Abstract
This paper investigated methods of determining stress in humans and developed of smart service system in medicine to automate this process. This paper evaluates existing research in this area. We conducted a study of the method of determining stress levels based on biomedical indicators. Also, we have developed a system that is relevant for use in many different areas. For example, such a system is convenient to use in office firms to prevent overexertion of workers, to prevent emergencies in jobs with a high level of human impact, where human life is endangered, and also for daily use in health care. The smart service system works with input data based on heart rate variability indices. Neural network training has been launched in 100 epochs. In each epoch, the results of accuracy and loss were recorded. Also, for better reliability of the results, we recorded the data obtained not only from training data but also from variation data. As a result, the classification problem is solved. We get 99% accuracy.
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Hentosh, L., Savchyn, V., Kravchenko, O. (2023). A System of Stress Determination Based on Biomedical Indicators. In: Hu, Z., Dychka, I., He, M. (eds) Advances in Computer Science for Engineering and Education VI. ICCSEEA 2023. Lecture Notes on Data Engineering and Communications Technologies, vol 181. Springer, Cham. https://doi.org/10.1007/978-3-031-36118-0_58
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