Brain-machine interfaces (BMIs) also called brain–computer interfaces (BCIs) are a focus of research in computer science. The goal of developing better BMIs is to assist, improve or repair human cognitive or sensory-motor functions.
Researchers at the University of Osaka, Japan (Cognitive Neuroscience Applied to Robotics) are working on a project called “Automating a brain-machine interface system”.
The brain-machine interfaces that this team is developing is measuring the activity of neurons by EEG to identify signals generated by thoughts.
After distinct signal patterns are found, the information is transformed into a signal for movements of, for example, a robotic prosthesis, a computer pointer or house appliances etc.
In addition, the team added several wireless sensors into the system that are continuously detecting and sending environmental information and also mobile hardware actuators that receive the signals to for example turn on and off appliances such as a thermostat based on the wanted room temperature. This all gets controlled via an artificial intelligence (AI) algorithm.
This method to have devices regulate environmental conditions autonomously is not new, but what is new in this system is that the collected data from wireless sensors, electrodes and user commands get correlated between the environment of the room, the mental state of the person and his/her activities. This allows to prevent users that have disabilities to yield to mental fatigue and frustration to operate the system.
The most intriguing part of the system is that it has learning capabilities through the implemented intelligent algorithms, which step by step learn user preferences.
Such a system could be very valuable one day to assist individuals to control an electric wheelchair and move it to another room using basic commands (forward, backward, turns etc.), which are learned by the system.
The next time the user wants to take the same action, he/she only need to think about it for the chair to automatically navigate to the desired destination because the system has already learned to associate the detected brain waves with an action.
The same is true for regulating the room temperature, a thought could control a thermostat or trigger that a window gets opened. Many more applications are thinkable.
If errors occur such as the TV is turned on instead of the window opened, the system needs to be re-trained.
Fascinating technology that can help those who have problems to communicate and/or cannot move their limbs.