Non-invasive EEG biomarker identifies risk of future cognitive decline long before diagnosis, reinforcing BrainScope's strategic focus on early, actionable dementia detection. ROCKVILLE, ...
Muse today announced Deep Sleep Boost (DSB), a new sleep feature designed to help users sustain deeper, more stable slow-wave ...
An individual may become completely paralyzed because of any number of accidents that interfere with the functioning of the ...
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 ...
1 Department of Electrical and Computer Engineering, Faculty of Engineering, King Abdulaziz University, Jeddah, Saudi Arabia 2 Center of Excellence in Intelligent Engineering Systems (CEIES), King ...
Abstract: Graph Signal Processing (GSP), an emerging field, provides a flexible framework to model and analyze Electroencephalogram (EEG) sensor data that exhibit intricate relationships and ...
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 ...
Abstract: Alzheimer's disease (AD), is a prevalent neurodegenerative disorder, characterized by cognitive decline. Alongside AD, and Frontotemporal dementia (FTD) poses significant challenges in ...
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