ArticleSensors (Basel, Switzerland)2021
EEG Mental Stress Assessment Using Hybrid Multi-Domain Feature Sets of Functional Connectivity Network and Time-Frequency Features.
Article in Sensors (Basel, Switzerland), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers, 1 of them a synthesis that pooled it.
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Who cites it
14 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Human-Centric Cognitive State Recognition Using Physiological Signals: A Systematic Review of Machine Learning Strategies Across Application Domains.Sensors (Basel, Switzerland) · 2025Pooled it
- Heartfulness Meditation-induced State and Trait Effects on Long-term, Short-term and Non-meditators Using Connectivity Analysis: An EEG Study on Prefrontal Cortex.Annals of neurosciences · 2026Article
- Machine-learning methods for epilepsy diagnosis and therapeutic prevention: advances, setbacks, and opportunities.Neurological sciences : official journal of the Italian Neurological Society and of the Italian Society of Clinical Neurophysiology · 2026Review
- Impact of stress on EEG functional connectivity during procedural learning.Clinical neurophysiology practice · 2026Article
- Neurocardiac signatures of acute mental stress: a sex-comparative study.Frontiers in neuroscience · 2025Article
- The influence of mental calculations on brain regions and heart rates.Scientific reports · 2024Article
- Mental Stress Classification Based on Selected Electroencephalography Channels Using Correlation Coefficient of Hjorth Parameters.Brain sciences · 2023Article
- Source-Space Brain Functional Connectivity Features in Electroencephalogram-Based Driver Fatigue Classification.Sensors (Basel, Switzerland) · 2023Article
- Article
- EEG Signal Processing for Biomedical Applications.Sensors (Basel, Switzerland) · 2022Article
- Complex Pearson Correlation Coefficient for EEG Connectivity Analysis.Sensors (Basel, Switzerland) · 2022Article
- Enhancing EEG-Based Mental Stress State Recognition Using an Improved Hybrid Feature Selection Algorithm.Sensors (Basel, Switzerland) · 2021Article
- Attention-based multi-feature fusion neuromarker for EEG-driven stress classification in learners.International journal of clinical and health psychology : IJCHPArticle
- Capturing the multimodal dynamics of acute stress responses: Evidence from the Montreal Imaging Stress Task (MIST).International journal of clinical and health psychology : IJCHPArticle
Corrections and comments
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Authors and funding
6 authors.
Funding
Abstract
Exposure to mental stress for long period leads to serious accidents and health problems. To avoid negative consequences on health and safety, it is very important to detect mental stress at its early stages, i.e., when it is still limited to acute or episodic stress. In this study, we developed an experimental protocol to induce two different levels of stress by utilizing a mental arithmetic task with time pressure and negative feedback as the stressors. We assessed the levels of stress on 22 healthy subjects using frontal electroencephalogram (EEG) signals, salivary alpha-amylase level (AAL), and multiple machine learning (ML) classifiers. The EEG signals were analyzed using a fusion of functional connectivity networks estimated by the Phase Locking Value (PLV) and temporal and spectral domain features. A total of 210 different features were extracted from all domains. Only the optimum multi-domain features were used for classification. We then quantified stress levels using statistical analysis and seven ML classifiers. Our result showed that the AAL level was significantly increased (
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