Classifying Multi-Level Stress Responses From Brain Cortical EEG in Nurses and Non-Health Professionals Using Machine Learning Auto Encoder

Classifying Multi-Level Stress Responses From Brain Cortical EEG in Nurses and Non-Health Professionals Using Machine Learning Auto Encoder

Objective: Mental stress is a major problem in our society and has become an area of interest for many psychiatric researchers. One primary research focus area is the identification of bio-markers that not only identify stress but also predict the conditions (or tasks) that cause stress. Electroence...

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Bibliographic Details
Main Authors: Ashlesha Akella, Avinash Kumar Singh, Daniel Leong, Sara Lal, Phillip Newton, Roderick Clifton-Bligh, Craig Steven Mclachlan, Sylvia Maria Gustin, Shamona Maharaj, Ty Lees, Zehong Cao, Chin-Teng Lin
Format: Article
Language:English
Published: IEEE 2021-01-01
Series:IEEE Journal of Translational Engineering in Health and Medicine
Subjects:
Autoencoder
support vector machine
stress classification
electroencephalogram
Online Access:https://ieeexplore.ieee.org/document/9424034/

Internet

https://ieeexplore.ieee.org/document/9424034/

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