The list of mind-controlled robotics keeps growing. New advancements are showing high accuracy and precision without any of the surgical steps required by some brain-computer interfaces. A team of researchers from the University of Minnesota, led by Biomedical Engineering Professor, Bin He, is now testing their BCI that allows the user to control a Parrot AR Drone, in three dimensions, with brain signals.
The system focuses on specific sensorimotor rhythms (SMRs) that the brain generates when it is thinking of a certain muscle contraction. The system still takes months of training to master to the point of driving an AR Drone. Subjects took a three month course, first practicing moving a computer cursor in one direction, then 2 directions before flying a virtual helicopter. Only five students were able to pass these first tests. The signals created by some users were not clear enough for the computer to register and so these trainees were not able to advance. Professor Bin He believes these unclear signals are caused by a lack of bodily awareness. He says his previous research shows that people who practice mediation and yoga are better suited for learning to work with BCIs.
A simple EEG cap fitted on the head of the user is enough to send signal to the computer and send interpretations via Wifi to control the drone. Thinking of clenching the right or left fist will steer it to the right or left accordingly. Clenching both will accelerate the drone upwards. The users were challenged with a field of hoops to fly through and on average; they successfully maneuvered through 90.5% of the targets, flying at an average linear speed of 0.69m/s. They relied on a front-mounted camera that streamed from the POV of the drone and appeared on a screen in front of them.
A conceptual diagram of the potential role of BCI driven telepresence robotics in the restoration of autonomy to a paralyzed individual. The bioelectric signal generated from motor imaginations of the hands is represented in the background of the figure. The signal is acquired through the amplifiers in the subject's workstation where it is then digitized and passed to the computer system. Filtering and further processing of the signal results in a conversion to a control signal that can determine the movement of the quadcopter. Restoration of autonomy and the ability to freely explore the world are the driving factors for the development of the system and can be expanded to control of any number of robotic telepresence or replacement systems. (via IOPScience)
Professor He wants the technology to help disabled people and people with mental disorders to restore user ability to interact with their environment. This non-intrusive BCI is similar in accuracy to systems that use permanent, implanted electrodes. It could be used to control prosthetics, wheelchairs and many other tools, while being accessible for people who do not want to go through with surgery. This latest experiment also displays the potential for telepresense robotics and the role they could have alongside BCIs. The team has published a paper detailing their achievements in the journal Neural Engineering.
(via Nature)
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