Audio and Contact Microphones for Cough Detection

By Thomas Drugman, J. Urbain, N. Bauwens, Ricardo Chessini, A. Aubriot, P. Lebecque, Thierry Dutoit. 2020

36 citations recorded by the source corpus.

In the framework of assessing the pathology severity in chronic cough diseases, medical literature underlines the lack of tools for allowing the automatic, objective and reliable detection of cough events. This paper describes a system based on two microphones which we developed for this purpose. The proposed approach relies on a large variety of audio descriptors, an efficient algorithm of feature selection based on their mutual information and the use of artificial neural networks. First, the possible use of a contact microphone (placed on the patient's thorax or trachea) in complement to the audio signal is investigated. This study underlines that this contact microphone suffers from reliability issues, and conveys little new relevant information compared to the audio modality. Secondly, the proposed audioonly approach is compared to a commercially available system using four sensors on a database with different sound categories often misdetected as coughs, and produced in various conditions. With average sensitivity and specificity of 94.7% and 95% respectively, the proposed method achieves better cough detection performance than the commercial system.

Subfields: Pharmacy, Physiology, Pulmonary and Respiratory Medicine

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Physiology

  1. Jordi Pons
  2. Xavier Serra

In Pulmonary and Respiratory Medicine

  1. Xavier Serra
  2. Eduardo Fonseca
  3. Xavier Favory
  4. Frederic Font

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