A comparative study on machine learning approach towards epileptiform eeg signals detection
Electroencephalogram (EEG) signal is extensively used for the diagnosis of various kinds of neurological brain disorders. The classification of normal and abnormal electrical brain spikes through visual inspection is highly subjective and varying across medical experts. Hence, in this project, comp...
Saved in:
Main Author: | Oh, Pearly Bei Qing |
---|---|
Format: | Final Year Project Report |
Language: | English English |
Published: |
Universiti Malaysia Sarawak, (UNIMAS)
2017
|
Subjects: | |
Online Access: | http://ir.unimas.my/id/eprint/20936/1/A%20comparative%20study%20on%20machine%20learning%20approach...%2824%20pgs%29.pdf http://ir.unimas.my/id/eprint/20936/8/PEARLY%20OH%20BEl%20QING.pdf http://ir.unimas.my/id/eprint/20936/ |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Analysis of EEG signals using mathematical morphology decomposition and kurtosis: Detection of epileptiforms
by: Qayoom, Abdul, et al.
Published: (2014) -
Dysphoria detection using EEG signals
by: Kamaruddin, Norhaslinda, et al.
Published: (2019) -
Feature extraction and classification for EEG signals using wavelet transform and machine learning techniques
by: Amin, Hafeez Ullah, et al.
Published: (2015) -
Early detection on autistic children by using EEG signals
by: KM, Zubair, et al.
Published: (2022) -
Periodic lateralized epileptiform discharges in neuropsychiatric lupus: Association with cerebritis in magnetic resonance imaging and resolution after intravenous immunoglobulin
by: Lim, K-S, et al.
Published: (2010)