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Analysis on Mental Stress of Professionals and Pregnant Women Using Machine Learning Techniques

Authors :
S. Ravikumar
E. Kannan
Source :
International Journal of Image and Graphics.
Publication Year :
2022
Publisher :
World Scientific Pub Co Pte Ltd, 2022.

Abstract

Stress is the way that everyone can respond actually, intellectually and sincerely to different conditions, changes and requests in our lives. Stress problems are a typical issue among working experts in the business today. With changing way of life and work societies, there is an expansion in the stress among the representatives. However, numerous ventures and corporate give emotional wellness-related plans and attempt to facilitate the work environment climate, the issue is a long way from control. When it comes to Pregnant Women, the uterus climate assumes a fundamental part in future development and improvement of hatchling. Stress during pregnancy will influence the sensitive climate of the hatchling. These can remember impacts for your unborn child’s development and the length of incubation period. They can likewise expand the danger of issues in your child’s future physical and mental turn of events, just as social issues in youth. By using various machine learning techniques, the proposed model can analyze the stress in a working professional and also in a pregnant woman. We can predict the best way of yoga to reduce their stress and get good work results from working employees and a good growth in fetus of a pregnant women. Yoga can positively affect the parasympathetic sensory system and helps in bringing down heartbeat and circulatory strain. This decreases the interest of the body for oxygen and furthermore increment lung limit. Compelling utilization of yoga can likewise decrease the odds of stress, nervousness and despondency.

Details

ISSN :
17936756 and 02194678
Database :
OpenAIRE
Journal :
International Journal of Image and Graphics
Accession number :
edsair.doi...........6754d819b533edb156111ed966d50c82
Full Text :
https://doi.org/10.1142/s0219467823500389