News

GitHub3y
Feature Extraction of Mental Load EEG signals - GitHub
Contribute to JoyRabha/Feature-Extraction-EEG development by creating an account on GitHub. Skip to content. Navigation Menu Toggle navigation. Sign in Appearance settings. ... 1-Back,2-Back and Idle ...
IEEE9y
Feature extraction with deep belief networks for driver's cognitive states prediction from EEG data
This study considers the prediction of driver's cognitive states from electroencephalographic (EEG) data. Extracting EEG features correlated with driver's cognitive states is key for achieving ...
Frontiers3mon
The performance of domain-based feature extraction on EEG, ECG, and fNIRS for Huntington’s disease diagnosis via shallow machine learning - Frontiers
Each patient finally had 1,200s of data for each of EEG, ECG, and fNIRS, and thus the segmentation created 300 epochs per signal per patient. Finally, each data array was normalized by subtracting the ...
IEEE2y
Haralick feature extraction from time-frequency images for epileptic seizure detection and classification of EEG data
This paper presents novel time-frequency (t-f) features based on t-f image descriptors for the automatic detection and classification of epileptic seizure activities in EEG data. Most previous methods ...
Frontiers8mon
High-order brain network feature extraction and classification method of first-episode schizophrenia: an EEG study - Frontiers
Compared to direct feature extraction from complex EEG data for classification, converting PD into multimodal features offers extremely high interpretability and visualization. To summarize the three ...
GitHub2y
EEG-SIGNAL-ANALYSIS-USING-MACHINE-LEARNING - GitHub
This project uses machine learning algorithms to analyze EEG signals and identify patterns and abnormalities for improved diagnosis and treatment of neurological disorders. It involves pre-processing ...