A Japanese research group developed a BMI (brain machine interface) technology that can continuously estimate the movements of the user's finger and reproduce them by noninvasively measuring the person's brain activity.
The group consists of members of Japan's National Institute of Information and Communications Technology (NICT) and Advanced Telecommunications Research Institute International (ATR).
Existing noninvasive BMI technologies estimate right answers by using several patterns of movements registered in advance. But, with the new technology, it is possible to continuously estimate the two-dimensional coordinates of a fingertip (within a range of 20cm) at a frame rate of 50fps (20ms), which is as high as that of a movie.
The spatial accuracy is 14.7mm. The research group expects that the technology will be used for the remote control of a robot and so forth (See related movie).
In March 2009, ATR announced a technology to control the "Asimo," Honda Motor Co Ltd's humanoid robot, with a BMI technology (See related article). And the latest BMI technology was developed by making improvements to it. While the BMI technology for the Asimo can recognize only four pre-registered patterns of movements (category identification), the new technology can estimate the coordinates of a finger tip, which is a continuous parameter.
"Because the latest BMI technology can smoothly reconfigure rapid movements, it gives the user a feeling of controlling a robot by himself," said Hiroshi Imamizu, Biological ICT Group, NICT.
Combining several brain measurement methods
The BMI technology for the Asimo is used by combining an electroencephalograph (EEG) with a high time resolution and a near-infrared brain measurement device (NIRS, optical topography) with a high spatial resolution in a mutually complementary manner. And the researchers employed the same approach of combining multiple measurement devices for the new technology.
Specifically, they combined a magnetoencephalograph (MEG) with a high time resolution and an fMRI (functional Magnetic Resonance Imaging) with a high spatial resolution. Both of the devices are large and expensive. So, they intend to enable to use the latest technology with a combination of an EEG and a NIRS.
Because brain activity differs from person to person, it is necessary for a BMI system to go through a learning process before using the new BMI technology. When the user is moving the finger tip in eight directions, the brain activity of the person is measured individually by the MEG and the fMRI. And the system learns from the data collected by measuring 200 rounds of fingertip movements per user.
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