Hybrid approach of EEG stress level classification using K-means clustering and support vector machine
Support vector machine (SVM) algorithms are prevalent in classifying electroencephalogram (EEG) signals for the detection of mental stress at various levels. This study aimed to reduce the subjective bias in form of human stress reactivity, by employing clustering methods to pre-label stress levels...
Saved in:
| Main Authors: | , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Institute of Electrical and Electronics Engineers Inc.
2022
|
| Subjects: | |
| Online Access: | http://eprints.utm.my/104361/1/SitiArmiza2022_HybridApproachofEEGStressLevel.pdf http://eprints.utm.my/104361/ http://dx.doi.org/10.1109/ACCESS.2022.3148380 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|