Please use this identifier to cite or link to this item: http://13.232.72.61:8080/jspui/handle/123456789/469
Title: Applying Machine Learning Techniques to Categorize and Reduce Stress in Human Beings.
Authors: Swamy, M. R.
Swarna, Shilpitha
Hegde, Ramesh
Keywords: Computer science
Machine learning techniques
Wearable sensors
Issue Date: Feb-2018
Publisher: IJRITCC
Citation: Swamy, M. R., Swarna, Shilpitha., & Hegde, Ramesh. (2018). Applying Machine Learning Techniques to Categorize and Reduce Stress in Human Beings. International Journal on Recent and Innovation Trends in Computing and Communication, 6(2), 39-42.
Abstract: The number of individuals in the modernworld experience elevated stress level, which is non-specific response on the body and plays a significant toll on health, productivity at work, relationships and also effect overall well-being. Many individuals are not aware of the stress triggers and potential health problems caused by prolonged stress. In order to effectively combat stress and its ill effects on health, stress triggers and responses to stress must be recognized and managed in real time. In this paper, applications of machine learning techniques are suggested to categorize and reduce stress is explored. The idea of monitoring stress and reducingstress usesmethods like personalized music, wallpaper themes, favorite games or favorite food ordering and so on. Activities which reduce stress and their degree of reduction are monitored in real time and based on customized stress reduction portfolio is designed using machine learning algorithms.
URI: http://13.232.72.61:8080/jspui/handle/123456789/469
ISSN: 2321-8169
Appears in Collections:Articles

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