Efficient Method for Stress Detection and Analysis
DOI:
https://doi.org/10.24297/ijrem.v3i3.3941Keywords:
stress, electrocardiogram, feature extraction, classification, ischemia, myocardial infarction.Abstract
ECG is an interpretation of the electrical activity of the heart over time captured and externally recorded by skin electrodes. They are important for diagnostic and research purposes of the human heart. In this paper we discuss a method of detecting stress from a human body using ECG signal sample. A web application has been developed for the same, which works in four basic steps, 1) Signal acquisition, 2) Feature extraction, 3) Classification and 4) Remedies suggestion. This application extracts features of acquired ECG signal and uses these features for categorizing a person basically into stressed mode or relaxed mode. The application is built using a decision support system formed by extensive learning of behavior of the signals of various persons. Algorithm for feature extraction, which is an ineluctable step in most approaches in diagnosing aberrant activities in the heart, is also itemized in this paper.
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