DSP algorithm for cough identification and counting

Y. H. Hiew; J. A. Smith; J. E. Earis; B. M G Cheetham; A. A. Woodcock

DSP algorithm for cough identification and counting

Y. H. Hiew, J. A. Smith, J. E. Earis, B. M G Cheetham, A. A. Woodcock

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

Abstract

Digital signal processing (DSP) is applied to the analysis of the acoustic properties of pathological cough sounds. This work emanates from a clinical study of asthmatic, cystic fibrosis and cryptogenic fibrosing alveolitis patients. The pathological vocalisations exhibit clinically inconsistent acoustic properties from one disease to another. We aim to analyse the individual cough characteristic to adapt a DSP algorithm for identifying particular coughs and distinguishing them from background noise over long periods. The application is to obtain long-term statistical measurements to allow objective assessment of the severity of cough. This will be used for comparing the effectiveness of various treatments as well as to study the physiological characteristic of pulmonary diseases. In this work, cough identification and counting algorithm has been developed to detect and count coughs characteristic of asthma. Its accuracy has been assessed. A sensitivity of 70.5% and specificity of 98.3% were achieved.

Original language	English
Title of host publication	ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings\|ICASSP IEEE Int Conf Acoust Speech Signal Process Proc
Place of Publication	USA
Publisher	IEEE
Pages	IV/3891
Volume	4
Publication status	Published - 2002
Event	2002 IEEE International Conference on Acoustic, Speech, and Signal Processing - Orlando, FL Duration: 1 Jul 2002 → …

Conference

Conference	2002 IEEE International Conference on Acoustic, Speech, and Signal Processing
City	Orlando, FL
Period	1/07/02 → …

UN SDGs

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

Cite this

@inproceedings{4b6869de1edf4155bfebde5e1e428a04,

title = "DSP algorithm for cough identification and counting",

abstract = "Digital signal processing (DSP) is applied to the analysis of the acoustic properties of pathological cough sounds. This work emanates from a clinical study of asthmatic, cystic fibrosis and cryptogenic fibrosing alveolitis patients. The pathological vocalisations exhibit clinically inconsistent acoustic properties from one disease to another. We aim to analyse the individual cough characteristic to adapt a DSP algorithm for identifying particular coughs and distinguishing them from background noise over long periods. The application is to obtain long-term statistical measurements to allow objective assessment of the severity of cough. This will be used for comparing the effectiveness of various treatments as well as to study the physiological characteristic of pulmonary diseases. In this work, cough identification and counting algorithm has been developed to detect and count coughs characteristic of asthma. Its accuracy has been assessed. A sensitivity of 70.5% and specificity of 98.3% were achieved.",

author = "Hiew, {Y. H.} and Smith, {J. A.} and Earis, {J. E.} and Cheetham, {B. M G} and Woodcock, {A. A.}",

year = "2002",

language = "English",

volume = "4",

pages = "IV/3891",

booktitle = "ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings|ICASSP IEEE Int Conf Acoust Speech Signal Process Proc",

publisher = "IEEE",

address = "United States",

note = "2002 IEEE International Conference on Acoustic, Speech, and Signal Processing ; Conference date: 01-07-2002",

}

Hiew, YH, Smith, JA, Earis, JE, Cheetham, BMG & Woodcock, AA 2002, DSP algorithm for cough identification and counting. in ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings|ICASSP IEEE Int Conf Acoust Speech Signal Process Proc. vol. 4, IEEE, USA, pp. IV/3891, 2002 IEEE International Conference on Acoustic, Speech, and Signal Processing, Orlando, FL, 1/07/02.

DSP algorithm for cough identification and counting. / Hiew, Y. H.; Smith, J. A.; Earis, J. E. et al.
ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings|ICASSP IEEE Int Conf Acoust Speech Signal Process Proc. Vol. 4 USA: IEEE, 2002. p. IV/3891.

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

TY - GEN

T1 - DSP algorithm for cough identification and counting

AU - Hiew, Y. H.

AU - Smith, J. A.

AU - Earis, J. E.

AU - Cheetham, B. M G

AU - Woodcock, A. A.

PY - 2002

Y1 - 2002

N2 - Digital signal processing (DSP) is applied to the analysis of the acoustic properties of pathological cough sounds. This work emanates from a clinical study of asthmatic, cystic fibrosis and cryptogenic fibrosing alveolitis patients. The pathological vocalisations exhibit clinically inconsistent acoustic properties from one disease to another. We aim to analyse the individual cough characteristic to adapt a DSP algorithm for identifying particular coughs and distinguishing them from background noise over long periods. The application is to obtain long-term statistical measurements to allow objective assessment of the severity of cough. This will be used for comparing the effectiveness of various treatments as well as to study the physiological characteristic of pulmonary diseases. In this work, cough identification and counting algorithm has been developed to detect and count coughs characteristic of asthma. Its accuracy has been assessed. A sensitivity of 70.5% and specificity of 98.3% were achieved.

AB - Digital signal processing (DSP) is applied to the analysis of the acoustic properties of pathological cough sounds. This work emanates from a clinical study of asthmatic, cystic fibrosis and cryptogenic fibrosing alveolitis patients. The pathological vocalisations exhibit clinically inconsistent acoustic properties from one disease to another. We aim to analyse the individual cough characteristic to adapt a DSP algorithm for identifying particular coughs and distinguishing them from background noise over long periods. The application is to obtain long-term statistical measurements to allow objective assessment of the severity of cough. This will be used for comparing the effectiveness of various treatments as well as to study the physiological characteristic of pulmonary diseases. In this work, cough identification and counting algorithm has been developed to detect and count coughs characteristic of asthma. Its accuracy has been assessed. A sensitivity of 70.5% and specificity of 98.3% were achieved.

M3 - Conference contribution

VL - 4

SP - IV/3891

BT - ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings|ICASSP IEEE Int Conf Acoust Speech Signal Process Proc

PB - IEEE

CY - USA

T2 - 2002 IEEE International Conference on Acoustic, Speech, and Signal Processing

Y2 - 1 July 2002

ER -

DSP algorithm for cough identification and counting

Abstract

Conference

UN SDGs

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