Data Reduction for Cough Studies Using Distribution of Audio Frequency Content

Overview

Journal Cough

Publisher Biomed Central

Date 2012 Dec 13

PMID 23231789

Citations 17

Authors

Antony Barton

Patrick Gaydecki

Kimberley Holt

Jaclyn A Smith

Affiliations

Soon will be listed here.

Abstract

Unlabelled:

Background: Recent studies suggest that objectively quantifying coughing in audio recordings offers a novel means to understand coughing and assess treatments. Currently, manual cough counting is the most accurate method for quantifying coughing. However, the demand of manually counting cough records is substantial, demonstrating a need to reduce record lengths prior to counting whilst preserving the coughs within them. This study tested the performance of an algorithm developed for this purpose.

Methods: 20 subjects were recruited (5 healthy smokers and non-smokers, 5 chronic cough, 5 chronic obstructive pulmonary disease and 5 asthma), fitted with an ambulatory recording system and recorded for 24 hours. The recordings produced were divided into 15 min segments and counted. Periods of inactive audio in each segment were removed using the median frequency and power of the audio signal and the resulting files re-counted.

Results: The median resultant segment length was 13.9 s (IQR 56.4 s) and median 24 hr recording length 62.4 min (IQR 100.4). A median of 0.0 coughs/h (IQR 0.0-0.2) were erroneously removed and the variability in the resultant cough counts was comparable to that between manual cough counts. The largest error was seen in asthmatic patients, but still only 1.0% coughs/h were missed.

Conclusions: These data show that a system which measures signal activity using the median audio frequency can substantially reduce record lengths without significantly compromising the coughs contained within them.

Citing Articles

Kang J, Seo W, Kim J, Moon J, Kim D, Kim J Ther Adv Respir Dis. 2024; 18:17534666241252545.

PMID: 38780129 PMC: 11119368. DOI: 10.1177/17534666241252545.

A smartphone-based application for cough counting in patients with acute asthma exacerbation.

Shim J, Kim B, Kim S, Kwon J, Ahn K, Kang S J Thorac Dis. 2023; 15(7):4053-4065.

PMID: 37559656 PMC: 10407484. DOI: 10.21037/jtd-22-1492.

Validation of a small cough detector.

Kuhn M, Nalbant E, Kohlbrenner D, Alge M, Kuett L, Arvaji A ERJ Open Res. 2023; 9(1).

PMID: 36699651 PMC: 9868968. DOI: 10.1183/23120541.00279-2022.

Chronic cough-the limitation and advances in assessment techniques.

Zhang M, Sykes D, Brindle K, Sadofsky L, Morice A J Thorac Dis. 2023; 14(12):5097-5119.

PMID: 36647459 PMC: 9840016. DOI: 10.21037/jtd-22-874.

Performance of cough monitoring by Albus Home, a contactless and automated system for nocturnal respiratory monitoring at home.

Do W, Russell R, Wheeler C, Javed H, Dogan C, Cunningham G ERJ Open Res. 2022; 8(4).

PMID: 36478916 PMC: 9720547. DOI: 10.1183/23120541.00265-2022.

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