Automated algorithm for Wet/Dry cough sounds classification

Vinayak Swarnkar, Udantha Abeyratne, Yusuf Amrulloh, Anne Chang

    Research output: Chapter in Book/Report/Conference proceedingConference Paper published in Proceedings

    Abstract

    Cough is the most common symptom of several respiratory diseases. It is a defense mechanism of the body to clear the respiratory tract from foreign materials inhaled accidentally or produced internally by infections. The identification of wet and dry cough is an important clinical finding, aiding in the differential diagnosis. Wet coughs are more likely to be associated with bacterial infections. At present, the wet/dry decision is based on the subjective judgment of a physician, during a typical consultation session. It is not available for long term monitoring or in the assessment of treatment efficacy. In this paper we address these issues and develop fully automated technology to classify cough into ‘Wet’ and ‘Dry’ categories. We propose novel features and a Logistic regression-based model for the classification of coughs into wet/dry classes. The performance of the method was evaluated on a clinical database of pediatric and adult coughs recorded using a bed-side non-contact microphone. The sensitivity and specificity of the classification were obtained as 79±9% and 72.7±8.7% respectively. These indicate the potential of the method as a useful clinical tool for cough monitoring, especially at home settings.
    Original languageEnglish
    Title of host publicationEngineering in Medicine and Biology Society (EMBC), 2012 Annual International Conference of the IEEE
    Place of PublicationUnited States of America
    PublisherIEEE, Institute of Electrical and Electronics Engineers
    Pages3147-3150
    Number of pages4
    ISBN (Print)978-1-4577-1787-1
    DOIs
    Publication statusPublished - 2012
    EventIEEE The Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC 2012 34th) - San Diego, United States of America, San Diego, United States
    Duration: 28 Aug 20121 Sep 2012
    Conference number: 2012 (34th)

    Conference

    ConferenceIEEE The Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC 2012 34th)
    Abbreviated titleEMBC
    CountryUnited States
    CitySan Diego
    Period28/08/121/09/12

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    Cite this

    Swarnkar, V., Abeyratne, U., Amrulloh, Y., & Chang, A. (2012). Automated algorithm for Wet/Dry cough sounds classification. In Engineering in Medicine and Biology Society (EMBC), 2012 Annual International Conference of the IEEE (pp. 3147-3150). United States of America: IEEE, Institute of Electrical and Electronics Engineers. https://doi.org/10.1109/EMBC.2012.6346632