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Authors: Anthony Windmon ; Mona Minakshi ; Sriram Chellappan ; Ponrathi R. Athilingam ; Marcia Johansson and Bradlee A. Jenkins

Affiliation: University of South Florida, United States

ISBN: 978-989-758-281-3

Keyword(s): Chronic Obstructive Pulmonary Disease, COPD, Cough, Machine Learning, Algorithms, Classification.

Related Ontology Subjects/Areas/Topics: Biomedical Engineering ; Cloud Computing ; Distributed and Mobile Software Systems ; e-Health ; Health Engineering and Technology Applications ; Health Information Systems ; Mobile Technologies ; Mobile Technologies for Healthcare Applications ; Neural Rehabilitation ; Neurotechnology, Electronics and Informatics ; Pervasive Health Systems and Services ; Platforms and Applications ; Software Engineering

Abstract: Chronic Obstructive Pulmonary Disease (COPD) is a lung disease that makes breathing a strenuous task with chronic cough. Millions of adults, worldwide, suffer from COPD, and in many cases, they are not diagnosed at all. In this paper, we present the feasibility of leveraging cough samples recorded using a smart-phone’s microphone, and processing the associated audio signals via machine learning algorithms, to detect cough patterns indicative of COPD. Using 39 adult cough samples evenly spread across both genders, that included 23 subjects infected with COPD and 16 Controls, not infected with COPD, our system, using Random Forest classification techniques, yielded a detection accuracy of 85:4% with very good Precision, Recall and FMeasures. To the best of our knowledge, this is the first work that designs a smart-phone based learning technique for detecting COPD via processing cough.

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Paper citation in several formats:
Windmon, A.; Minakshi, M.; Chellappan, S.; R. Athilingam, P.; Johansson , M. and A. Jenkins , B. (2018). On Detecting Chronic Obstructive Pulmonary Disease (COPD) Cough using Audio Signals Recorded from Smart-Phones.In Proceedings of the 11th International Joint Conference on Biomedical Engineering Systems and Technologies - Volume 5: HEALTHINF, ISBN 978-989-758-281-3, pages 329-338. DOI: 10.5220/0006549603290338

@conference{healthinf18,
author={Anthony Windmon. and Mona Minakshi. and Sriram Chellappan. and Ponrathi R. Athilingam. and Marcia Johansson . and Bradlee A. Jenkins .},
title={On Detecting Chronic Obstructive Pulmonary Disease (COPD) Cough using Audio Signals Recorded from Smart-Phones},
booktitle={Proceedings of the 11th International Joint Conference on Biomedical Engineering Systems and Technologies - Volume 5: HEALTHINF,},
year={2018},
pages={329-338},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006549603290338},
isbn={978-989-758-281-3},
}

TY - CONF

JO - Proceedings of the 11th International Joint Conference on Biomedical Engineering Systems and Technologies - Volume 5: HEALTHINF,
TI - On Detecting Chronic Obstructive Pulmonary Disease (COPD) Cough using Audio Signals Recorded from Smart-Phones
SN - 978-989-758-281-3
AU - Windmon, A.
AU - Minakshi, M.
AU - Chellappan, S.
AU - R. Athilingam, P.
AU - Johansson , M.
AU - A. Jenkins , B.
PY - 2018
SP - 329
EP - 338
DO - 10.5220/0006549603290338

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