EEG-based machine learning predicted SSRI treatment response in depression with high accuracy. Learn how brain signals could ...

An overview of attention detection using EEG signals, which includes six steps: an experimental paradigm design, in which the task and the stimuli are defined and presented to the subjects; EEG data ...

Researchers have developed a machine learning model capable of predicting whether a patient with depression will respond to ...

A dual-network hydrogel (PGEH) cross-linked via liquid metal induction was developed exhibiting remarkable mechanical properties and skin-temperature-triggered on-demand adhesion capabilities. The ...

The first patenting from Encephalogix Inc. details its development of platform that uses machine learning and AI to analyze EEG data that is typically ignored.

DENVER -- A high seizure burden derived by an artificial intelligence (AI) algorithm was associated with worse outcomes, a retrospective analysis showed. Hospitalized patients who had a high seizure ...

People with spinal cord injuries often lose some or all their limb function. In most patients, the nerves in their limbs work ...

People with spinal cord injuries often lose movement even though their brains still send the right signals. Researchers ...

Machine learning decodes brain signals for paralysis recovery in just one second using sensors placed on scalp not inside ...

An individual may become completely paralyzed because of any number of accidents that interfere with the functioning of the ...