Machine Learning and Stress Assessment: A Review

被引:0
作者
Faraz, Syed [1 ]
Ali, Syed Saad Azhar [1 ]
Adil, Syed Hasan [2 ]
机构
[1] Univ Teknol PETRONAS, Ctr Intelligent Signal & Imaging Res, Seri Iskandar, Malaysia
[2] Iqra Univ, Dept Comp Sci, Karachi, Pakistan
来源
2018 3RD INTERNATIONAL CONFERENCE ON EMERGING TRENDS IN ENGINEERING, SCIENCES AND TECHNOLOGY (ICEEST) | 2018年
关键词
Stress-Assessment; Machine Learning; EEG; NEUROFEEDBACK; RECOGNITION; DEPRESSION; TRAUMA; SYSTEM;
D O I
暂无
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
Stress assessment has been considered essentials in the early stages because stress-related abnormalities tend to increase the risk of strokes, heart attacks, depression, and hypertension. This may also induce suicidal thought within the victims of this neurological state. The CAD (Computer Aided Diagnosis) have been a way forward for both medical experts and people with complications. The recent development of Machine learning revolution has proved to be substantial for medical diagnosis and prediction. This approach can further be used with neurological tools. The initial status of the brain activities would act as a window into the brain; which can be used as an insight. With the influence of machine learning more generalized way of discriminating stress activities with other normal activities can be possible.
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页数:4
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