Frontiers

Brain-Computer Interfaces (BCIs) for daily activities: Innovations in EEG signal analysis and machine learning approaches

Brain-Computer Interfaces (BCIs) are emerging as transformative tools that enable direct communication between the human brain and external devices. With recent advancements in Electroencephalography ...
2 Minute Medicine

Deep-learning models displayed expert-level accuracy in detecting epileptiform discharges on electroencephalogram (EEG) recordings

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 ...
9to5Mac

New Apple research hints at how future AirPods could read brain signals

A new study by Apple researchers presents a method that lets an AI model learn one aspect of the structure of brain electrical activity without any annotated data. Here’s how. In a new study called ...
EurekAlert!

Topology-aware deep learning model enhances EEG-based motor imagery decoding

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 ...
Los Angeles Times

Professionals Unlock Hidden Signals of the Mind with Electroencephalography (EEG)?

Hans Berger recorded the first human EEG in 1924. EEG records electrical activity via 16–25 scalp electrodes. Focal “slowing” in brain waves can indicate tumors or lesions. Patients must avoid ...