Affiliation:
1. IT Fusion Technology Research Center, Department of IT Fusion Technology, Chosun University, 309 Pilmun-daero Dong-gu Gwangju 61452, Korea
Abstract
In this study, we propose a method to classify individuals under stress and those without stress using k-means clustering. After extracting the R and S peak values from the ECG signal, the heart rate variability is extracted using a fast Fourier transform. Then, a criterion for classifying the ECG signal for the stress state is set, and the stress state is classified through k-means clustering. In addition, the stress level is indicated using the 𝐑 − 𝐒𝐩𝐞𝐚𝐤 value. This method is expected to be applied to the U-healthcare field to help manage the mental health of people suffering from stress.
Publisher
North Atlantic University Union (NAUN)
Subject
General Biochemistry, Genetics and Molecular Biology,Biomedical Engineering,General Medicine,Bioengineering
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