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Brain-computer interface
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A brain-computer interface (BCI), sometimes called a direct neural interface or a brain-machine interface, is a direct communication pathway between a human or animal brain (or brain cell culture) and an external device. In one-way BCIs, computers either accept commands from the brain or send signals to it (for example, to restore vision) but not both.[1] Two-way BCIs would allow brains and external devices to exchange information in both directions but have yet to be successfully implanted in animals or humans.
In this definition, the word brain means the brain or nervous system of an organic life form rather than the mind. Computer means any processing or computational device, from simple circuits to silicon chips (including hypothetical future technologies such as quantum computing).
Research on BCIs began in the 1970s, but it wasn't until the mid-1990s that the first working experimental implants in humans appeared. Following years of animal experimentation, early working implants in humans now exist, designed to restore damaged hearing, sight and movement. The common thread throughout the research is the remarkable cortical plasticity of the brain, which often adapts to BCIs, treating prostheses controlled by implants as natural limbs. With recent advances in technology and knowledge, pioneering researchers could now conceivably attempt to produce BCIs that augment human functions rather than simply restoring them, previously only the realm of science fiction.
We're still in the extremely early days of neural computing interfaces, but make no mistake about it, when it comes to directly connecting our brains to our hardware, we're ready and rearin' when the gear is. And lucky us, apparently at least one such system will be shown this week at CeBIT developed by none other than Fraunhofer: the aptly and succinctly dubbed Brain Computer Interface (we'd prefer something a little snappier, say, like the Computer Brain Interface, but whatevs). The system reads brain-waves from 128 scalp electrodes -- very slowly, mind you -- and apparently over the last couple of years they've already honed the device to control a pointer and enable trained users to actually write a sentence with their mind alone (even though it may take between five and ten minutes to do so).
[Via Popgadget]
Project Overview
The long-term objective of this research is to create a multi-position, brain-controlled switch that is activated by signals measured directly from an individual’s brain. We believe that such a switch will allow an individual with a severe disability to have effective control of devices such as assistive appliances, computers, and neural prostheses in natural environments. This type of direct-brain interface would increase an individual’s independence, leading to a dramatically improved quality of life and reduce social costs.
Most often the greatest failing of technical aids for persons with severe physical disabilities is the inadequacy of the human-machine interface. With a universal, effective and efficient interface, current technology has the capability of providing substantial independence and hence, a greatly improved quality of life for even the most severely disabled persons. In pursuit of such an ideal interface, researchers have been studying the feasibility of utilizing electrical brain potentials to directly communicate to devices such as a personal computer system.
Dr. Gary Birch, an Adjunct Professor at the Dept. of Electrical and Computer Engineering at UBC and the Executive Director of the Neil Squire Foundation, has spent the last ten years working with other researchers to develop such a direct brain to machine interface.
"It was clear to me that the weakest link in utilizing technology to help people with disabilities is the human machine interface. It is the ability of someone with a disability to be able to control the technology that is the limiting factor, not the technology itself. The ideal interface would be to tap directly into the brain signals."
The technology that we have developed to date is based on methods to detect user-generated patterns in the user’s EEG related to imagined movements. This research is being pursued in three streams:
1) development of new brain-computer interface technology;
2) evaluation of BCI technology across different user populations and under varying conditions; and
3) development of consumer-ready electrode arrays and DSP hardware platform.
Financial Support
This project has been made possible by support from the Natural Sciences and Engineering Research Council of Canada, Grant 90278-96, the Rick Hansen Neurotramuma Initiative, Grant 99031, and by the Government of British Columbia’s Information, Science and Technology Agency.
Progress
Prior to Sept. 1999, the BCI research team had developed a single-position, brain-controlled switch that responds to specific patterns detected in spatiotemporal electroencephalograms (EEG) measured from the human scalp. We refer to our initial design as the Low-Frequency Asynchronous Switch Design (LF-ASD) [2]. Our initial evaluations of the LF-ASD had demonstrated that it was capable of detecting actual motor potentials in able-bodied subjects. This provided the necessary ground for advancing towards the next stage of the research, which was to test the system’s ability in detecting imagined motor potentials in able-bodied individuals (our control population) and individuals with spinal-cord injuries.
