Researchers from University of California San Diego have found a way to distinguish among hand gestures that people are making by examining only data from noninvasive brain imaging, without information from the hands themselves. The results are an early step in developing a non-invasive brain-computer interface that may one day allow patients with paralysis, amputated limbs or other physical challenges to use their mind to control a device that assists with everyday tasks.
The researchers underscored the advantages of MEG, which uses a helmet with embedded 306-sensor array to detect the magnetic fields produced by neuronal electric currents moving between neurons in the brain. Alternate brain-computer interface techniques include electrocorticography (ECoG), which requires surgical implantation of electrodes on the brain surface, and scalp electroencephalography (EEG), which locates brain activity less precisely.
More information: