Li and colleagues developed a deep-learning model to analyze EEG recordings and detect event-level EEG spikes. 2. The model achieved high accuracy and a low false-positive rate, with only 32% of human ...
Dallas, Texas - January 29, 2026 - PRESSADVANTAGE - Mindmachines.com, a leading distributor of brainwave entrainment ...
Non-invasive EEG biomarker identifies risk of future cognitive decline long before diagnosis, reinforcing BrainScope's strategic focus on early, actionable dementia detection. ROCKVILLE, ...
New AI model decodes brain signals captured noninvasively via EEG opens the possibility of developing future neuroprosthetics ...
A machine learning model trained on EEG data from patients recovering from strokes helps predict how new patients will regain mobility.
ABSTRACT: Meditation offers a controlled behavioral context for probing attention, arousal, and self-regulation. Rather than positioning the present work as a discovery of novel neural signatures, we ...
An EEG machine is a crucial tool in monitoring brain waves. This part is vital because reliable data requires identifying people and ensuring accuracy. To accomplish this, regular maintenance and ...
Background: Wearable electroencephalography (EEG) devices enable noninvasive, real-time monitoring of cognitive states such as attention and stress. However, their practical deployment is limited by ...
Abstract: Epileptic seizures impair patients’ health and quality of life, and electroencephalography (EEG)-based prediction enables timely intervention. Early work on epileptic seizure prediction ...
Abstract: Stroke remains a leading cause of disability and mortality worldwide, highlighting the need for effective tools for early detection and intervention. Recent research has explored the use of ...
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