Systems able to process thoughts and translate them into a command to move objects are very useful for people who cannot speak or move, but have the disadvantage of causing mental fatigue. However, a Mexican researcher designed an intelligent interface that is capable of learning up to 90 percent of the user's instructions thus operate autonomously and reduce fatigue.
This project, called "Automating a brain-machine interface system", is in charge of Christian Isaac Peñaloza Sanchez, a PhD candidate for Cognitive Neuroscience Applied to Robotics at the University of Osaka, Japan.
"I have worked for three years in this project, based on brain-machine interfaces, whose function is to measure the activity of neurons in order to obtain a signal generated by a thought, which is processed and converted into an indication for moving, for example, a robotic prosthesis, a computer pointer or house appliances," says the scientist, who is part of the Mexican Talent Network, Chapter Japan.
He explains that the system consists of electrodes placed on the scalp of the person, which measure brain activity in form of EEG signals. These are used to detect patterns generated by various thoughts and the mental state of the user (awaken, drowsy or asleep, etc.) and level of concentration.
It also includes a graphical interface that displays the available devices or objects, which interprets EEG signals to assign user commands and control devices.
In addition, there are wireless sensors distributed in the room in charge of sending environmental information (such as temperature or lighting); mobile hardware actuators which receive signals to turn on and off appliances and an artificial intelligence algorithm ( via phys.org ).