The World Health Organization (WHO) has announced a COVID-19 was a global pandemic in March 2020. It was initially started in china in the year 2019 December and affected an expanding number of nations in various countries in the last few months. In this particular situation, many techniques, methods, and AI-based classification algorithms are put in the spotlight in reacting to fight against it and reduce the rate of such a global health crisis. COVID-19's main signs are heavy temperature, different cough, cold, breathing shortness, and a combination of loss of sense of smell and chest tightness. The digital world is growing day by day, in this context digital stethoscope can read all of these symptoms and diagnose respiratory disease. In this study, we majorly focus on literature reviews of how SARS-CoV-2 is spreading and in-depth analysis of the diagnosis of COVID-19 disease from human respiratory sounds like cough, voice, and breath by analyzing the respiratory sound parameters. We hope this review will provide an initiative for the clinical scientists and researcher's community to initiate open access, scalable, and accessible work in the collective battle against COVID-19.
翻译:世界卫生组织(世卫组织)于2020年3月宣布COVID-19为全球流行病,最初始于2019年12月中国,在过去几个月里影响到不同国家越来越多的国家,在这一特殊情况下,许多技术、方法和基于AI的分类算法被作为打击这种疾病和降低这种全球健康危机速度的焦点。COVID-19的主要征兆是高温、不同咳嗽、寒冷、呼吸短促,以及嗅觉和胸部紧绷感的混合体。数字世界正在日复一日地增长,在这种背景下,数字听诊器可以读取所有这些症状并诊断呼吸道疾病。在本研究中,我们主要侧重于文献审查SARS-COV-2是如何传播和深入分析人类呼吸道声音(如咳嗽、声音和呼吸)对COVID-19疾病的诊断的。我们希望这一审查将为临床科学家和研究人员社区提供主动倡议,在反对COVID-19的集体斗争中发起开放、可缩放和无障碍的工作。