Recently our work has focused on verifying LF-ASD function when it is driven by EEG patterns related to imagined movements. This work has taken place at our new experimental recording site at the GF Strong Rehabilitation Center. We are the first research laboratory to attempt to recognize self-paced, imagined movements for a BCI and as such there was no existing protocol for these types of evaluations. We have invested several months developing and testing a suitable experimental methodology (and related equipment) for evaluating the LF-ASD driven by self-paced, imaginary movements. The methodology and equipment were refined in studies involving 6 pilot subjects. The methodology is summarized in [8].
One first on-line study with imagined movements demonstrated that able-bodied subjects using imaginary movements could attain equal or better control accuracies than able-bodied subjects using real movements [8]. Two able-bodied subjects (participating in two sessions each) used imagined finger movements to activate the LF-ASD and trigger events in our experimental video game. These two subjects demonstrated activation accuracies in the range of 70-82% with false activations below 2%. These accuracy rates were encouraging and were comparable to accuracies using actual finger movements, which were observed in the range 36-83%. In terms of overall correct decisions, given that the system was making a classification every 1/8 of a second over a period of an hour, the average classification accuracy was over 99%. We are currently verifying this performance in a large population of subjects.
We have completed a second study, which demonstrated that subjects with high tetraplegia could activate the LF-ASD at levels similar to able-bodied subjects [9]. Two subjects, one C4-C5 and one C5-C6, demonstrated activation accuracies in the range of 44-55% while maintaining false activations below 1%. During this study, we also collected pilot data from the subjects using imagined foot movement to activate the LF-ASD. Using imagined foot movements, the subjects demonstrated the same level of accuracy as with imaged finger movements. If our subjects continue to demonstrate this level of control, we will be able to confidently use the LF-ASD (with our current methods) to capture and study single-trial imagined, voluntary movement-related potentials (IVMRPs) in SCI subjects. This will be a critical tool to improve our understanding of the characteristics of single-trial IVMRPs. With a better understanding of IVMRPs, we should be able to improve the activation accuracy of the LF-ASD by improving its design. Note, the control accuracies reported above are all based on a single configuration of the LF-ASD (i.e., a single set of switch parameters). A preliminary, off-line study with one subject has indicated that after customizing a subset of the LF-ASD parameters, the activation accuracy increased by 10% and false activations decreased by 67%. In the future we expect to see significant improvement in classification accuracy with customization of the full set of LF-ASD parameters, subject training, and improvements to the LF-ASD design. We have already begun exploring methods for automatic, on-line customization. We are currently verifying this performance in a large population of subjects.
There is still a great deal of work and several significant problems must be overcome before an interface of this nature is at a stage where it can be used practically. Despite the fact that there is still several years of work to be carried out, we believe that this concept of mapping imaged motor potentials from persons with severe disabilities to the control of technical aids represents a realistic approach towards a direct brain interface system that utilizes activity related to self-initiated cognitive processes.
Related Publications
Refereed Journals
[1] S.G. Mason and G.E. Birch. A General Framework for Describing Brain-Computer Interface Design and Evaluation, revised and resubmitted to IEEE Trans. Rehab. Engineering, 2000.
[2] S.G. Mason and G.E. Birch. A Brain-Controlled Switch for Asynchronous Control Applications, IEEE Trans. Biomedical Engineering, 47(10), 1297-1307, 2000.
[3] G.E. Birch and S.G. Mason. Brain-Computer Interface Research at the Neil Squire Foundation, IEEE Trans. Rehab. Eng., 8(2), 193-95, 2000.
[4] S.G. Mason, G.E. Birch and M.R. Ito. Improved Single-Trial Signal Extraction of Low SNR Events, IEEE Trans. Signal Processing, 42(2), 423-426, 1994.
[5] Birch, G. E., Lawrence, P. D., and Hare, R. D., Single Trial Processing of Event Related Potentials Using Outlier Information, IEEE Trans Biomed Eng, vol. 40, no. 1, pp. 59-73, 1993.
[6] Birch, G. E., Lawrence, P. D., and Hare, R. D. Single-Trial Processing of Event Related Potentials. The Journal of Psychophysiology, 1988.
Refereed Conferences
تحقیق درباره Brain
