Prediction of ADHD from a small dataset using an adaptive EEG theta/beta ratio and PCA feature extraction
EEG Theta/beta ratio (TBR) is conventionally used as a biomarker in childhood Attention-Deficit/Hyperactivity Disorder (ADHD) prediction and treatment. Due to the heterogeneity of ADHD symptoms, several studies have applied machine learning algorithms for enhancing the recognition of ADHD. These me...
Saved in:
Main Authors: | Sase, Takumi, Othman, Marini |
---|---|
Format: | Conference or Workshop Item |
Language: | English |
Published: |
Springer Nature Switzerland
2022
|
Subjects: | |
Online Access: | http://irep.iium.edu.my/97972/3/97972_Prediction%20of%20ADHD%20from%20a%20Small%20Dataset.pdf http://irep.iium.edu.my/97972/ |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Prediction of ADHD from a small dataset using an adaptive EEG Theta/Beta Ratio and PCA feature extraction
by: Sase, Takumi, et al.
Published: (2022) -
Machine learning approach for stress detection based on alpha-beta and theta-beta ratios of EEG signals
by: Altaf, Hunain, et al.
Published: (2021) -
Electroencephalogram (eeg) stress analysis on alpha/beta ratio and theta/beta ratio
by: Tee, Y. W., et al.
Published: (2020) -
EEG Frontal Theta-Beta Ratio and Frontal Midline Theta for the Assessment of Social Anxiety Disorder
by: Al-Ezzi, A., et al.
Published: (2020) -
EEG Frontal Theta-Beta Ratio and Frontal Midline Theta for the Assessment of Social Anxiety Disorder
by: Al-Ezzi, A., et al.
Published: (2020)