A Review of Deep Learning and Machine Learning Methods for Analyzing Covid-19 Stress


Authors : V.Suganthi; Dr. M. Punithavalli

Volume/Issue : Volume 7 - 2022, Issue 3 - March

Google Scholar : https://bit.ly/3IIfn9N

Scribd : https://bit.ly/3jck9lu

DOI : https://doi.org/10.5281/zenodo.6421657

The COVID-19 (C-19) pervasive had impacted negatively on environmental health in a number of nations, with a substantial number of cases and deaths reported to far. C-19 produces not only serious bodily issues, but also a range of psychiatric diseases. In some areas, the spread of C-19 may have an impact on people's stress levels. As a result, monitoring and overviewing the Mental Health (MH) of the populace during emergencies is an important concern. Many researchers have used Machine Learning (ML) and Deep Learning (DL) to detect stress. This survey provides a comparative study on various stress detection (Str-Dec) techniques to understand the drawbacks of those detection frameworks and suggest a new solution to C-19 Str-Dec. A detailed survey on Str-Dec during C-19 epidemic is essential for preserving the psychological well-being for improving their healthy lifestyles. The merits and demerits of these approaches have been analyzed and studied to form a new solution for C-19 Str-Dec.

Keywords : Stress classifcation; deep neural network; Mental Health; feature learning; anxiety, insomnia.

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