ABSTRACT
The COVID-19 outbreak resulted in multiple waves of infections that have been associated with different SARS-CoV-2 variants. Studies have reported differential impact of the variants on respiratory health of patients. We explore whether acoustic signals, collected from COVID-19 subjects, show computationally distinguishable acoustic patterns suggesting a possibility to predict the underlying virus variant. We analyze the Coswara dataset which is collected from three subject pools, namely, i) healthy, ii) COVID-19 subjects recorded during the delta variant dominant period, and iii) data from COVID-19 subjects recorded during the omicron surge. Our findings suggest that multiple sound categories, such as cough, breathing, and speech, indicate significant acoustic feature differences when comparing COVID-19 subjects with omicron and delta variants. The classification areas-under-the-curve are significantly above chance for differentiating subjects infected by omicron from those infected by delta. Using a score fusion from multiple sound categories, we obtained an area-under-the-curve of 89% and 52.4% sensitivity at 95% specificity. Additionally, a hierarchical three class approach was used to classify the acoustic data into healthy and COVID-19 positive, and further COVID-19 subjects into delta and omicron variants providing high level of 3-class classification accuracy. These results suggest new ways for designing sound based COVID-19 diagnosis approaches. Copyright © 2022 ISCA.
ABSTRACT
The COVID-19 pandemic has accelerated research on design of alternative, quick and effective COVID-19 diagnosis approaches. In this paper, we describe the Coswara tool, a website application designed to enable COVID-19 detection by analysing respiratory sound samples and health symptoms. A user using this service can log into a website using any device connected to the internet, provide there current health symptom information and record few sound sampled corresponding to breathing, cough, and speech. Within a minute of analysis of this information on a cloud server the website tool will output a COVID-19 probability score to the user. As the COVID-19 pandemic continues to demand massive and scalable population level testing, we hypothesize that the proposed tool provides a potential solution towards this. Copyright © 2022 ISCA.
ABSTRACT
Burnout syndrome in recent days has creeped among the medical practitioners and supportive staffs in hospitals and health care units from around the globe, due to the pandemic situation that provoked because of COVID-19. Incessant flow of patients round the clock shattered the energy level of physicians and nurses who are in this life saving exercise without even caring about their own lives. But treating patients continuously in critical care unit leads to emotional fatigue and in a long run leads to futility among the health care workers. Analysing the root cause among the medical practitioners by means of their lifestyle, socio-psychological status and their inbuilt aptitudes will let the hidden reasons behind this burnout. By means of continuous monitoring, motivation and training they can overcome this syndrome and make their lives more meaningful for this society as well as their self. This paper reveals the common and psychological problems obsessed by the physicians during at their work place, their personal and social life situations with reference to studies carried out in different parts of the world.