Researchers at the University of California, San Francisco have found that machine-learning analysis of brain waves recorded during sleep can identify women at risk of cognitive decline up to five ...

Robots now read brain signals to detect mistakes 300ms before humans react, using EEG technology to create safer ...

Electroencephalography (EEG) signal compression techniques have evolved considerably over recent years, addressing the critical challenge of managing the voluminous datasets generated by ...

Increased communication between the amygdala and hippocampus appear to correlate with symptoms of depression and anxiety, in findings that may have treatment implications, new research suggests.

A machine-learning analysis of brain waves recorded during sleep may help identify people at high risk of developing dementia, according to a study led by UC San Francisco and Beth Israel Deaconess ...

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 ...

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 ...

Researchers at Chiba University in Japan have developed a new artificial intelligence framework capable of decoding complex brain activity with significantly improved accuracy, marking an important ...

The future of electroencephalography (EEG) monitoring may soon look like a strand of hair. In place of the traditional metal electrodes, a web of wires and sticky adhesives, a team of researchers from ...

Motor imagery or imagined limb movements can power brain–computer interface (BCI) devices, such as prostheses and wheelchairs, supporting rehabilitation for people with neuromusculoskeletal disorders.