCSCE 2016., 7893570, Proceedings - 6th IEEE International Conference on Control System, Computing and Engineering, ICCSCE 2016, Institute of Electrical and Electronics Engineers Inc., pp. 193-198, 6th IEEE International Conference on Control System, Computing and Engineering, ICCSCE 2016, Batu Ferringhi, Penang, Malaysia, 25/11/16. https://doi.org/10.1109/ICCSCE.2016.7893570

Time-frequency analysis of wheezing sound to differentiate asthmatic and non-asthmatic condition. / Alang, Tengku Ahmad Iskandar T.; Singh, Om Prakash; Malarvili, M. B.
Proceedings - 6th IEEE International Conference on Control System, Computing and Engineering, ICCSCE 2016. Institute of Electrical and Electronics Engineers Inc., 2017. p. 193-198 7893570 (Proceedings - 6th IEEE International Conference on Control System, Computing and Engineering, ICCSCE 2016).

Research output: Chapter in Book/Report/Conference proceeding › Conference proceedings published in a book › peer-review

TY - GEN

T1 - Time-frequency analysis of wheezing sound to differentiate asthmatic and non-asthmatic condition

AU - Alang, Tengku Ahmad Iskandar T.

AU - Singh, Om Prakash

AU - Malarvili, M. B.

PY - 2017/4/5

Y1 - 2017/4/5

N2 - In this paper, a new method to analyze wheezing sound to differentiate asthmatic and non-asthmatic condition is proposed. To achieve this, data acquisition was done on asthmatic and non-asthmatic patients. The data was then filtered by using the high pass-Butterworth filter to obtain a smooth signal. Segmentation of expiration phase emphasized wheezing signal characteristic of the total of 60 epochs. The next step was the selection of time-frequency distribution (TFD) which enabled the feature extraction of frequency, maximum energy, and average energy. Based on comparison done, Modified-B distribution exhibited the best time-frequency resolution for this application. Extracted wheezing features from the time-frequency distribution of asthmatic and non-asthmatic conditions were subsequently analyzed using statistical analysis of t-test. The result indicates that the frequency can be used to differentiate asthmatic and non-asthmatic condition. In conclusion, the Modified-B distribution can distinguish asthmatic and non-asthmatic condition, based on frequency extraction.

AB - In this paper, a new method to analyze wheezing sound to differentiate asthmatic and non-asthmatic condition is proposed. To achieve this, data acquisition was done on asthmatic and non-asthmatic patients. The data was then filtered by using the high pass-Butterworth filter to obtain a smooth signal. Segmentation of expiration phase emphasized wheezing signal characteristic of the total of 60 epochs. The next step was the selection of time-frequency distribution (TFD) which enabled the feature extraction of frequency, maximum energy, and average energy. Based on comparison done, Modified-B distribution exhibited the best time-frequency resolution for this application. Extracted wheezing features from the time-frequency distribution of asthmatic and non-asthmatic conditions were subsequently analyzed using statistical analysis of t-test. The result indicates that the frequency can be used to differentiate asthmatic and non-asthmatic condition. In conclusion, the Modified-B distribution can distinguish asthmatic and non-asthmatic condition, based on frequency extraction.

KW - asthma and non-asthma

KW - Features

KW - Modified B-distribution

KW - t-test

KW - time-frequency distribution

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DO - 10.1109/ICCSCE.2016.7893570

M3 - Conference proceedings published in a book

AN - SCOPUS:85018994735

T3 - Proceedings - 6th IEEE International Conference on Control System, Computing and Engineering, ICCSCE 2016

SP - 193

EP - 198

BT - Proceedings - 6th IEEE International Conference on Control System, Computing and Engineering, ICCSCE 2016

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 6th IEEE International Conference on Control System, Computing and Engineering, ICCSCE 2016

Y2 - 25 November 2016 through 27 November 2016

ER -

Alang TAIT, Singh OP, Malarvili MB. Time-frequency analysis of wheezing sound to differentiate asthmatic and non-asthmatic condition. In Proceedings - 6th IEEE International Conference on Control System, Computing and Engineering, ICCSCE 2016. Institute of Electrical and Electronics Engineers Inc. 2017. p. 193-198. 7893570. (Proceedings - 6th IEEE International Conference on Control System, Computing and Engineering, ICCSCE 2016). doi: 10.1109/ICCSCE.2016.7893570

Time-frequency analysis of wheezing sound to differentiate asthmatic and non-asthmatic condition

Abstract

Publication series

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UN SDGs

ASJC Scopus subject areas

Keywords

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