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20-06-2024

A Novel Method for Mental Stress Assessment Based on Heart Rate Variability Analysis of Electrocardiogram Signals

Authors: Sanjeev Kumar Saini, Rashmi Gupta

Published in: Wireless Personal Communications | Issue 1/2024

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Abstract

Mental stress and associated heart disorders are some of the considerable causes of death in India and globally, as reported by the World Health Organization (WHO). The long-term presence of mental stress and hypertension in lifestyle can lead to significant disorders, including cardiac arrhythmias. Some researchers in the past have proposed methods to assess mental health by considering various physiological signals and artificial intelligence methods. Most studies have used complex algorithms and a combination of features extracted from bio-signals such as electroencephalogram (EEG), electrocardiogram (ECG), etc. This work aims to develop a simple and efficient method to classify mental stress from Heart Rate Variability (HRV) features of ECG signal. The proposed method for stress assessment is implemented using 1-min segments of real-time ECG signals from the Stress Recognition in Automobile Drivers (SRAD) database. We derived the HRV signal from the de-noised ECG signal and extracted time-domain statistical features. Correlation analysis is applied to statistical HRV features to establish the relationship among different metrics of HRV. The main contribution is to develop a Multiple Linear Regression (MLR) model to predict Heart Rate (HR) using statistically correlated HRV features. Another contribution is the design of a multinomial logistic classifier to classify the mental stress level into three classes: low, medium, and high stress. Simulation results demonstrate that time-domain HRV features are statistically correlated, and with a suitable choice of parameters, the proposed method can achieve a classification accuracy of 90.32%. The findings suggest that using fewer relevant features of ECG, the proposed method provides improved classification performance comparable to the state-of-the-art methods. Because of the non-invasive and simple approach, the proposed technique is suitable for accurately assessing mental stress in real-time environments. The presented approach strongly promotes the development of remote and automatic methods of mental stress assessment for real-world applications using wearable sensors and the Internet of Things.

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Title: A Novel Method for Mental Stress Assessment Based on Heart Rate Variability Analysis of Electrocardiogram Signals
Authors: Sanjeev Kumar Saini
Rashmi Gupta
Publication date: 20-06-2024
Publisher: Springer US
Published in: Wireless Personal Communications / Issue 1/2024
Print ISSN: 0929-6212
Electronic ISSN: 1572-834X
DOI: https://doi.org/10.1007/s11277-024-11317-7

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A Novel Method for Mental Stress Assessment Based on Heart Rate Variability Analysis of Electrocardiogram Signals

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