No-Contact Brain-Machine Interface
[photopress:robot_hand.jpg,full,alignleft]Wouldn’t it be exciting if you could control a machine with your thoughts? Without surgery or electrodes stuck to your scalp, and without a lengthy learning/training process? Well, that possibility is detailed in ATR, Honda Develop New Brain-Machine Interface at PhysOrg.com. The article details how Advanced Telecommunications Research Institute International (ATR) and Honda Research Institute Japan Co. (HRI) have developed a new ?Brain Machine Interface? (BMI) for manipulating robots using brain activity signals. Subjects were able to control the motion of a robotic hand by moving their own hand; the brain activity associated with their hand movements was decoded and turned into instructions for the robot.
Before you start thinking about thought controlled cars or playing Halo 2 without lifting a finger, there are a few restrictions on the newly developed technology. The process uses an MRI scanner to detect brain activity, and there’s a lag of about seven seconds between thinking about the motion and the robotic simulation. The huge bulk and expense of the MRI unit mean that practical applications for this technology aren’t imminent. Still, it’s an exciting step. A press release from Honda states that there are a couple of advantages to their approach compared to other BMI techniques:
1)No Surgery Required
In conventional BMI research efforts led by U.S. neuroscientists, invasive technologies, including electrode array implants, have been used. If advanced non-invasive BMI becomes available, users will be free from the physical burden of a surgical procedure. This research accomplishment demonstrates the possibility of such a useful application.
2)No Specific Training Required
Conventional non-invasive BMI required the user to undergo intensive training in order to generate detectable brain activities. For example, as the brain activity associated with an intention, say “Yes”, is very hard to track, the user is instructed to perform a mental task that is irrelevant to the mental state but associated with easily detectable brain activity such as mental calculation. The user must learn to control such brain activity to express an intention. The new BMI technology is different in that natural brain activity associated with specific movements can be decoded without using alternative brain activity. The experiment revealed that paper-rock-scissors movements were decoded directly from an untrained subject’s real-time brain activity. This is an outstanding breakthrough in brain decoding technologies.
Rather optimistically, the release notes, “The system is aimed for applications of BMI to everyday life, without need for surgery or intensive user training.” Clearly, we can’t walk around encased in fMRI scanners… but now that the feasibility has been demonstrated in this minimal way, no doubt research will focus on faster, cheaper, and simpler ways to measure that same brain activity. It’s unlikely that neuromarketing applications will drive the development of cheap fMRI-equivalent systems. Nevertheless, it would certanly be a benefit to advertisers and marketers if techniques developed by automotive and consumer firms for eventual mass production could be spun off for neuromarketing applications. The current slow and expensive fMRI-based process for evaluating TV ads, for example, could be transformed into something as simple and cheap as organizing a focus group. That’s wishful thinking for now, but it’s nice to imagine…