Home automation machines (such as wheelchairs and other devices) controlled by EEG have provided severely disabled patients with a greater option for autonomy. However, these EEG-controlled devices are not often ideal. Many times it can be difficult for the user to focus their thoughts in order to specify commands in a way that the device can understand, ultimately leading to brain fatigue. A PhD student by the name of Peñaloza Sanchez studying at the University of Osaka in Japan is trying to create a solution to the conflicts that come with EEG-controlled devices by developing a learning mechanism to use with the EEG brain-computer interface.
So far the results have been promising. The new system can recognize patterns in a user’s brain activity and record them for future reference. In addition, the system is paired with sensors placed around the room which gain information on temperature, whether or not doors are open, and whether appliances have been left on in order to better predict the user’s commands. In addition, the system has algorithms to predict the user’s brain response to error. If an error is detected the system will cancel the action.