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Enhanced control through Brain Computer Interface

With today’s technology the easiest way to establish an interface between the brain and a computer is to look for brain signals related to movement. When you think of moving a hand an electrical signal is generated in a specific part of the brain and researchers have perfected their capability to intercept these signals. The problem is that even for this very specific type of signals the electrical activity of the brain is quite complex and singling out those exact signals from the thousands of others remains challenging.
One can be more accurate if the sensors picking up the signals are placed directly "in the brain". This is done using sensors array implanted on the surface of the brain with tiny spikes entering the brain in sub-millimetric way.
Using this approach researchers demonstrated few years ago, in 2012, the possibility to control a robot to perform like a "hand", picking up a glass, taking it into reach of the paralysed patient to let her drink from a straw.
Now a team of researchers at Stanford has perfected this technology to the point of detecting the intention to select a character on a keyboard displayed on a screen (as part of the Braingate Initiative). The paralysed patient looks with her eyes at the screen and that particular character. This induces tiny movements in the eyes that are controlled by muscles through the electrical activity in the brain. This activity is picked up by the array of sensors implanted in the brain and it is decoded to find intended character.
The experiment has shown that a paralysed patient can "type" with his "mind" at a speed that compares to the one of a person using a keyboard.
Clearly this is a significant result coming to the help of people that have lost the possibility to talk along with being paralysed.
Notice that there is still some training needed. The person has to learn to use the interface, it is not like connecting the sensors to the brain and the computer can detect the intention. Both the person and the computer need to do some training to achieve good result.  Also, the signals intercepted are the ones that would activate the muscles (even though in case of paralysed people the communication channel is broken so the muscle does not receive the signal). It is not really like reading the mind of the person. We are still quite far from that.

About Roberto Saracco

Roberto Saracco fell in love with technology and its implications long time ago. His background is in math and computer science. He's currently the Chair of the Symbiotic Autonomous Systems Initiative of IEEE-FDC. Until April 2017 he led the EIT Digital Italian Node and up to September 2018 he was the Head of the EIT Digital Industrial Doctoral School. Previously, up to December 2011, he was the Director of the Telecom Italia Future Centre in Venice, looking at the interplay of technology evolution, economics and society. At the turn of the century he led a World Bank-Infodev project to stimulate entrepreneurship in Latin America. He is a senior member of IEEE where he leads the Industry Advisory Board within the Future Directions Committee. He teaches a Master course on Technology Forecasting and Market impact at the University of Trento. He has published over 100 papers in journals and magazines and 14 books. He writes a daily blog,  http://sites.ieee.org/futuredirections/category/blog/, with commentary on innovation in various technology and market areas.