Electroencephalogram stress level classification using k-means clustering and support vector machine
Stress is the body’s natural reaction to life events and chronic stress disrupts the physiological equilibrium of the body which ultimately contributes to negative impact on physical and mental health. For this reason, an endeavour to develop stress level monitoring system is necessary and important...
Saved in:
Main Author: | Tee, Yi Wen |
---|---|
Format: | Thesis |
Language: | English |
Published: |
2021
|
Subjects: | |
Online Access: | http://eprints.utm.my/107084/1/TeeYiWenMFTIR2021.pdf |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Brain balancing level classification using deep neural network architecture on electroencephalogram signal
by: Lim, Zheng You
Published: (2022) -
Learner's brain Electroencephalogram subbands for Kolb's learning style classification (IR)
by: Nazre Abdul Rashid
Published: (2018) -
Traffic-signage detection and recognition on K-means clustering and Support Vector Machine classification
by: Quek, Kelvin Wei Luo
Published: (2014) -
A novel technique to identify source of the Neutral to Earth Voltage (NTEV) using support vector machine (SVM) based on timefrequency analysis / Mohd Abdul Talib Mat Yusoh
by: Mat Yusoh, Mohd Abdul Talib
Published: (2019) -
Neural Network in Biometrics : A Survey in Fingerprint Classification
by: Sarah Nazuha, Mohamad Nasir
Published: (2003)