A breakthrough technology allows individuals to control a robotic arm via a noninvasive brain-computer interface—eliminating the need for surgery.
Although BCIs are proving successful in controlling robotic devices, current devices require invasive implants to function.
As an alternative, the method developed by a team from Carnegie Mellon and the University of Minnesota can detect signals deep within the brain via an external EEG cap. Although the signals detected by an external device tend to be “dirtier” than those collected internally, the team was able to clarify the information using new sensing and machine learning methods. This improved technology allows for a high resolution of control over the robotic arm, and brings us a step closer to non-invasive brain-controlled interfaces.