Systems capable of processing thoughts and translating them into teams for moving objects, very useful for people who can’t speak or move, however they have a drawback: they cause mental fatigue.
Mexican scientist has developed an intelligent interface, able to learn up to 90% of user instructions for offline work and reduce fatigue.
Project entitled “Automation of the front-end system brain-machine “is an initiative of Christian Isaac Peñalosa Sanchez, doctoral candidate in cognitive neurology Applied Robotics at Osaka University, Japan.
“I worked on this project for three years, it is built on the basis of brain machine interface. Its function is to measure the activity of neurons. in order to receive the signal generated by the thought, process and convert it into an order to move, for example, robotic with a prosthesis, a mouse, or household appliances, “says the scientist.
He explains that this system consists of electrodes, located on the scalp of a person. They measure activity. brain in the form of EEG signals. Signals are used to detect patterns generated by various thoughts and mental state user.
The system also includes a graphical interface showing accessible devices or objects that interpret signals EEG and take user commands.
A photo from open sources
In addition, wireless sensors are distributed in the room, collecting environmental data (temperature and lighting); mobile hardware drives that turn devices on and off, as well as an artificial intelligence algorithm.
“The latter collects data from wireless sensors, electrodes and user commands to reveal a correlation between the surrounding the environment of the room, the mental state of man and his activity, “comments Christian Peñalosa.
He adds that in order to save users from mental fatigue and frustration due to high concentrations for extended periods of time that inevitable in working with such systems, this system should become independent. That is what Christian tried to do.
“We gave the system learning opportunities by introducing intelligent Algorithms that gradually study user settings. IN at some point, the system can take control of more part of the device, leaving the user the ability to focus for another purpose. ”
For example, a person can use it to control electric carriage when moving to the living room using basic commands (forward, backward, left and right) that the system is already studied. The next time the user wants to drive one same route, he just needs to press a button or think the stroller itself will take him to his destination.
As soon as the system runs automatically, the user no longer have to focus on managing different devices. However, the system continues to collect EEG data, to detect an error signal. It occurs when people alarming: the system or they themselves did something wrong.
For example, if the temperature in the room is quite high, the user wants the window to open automatically, and instead This system includes a TV. This is the action of the human brain. fixes as erroneous. The system receives an error signal and trying to get better.
Penyalosa’s efforts led to significant results: in a number subjects actually decreased mental fatigue after working with the system. The level of learning of such systems is also substantially increased.
Power of thought
