Deep learning techniques can enhance diagnosis of Meniere disease (MD) and severity grading, according to a study published ...

An individual may become completely paralyzed because of any number of accidents that interfere with the functioning of the nerves in their body. People who have lost the ability to walk due to spinal ...

Researchers from the Faculty of Engineering at The University of Hong Kong (HKU) have developed two innovative deep-learning ...

Tracking brain waves and eye signals could cut through the noise ...

Researchers at örebro University have developed two new AI models that can analyze the brain's electrical activity and accurately distinguish between healthy individuals and patients with dementia, ...

Researchers develop a novel topology-aware multiscale feature fusion network to enhance the accuracy and robustness of EEG-based motor imagery decoding Electroencephalography (EEG) is a fascinating ...

WASHINGTON — An inspector general’s investigation into Defense Secretary Pete Hegseth’s use of the Signal messaging app to discuss sensitive military operations in Yemen with national security ...

This repository contains the implementation, benchmarks, and supporting tools for my MSc dissertation project: Self-learning Variational Autoencoder for EEG Artifact Removal (Key code only). Benchmark ...

Firefly Neuroscience (NASDAQ:AIFF) stock gained after it unveiled its CLEAR (CLeaning EEG ARtifacts) Platform on Tuesday. This next-generation system is designed to deliver electroencephalogram (EEG) ...

Abstract: Alzheimer's disease (AD), is a prevalent neurodegenerative disorder, characterized by cognitive decline. Alongside AD, and Frontotemporal dementia (FTD) poses significant challenges in ...

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.