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Portable Device-Based Stress Level Estimation Using Biological Rhythms

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Data Science and Communication (ICTDsC 2023)

Abstract

Stress creates a major health-related issue in our society, because many health-related problems, such as a lot of economic losses, social disruptions, and human mental problems, are the consequences of it. In general, humans experience stress, especially those who are involved in work in developed capitalist countries and under huge mental workloads continuously and endless technological development. Stressors come across in our daily life (for instance, the difference of opinion among family members or hard work deadlines) and may play a vital role in personal health and well-being. In this study, we introduce a model of health awareness system that incorporates two assessment strategies: questionnaire asking method and physical measurement method, to determine the stress level using the android application-enabled portable device. The questionnaire asking method is useful for detecting psychological and behavioral scores of the stress level. These questionnaires were fixed based on the score of the subjective measure by surveying twenty (20) psychological questions related to the stressor. To estimate the stress level more precisely, we also used the measurement analysis method which includes the physical health-related fitness tests. The application has been developed using android studio IDE and smartphones. By identifying ongoing stress situations using the application, the users can modify physical or behavioral lifestyles to successfully avoid them. It is revealed that such an application can be applied effectively in research experiences and advances the research on stress level estimation.

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Correspondence to Md. Golam Rashed .

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Hossain, I., Rashed, M., Das, D., Julkarnain, M., Deka, V., Debnath, P.P. (2024). Portable Device-Based Stress Level Estimation Using Biological Rhythms. In: Tavares, J.M.R.S., Rodrigues, J.J.P.C., Misra, D., Bhattacherjee, D. (eds) Data Science and Communication. ICTDsC 2023. Studies in Autonomic, Data-driven and Industrial Computing. Springer, Singapore. https://doi.org/10.1007/978-981-99-5435-3_2

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