Classifying depression patients and normal subjects using machine learning techniques and nonlinear features from EEG signal

Eeg Signal ◽

Learning Techniques ◽

Nonlinear Features

Prediction of rTMS treatment response in major depressive disorder using machine learning techniques and nonlinear features of EEG signal

Journal of Affective Disorders ◽

10.1016/j.jad.2019.05.070 ◽

2019 ◽

Vol 256 ◽

pp. 132-142 ◽

Cited By ~ 9

Author(s):

Fatemeh Hasanzadeh ◽

Maryam Mohebbi ◽

Reza Rostami

Keyword(s):

Machine Learning ◽

Major Depressive Disorder ◽

Depressive Disorder ◽

Treatment Response ◽

Eeg Signal ◽

Major Depressive ◽

Learning Techniques ◽

Nonlinear Features

Robot Intelligence Technology and Applications - Communications in Computer and Information Science ◽

The Classification of EEG Signal Using Different Machine Learning Techniques for BCI Application

10.1007/978-981-13-7780-8_17 ◽

2019 ◽

pp. 207-221 ◽

Cited By ~ 6

Author(s):

Mamunur Rashid ◽

Norizam Sulaiman ◽

Mahfuzah Mustafa ◽

Sabira Khatun ◽

Bifta Sama Bari

Keyword(s):

Machine Learning ◽

Eeg Signal ◽

2018 Electric Electronics, Computer Science, Biomedical Engineerings' Meeting (EBBT) ◽

EEG signal analysis of patients with epilepsy disorder using machine learning techniques

10.1109/ebbt.2018.8391420 ◽

2018 ◽

Cited By ~ 2

Author(s):

Melike Gunay ◽

Tolga Ensari

Keyword(s):

Machine Learning ◽

Signal Analysis ◽

Eeg Signal ◽

Learning Techniques ◽

Patients With Epilepsy ◽

Eeg Signal Analysis

A Study of Human Sleep Stage Classification Based on Dual Channels of EEG Signal Using Machine Learning Techniques

SN Computer Science ◽

10.1007/s42979-021-00528-5 ◽

2021 ◽

Vol 2 (3) ◽

Author(s):

Santosh Kumar Satapathy ◽

D. Loganathan

Keyword(s):

Machine Learning ◽

Sleep Stage ◽

Eeg Signal ◽

Human Sleep ◽

Learning Techniques ◽

Stage Classification ◽

Sleep Stage Classification ◽

Dual Channels

Modeling, Simulation and Optimization - Smart Innovation, Systems and Technologies ◽

Automated Analysis and Classification of Sleep Stages Based on Machine Learning Techniques from a Dual-Channel EEG Signal

10.1007/978-981-15-9829-6_30 ◽

2021 ◽

pp. 391-403

Author(s):

Santosh Kumar Satapathy ◽

D. Loganathan ◽

Rupalin Nanda

Keyword(s):

Machine Learning ◽

Automated Analysis ◽

Sleep Stages ◽

Eeg Signal ◽

Dual Channel ◽

Proceedings of the 2nd International Conference on Data Engineering and Communication Technology - Advances in Intelligent Systems and Computing ◽

EEG Signal Analysis for Mild Alzheimer’s Disease Diagnosis by Means of Spectral- and Complexity-Based Features and Machine Learning Techniques

10.1007/978-981-13-1610-4_40 ◽

2018 ◽

pp. 395-403

Author(s):

Nilesh Kulkarni

Keyword(s):

Machine Learning ◽

Alzheimer’S Disease ◽

Alzheimer's Disease ◽

Signal Analysis ◽

Disease Diagnosis ◽

Eeg Signal ◽

Learning Techniques ◽

Alzheimer’S Disease Diagnosis ◽

Eeg Signal Analysis

Deep Review of Machine Learning Techniques on Detection of Drowsiness Using EEG Signal

IETE Journal of Research ◽

10.1080/03772063.2021.1913070 ◽

2021 ◽

pp. 1-16

Author(s):

B. Venkata Phanikrishna ◽

Allam Jaya Prakash ◽

Chinara Suchismitha

Keyword(s):

Machine Learning ◽

Eeg Signal ◽

2020 IEEE 7th Uttar Pradesh Section International Conference on Electrical, Electronics and Computer Engineering (UPCON) ◽

A Comparative Assessment of Machine Learning Techniques for Epilepsy Detection using EEG Signal

10.1109/upcon50219.2020.9376567 ◽

2020 ◽

Author(s):

Balan Dhanka ◽

Ankit Vijayvargiya ◽

Rajesh Kumar ◽

Ghanshyam Singh

Keyword(s):

Machine Learning ◽

Comparative Assessment ◽

Eeg Signal ◽

Effect of Linear Features to Determination of Sleep Stages Classification from Dual Channel of EEG Signal Using Machine Learning Techniques

Applications of Internet of Things - Lecture Notes in Networks and Systems ◽

10.1007/978-981-15-6198-6_9 ◽

2020 ◽

pp. 89-105

Author(s):

Santosh Kumar Satapathy ◽

D. Loganathan

Keyword(s):

Machine Learning ◽

Sleep Stages ◽

Eeg Signal ◽

Linear Features ◽

Dual Channel ◽

Data Management, Analytics and Innovation - Advances in Intelligent Systems and Computing ◽

Performance Comparison of Machine Learning Techniques for Epilepsy Classification and Detection in EEG Signal

10.1007/978-981-32-9949-8_29 ◽

2019 ◽

pp. 425-438 ◽

Cited By ~ 1

Author(s):

Rekh Ram Janghel ◽

Archana Verma ◽

Yogesh Kumar Rathore

Keyword(s):

Machine Learning ◽

Performance Comparison ◽

Eeg Signal ◽

Learning Techniques ◽

Epilepsy Classification