A State of the Art: EEG-Based Classification and Recognition Models of Mental Stress  

作　　者：Azleena Kamarul Bahrain Zulkifli Mahmoodin Muhammad Noor Nordin Mohd Zubir Suboh Azleena Kamarul Bahrain;Zulkifli Mahmoodin;Muhammad Noor Nordin;Mohd Zubir Suboh(Medical Engineering Technology Section, Universiti Kuala Lumpur-British Malaysian Institute, Selangor, Malaysia)

机构地区：[1]Medical Engineering Technology Section, Universiti Kuala Lumpur-British Malaysian Institute, Selangor, Malaysia

出　　处：《Journal of Computer and Communications》2024年第12期218-245,共28页电脑和通信(英文)

摘　　要：Over the past several decades, numerous methods have been applied by research and professionals to detect and measure mental stress, varying from subjective methods such questionnaires and face-to-face interviews up to the objective methods using physiological signals and neuroimaging equipment such as salivary cortisol and functional magnetic resonance imaging (fMRI), respectively. Among those methods, an Electroencephalograph (EEG) is one of the utmost chosen non-invasive methods by professionals and researchers in recording real time brain signals. This paper highlights the state of art for each of the studies, by comparing and analyzing the method and protocol of EEG data collection, including the selection of electrodes and brain regions involving two major categories of mental stress: acute and chronic. Selection of EEG features, with the necessary signal pre-processing and processing techniques, and the classification models used in these studies have been summarized and discussed.Over the past several decades, numerous methods have been applied by research and professionals to detect and measure mental stress, varying from subjective methods such questionnaires and face-to-face interviews up to the objective methods using physiological signals and neuroimaging equipment such as salivary cortisol and functional magnetic resonance imaging (fMRI), respectively. Among those methods, an Electroencephalograph (EEG) is one of the utmost chosen non-invasive methods by professionals and researchers in recording real time brain signals. This paper highlights the state of art for each of the studies, by comparing and analyzing the method and protocol of EEG data collection, including the selection of electrodes and brain regions involving two major categories of mental stress: acute and chronic. Selection of EEG features, with the necessary signal pre-processing and processing techniques, and the classification models used in these studies have been summarized and discussed.

关 键 词：Electroencephalograph (EEG) Mental Stress Feature Extraction 

分 类 号：R74[医药卫生—神经病学与精神病学]