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- W2809842008 abstract "Mental stress is common in today's world and it influences many physiological functions of the body predominantly the cardiovascular system. This stress detection is very important because it devotes to diverse pathological changes including sudden cardiac death, myocardial infarction and wall motion abnormalities etc. There are various parameters on which stress can be identified. Here we have taken the stress database of person who is in stress before the day of his seminar presentation and examination. In this paper we have focused on the parameter heart rate variability (HRV) as a main approach for detecting stress. Heart rate variability (HRV) analyzed by using time domain, frequency domain method as well as geometrical method. From Time domain method, the features like SDRR (The RR intervals standard deviation), RMSSD (The square root of the mean of the sum of the squares of differences between consecutive RR interval's) and pRR50 (RR50 count divided by the total number of all RR intervals) were calculated. And Frequency domain features have determined by calculating power spectral density of HRV and the spectral response divided into three main components that are, very low frequency (VLF) component, low frequency (LF) component and high frequency (HF) component. Whereas the geometrical features are obtained from poincare plot." @default.
- W2809842008 created "2018-07-10" @default.
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- W2809842008 creator A5060441572 @default.
- W2809842008 date "2017-08-01" @default.
- W2809842008 modified "2023-10-16" @default.
- W2809842008 title "Stress detection of students at academic level from heart rate variability" @default.
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- W2809842008 doi "https://doi.org/10.1109/icecds.2017.8389833" @default.
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