CASCO: A Contactless Cough Screening System Based on Audio Signal Processing

Xinxin Zhang, Hang Liu, Xinru Chen, Rui Qin, Yan Zhu, Wenfang Li, Menghan Hu, Jian Zhang

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Cough is a common symptom of respiratory disease, which produces a specific sound. Cough detection has great significance to prevent, assess, and control epidemics. This paper proposes CASCO (Cough Analysis System using Short-Time Fourier Transform (STFT) and Convolutional Neural Networks (CNN) in the WeChat mini Program), a cough detection system capable of quantifying the number of coughs through an audio division algorithm. This system combines STFT with CNN, achieving accuracy, precision, recall, and F1-score with 97.0%, 95.6%, 98.7%, and 0.97 respectively in cough detection. The model is embedded into the WeChat mini program to make it feasible to apply cough detection on smartphones and realize large-scale and contactless cough screening. Future research can combine audio and video signals to further improve the accuracy of large-scale cough screening.

Original languageEnglish
Title of host publicationAdvances in Computer Graphics - 40th Computer Graphics International Conference, CGI 2023, Proceedings
EditorsBin Sheng, Lei Bi, Jinman Kim, Nadia Magnenat-Thalmann, Daniel Thalmann
PublisherSpringer Science and Business Media Deutschland GmbH
Pages287-300
Number of pages14
ISBN (Print)9783031500770
DOIs
StatePublished - 2024
Event40th Computer Graphics International Conference, CGI 2023 - Shanghai, China
Duration: 28 Aug 20231 Sep 2023

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume14498 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference40th Computer Graphics International Conference, CGI 2023
Country/TerritoryChina
CityShanghai
Period28/08/231/09/23

Keywords

  • Audio Signal Processing
  • Cough detection
  • Deep neural network

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