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All Journal Jurnal Teknik ITS IPTEK Journal of Proceedings Series Jurnal Simetris Journal of Applied Data Sciences
Wiratno Argo Asmoro
Departemen Teknik Fisika, Institut Teknologi Sepuluh Nopember (ITS) Surabaya
Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Engineering

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Performance Improvement of Covid-19 Cough Detection Based on Deep Learning with Segmentation Methods Suyanto, Suyanto; Zanjabila, Zanjabila; Atmaja, Bagus Tris; Asmoro, Wiratno Argo
Journal of Applied Data Sciences Vol 5, No 2: MAY 2024
Publisher : Bright Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47738/jads.v5i2.205

Abstract

COVID-19 is an emergency problem that is being widely discussed in the world, one of which is the deep learning-based COVID-19 detection method which has been developed based on images of the patient's chest or cough. In this research, we propose a way to improve the performance of deep learning-based COVID-19 cough detection by using a segmentation method to produce several audio files containing one cough signal from one audio file containing several cough sound signals. In addition, we enabled two automatic cough segmentation methods, namely a Hysteresis Comparator based on the power spectrum and an RMS threshold based on the RMS energy value. The results obtained show that using the segmentation method for cough sounds can improve the model's performance in detecting COVID-19 coughs by 4% to 8%. The segmentation process can also remove noise between cough sound signals and provide a standard input model in the form of one cough signal. In addition, the segmentation results show information related to the characteristics of COVID-19 cough. The evaluation results show that the hysteresis comparator method has better results with an unweighted accuracy (UA) value of 83.19% compared to the RMS threshold method with a UA value of 79.06%.
Co-Authors Andi Rahmadiansah Bagus Tris Atmaja, Bagus Tris Benny Adi Nugraha Defiana, Ima Edy Sugiantoro Fasial, Muhamad Fitri Rachmawati Hade Lieberika Monhaziz Indan Pratiwi Mayang Ananda Putri Muhamad Fasial Muhammad Bintang Tsaqib Prilya Lutvitania Pradita Ruri Agung Wahyuono Sugiantoro, Edy Suyanto Suyanto Wisnu Wardhana Zanjabila, Zanjabila