Introduction: Brain-computer interfaces (BCIs) leverage EEG signal processing to enable human-machine communication and have broad application potential. However, existing deep learning-based BCI ...

Abstract: The proposed study aimed to discover the development and optimization of an innovative EEG feature extraction technique, namely the S-Transform, for emotion recognition. In this regard, a ...

Design a lightweight machine-learning pipeline that analyzes single-channel frontal EEG data (Fp1/Fp2) and accurately detects driver drowsiness in real-time. 50 Hz IIR notch filter + 0.5–30 Hz ...

Electroencephalogram (EEG) signal analysis plays a vital role in diagnosing and monitoring alcoholism, where accurate classification of individuals into alcoholic and control groups is essential.

This project demonstrates the design and development of an open-source, homebrew single-lead EEG acquisition and preprocessing system. It spans circuit-level prototyping, simulation (Simscape), ...

ABSTRACT: This paper reviews fault identification and predictive maintenance techniques essential for the reliable operation of high-voltage power systems. The increasing integration of renewable ...

Abstract: This paper introduces MNE-RT, a Python package designed for real-time neural feature extraction from magne-toencephalography (MEG) and electroencephalography (EEG) signals in Brain-Computer ...