Dr Andrei Alexandrov discusses his experience implementing point-of-care EEG equipped with artificial intelligence. As neurologists, our responsibility goes beyond interpreting electroencephalograms ...

Start your journey into machine learning with EEG time-series data in this easy-to-follow Python project. Perfect for beginners looking to explore brain signal analysis! #MachineLearning #EEG ...

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 ...

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 ...

Schizophrenia (SCZ) is a severe mental disorder that impairs brain function and daily life, while its early and objective diagnosis remains a major clinical challenge due to the reliance on subjective ...

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 presents a novel low-complexity VLSI architecture for an EEG Feature Extraction Platform for wearable health monitoring systems. It integrates a processing core unit, ...

Abstract: Electroencephalography is a clinical technique which reads the scalp electrical activity from brain structures. The electroencephalogram (EEG) records the scalp surface using metal ...