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BY 4.0 license Open Access Published by De Gruyter November 26, 2020

Automatic Detection and Classification of Cough Events Based on Deep Learning

Seyed Amir Hossein Tabatabaei, Gabriela Augustinov, Volker Gross, Keywan Sohrabi, Patrick Fischer and Ulrich Koehler


In this paper, a deep learning approach for classification of cough sound segments is presented. The architecture of the network is based on a pre-trained network and the spectrogram images of three recording channels have been extracted for the sake of training the network. The classification accuracy based on three recording channels is 92% for a binary classification model and the network converges fast. Two classification models based on binary and multi-class problems are proposed. Relevant classification parameters including the Receiver Operating Characteristic (ROC) curve are reported.

Published Online: 2020-11-26
Published in Print: 2020-09-01

© 2020 by Walter de Gruyter Berlin/Boston

This work is licensed under the Creative Commons Attribution 4.0 International License.

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