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01-Applied Mathematics & Information Sciences
An International Journal
               
 
 
 
 
 
 
 
 
 
 
 
 
 

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Volumes > Volume 17 > No. 5

 
   

Detecting Stress Level Using EEG Signals

PP: 1095-1104
doi:10.18576/amis/170564
Author(s)
V Sharmila1, U Kasthuri,
Abstract
Electroencephalography (EEG) has been a staple strategy for distinguishing specific medical issue in patients since its revelation. Because of the various kinds of classifiers accessible to utilize, the investigation techniques are likewise similarly various. In this survey, we will analyze explicitly AI techniques that have been created for EEG investigation with bioengineering applications. From this data, we can decide the general viability of each AI technique as well as the key qualities. We have observed that every one of the essential techniques utilized in AI have been applied in some structure in EEG order. Stress is defined as a state of mental strain or pressure that arises as a result of distressing or demanding circumstances. (There are several causes of stress. The greatest source of stress, according to researchers, is the human cerebrum. Surveys and monitoring are used by researchers to understand how each individual experiences stress in various forms. The ADT -SVM is used in this study to improve the accuracy of detecting mental stress using EEG data.

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