Fruit-CoV: An efficient vision-based framework for speedy detection and diagnosis of SARS-CoV-2 infections through recorded cough sounds

Long H. Nguyen, Nhat Truong Pham, Van Huong Do, Liu Tai Nguyen, Thanh Tin Nguyen, Hai Nguyen, Ngoc Duy Nguyen, Thanh Thi Nguyen, Sy Dzung Nguyen, Asim Bhatti, Chee Peng Lim

Research output: Contribution to journalArticleResearchpeer-review

2 Citations (Scopus)

Abstract

COVID-19 is an infectious disease caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). This deadly virus has spread worldwide, leading to a global pandemic since March 2020. A recent variant of SARS-CoV-2 named Delta is intractably contagious and responsible for more than four million deaths globally. Therefore, developing an efficient self-testing service for SARS-CoV-2 at home is vital. In this study, a two-stage vision-based framework, namely Fruit-CoV, is introduced for detecting SARS-CoV-2 infections through recorded cough sounds. Specifically, audio signals are converted into Log-Mel spectrograms, and the EfficientNet-V2 network is used to extract their visual features in the first stage. In the second stage, 14 convolutional layers extracted from the large-scale Pretrained Audio Neural Networks for audio pattern recognition (PANNs) and the Wavegram-Log-Mel-CNN are employed to aggregate feature representations of the Log-Mel spectrograms and the waveform. Finally, the combined features are used to train a binary classifier. In this study, a dataset provided by the AICovidVN 115M Challenge is employed for evaluation. It includes 7,371 recorded cough sounds collected throughout Vietnam, India, and Switzerland. Experimental results indicate that the proposed model achieves an Area Under the Receiver Operating Characteristic Curve (AUC) score of 92.8% and ranks first on the final leaderboard of the AICovidVN 115M Challenge. Our code is publicly available.

Original languageEnglish
Article number119212
Number of pages12
JournalExpert Systems with Applications
Volume213
DOIs
Publication statusPublished - 1 Mar 2023
Externally publishedYes

Keywords

  • COVID-19
  • Deep learning
  • Delta variant
  • EfficientNet
  • Log-Mel spectrogram
  • Machine vision
  • Neural network
  • PANNs
  • Recorded cough sounds
  • Remote detection
  • SARS-CoV-2 infections
  • Self-testing service
  • Sound classification
  • Speedy detection
  • Wavegram

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