Design and Simulation of ECG Signal Generator by Making Use of Medical Datasets and Fourier Transform for Various Arrhythmias

2022 ◽  
pp. 577-599
Author(s):  
M. R. Rajeshwari ◽  
K. S. Kavitha
Keyword(s):  
Fourier Transform ◽  
Signal Generator ◽  
Ecg Signal

scholarly journals Stress Classification Using K-means Clustering and Heart Rate Variability from Electrocardiogram

2021 ◽  
Vol 14 ◽  
pp. 251-254
Author(s):  
Mingu Kang ◽  
Siho Shin ◽  
Jaehyo Jung ◽  
Youn Tae Kim
Keyword(s):  
Mental Health ◽  
Heart Rate ◽  
Heart Rate Variability ◽  
Fourier Transform ◽  
Stress State ◽  
Fast Fourier Transform ◽  
Stress Level ◽  
Ecg Signal ◽  
Stress Classification ◽  
S Peak

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.

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