Nature

Classification of mental workload using brain connectivity and machine learning on electroencephalogram data

Mental workload refers to the cognitive effort required to perform tasks, and it is an important factor in various fields, including system design, clinical medicine, and industrial applications. In ...
EurekAlert!

Attention detection using EEG signals and machine learning: A review

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 ...
Nature

Retraining and evaluation of machine learning and deep learning models for seizure classification from EEG data

Electroencephalography (EEG) is one of the most used techniques to perform diagnosis of epilepsy. However, manual annotation of seizures in EEG data is a major time-consuming step in the analysis ...
Indiatimes

Early EEG data, machine learning can help predict antidepressant treatment response, finds study by scientists from IIT Madras and Czech Academy of Sciences

Chennai: Data from the neurophysiological test, electroencephalography (EEG), used to measure and record the brain's electrical activity, can predict if treatment such as stimulation or ...