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EEG based stress level identification

158 citations0/0 files storedConference proceedings/Conference proceedings - IEEE International Conference on Systems, Man, and Cybernetics

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Emotion and Mood Recognition EEG and Brain-Computer Interfaces Heart Rate Variability and Autonomic Control

Abstract

This paper investigates detection of patterns in brain waves while induced with mental stress. Electroencephalogram (EEG) is the most commonly used brain signal acquisition method as it is simple, economical and portable. An automatic EEG based stress recognition system is designed and implemented in this study with two effective stressors to induce different levels of mental stress. The Stroop colour-word test and mental arithmetic test are used as stressors to induce low level and high level of stress respectively, and their relevant C# applications are developed in Microsoft Visual Studio to interface with Emotiv Epoc device. Power band features from EEG signals are analyzed and using the relative difference of beta and alpha power as feature along with Support Vector Machine as classifier, three-levels of stress can be recognized with an accuracy of 75%. For two-level stress analysis, accuracy of 88% and 96% are achieved for Stroop colour-word test and mental arithmetic test respectively.

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2013The Psychology Experiment Building Language (PEBL) and PEBL Test Battery 2015EEG Based Stress Monitoring

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2020A Wearable EEG Instrument for Real-Time Frontal Asymmetry Monitoring in Worker Stress Analysis 2022Frontal lobe real-time EEG analysis using machine learning techniques for mental stress detection 2020EEG Based Classification of Long-Term Stress Using Psychological Labeling 2020An Effective Mental Stress State Detection and Evaluation System Using Minimum Number of Frontal Brain Electrodes 2024Review of Stress Detection Methods Using Wearable Sensors 2021Detection of Mental Stress through EEG Signal in Virtual Reality Environment 2022Hybrid Approach of EEG Stress Level Classification Using K-Means Clustering and Support Vector Machine 2022MuLHiTA: A Novel Multiclass Classification Framework With Multibranch LSTM and Hierarchical Temporal Attention for Early Detection of Mental Stress

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