1、BRAIN-COMPUTER INTERFACE (BCI),Presentation by Raghuvarma Basavaraju12/20/08DCS860A,Agenda,What is BCI? BCI Disciplines Why BCI? BCI paradigms Applications of BCI Current trends and Future directions References,What is a BCI?,BCIs read electrical signals or other manifestations of brain activity and
2、 translate them into a digital form that computers can understand, process, and convert into actions of some kind, such as moving a cursor or turning on a TV. BCI can help people with inabilities to control computers, wheelchairs, televisions, or otherdevices with brain activity.,The 3 major compone
3、nts of BCIs 4,Ways of measuring neural signals from the human brain Methods and algorithms for decoding brain states/intentions from these signals and Methodology and algorithms for mapping the decoded brain activity to intended behavior or action.,Invasive versus Non-invasive BCI,Invasive technique
4、s, which implant electrodes directly onto a patients brain; Noninvasive techniques, in which medicalscanning devices or sensors mounted on caps or headbands read brain signals.,BCI Disciplines 1,Nanotechnology Biotechnology Information technology Cognitive science Computer science Biomedical enginee
5、ring Neuroscience Applied mathematics,Why BCI? 2,BCI is a new neuroscience paradigm that might help us better understand how the human brain works in terms of reorganization, learning, memory, attention, thinking, social interaction, motivation, interconnectivity, and much more. BCI research allows
6、us to develop a new class of bioengineering control devices and robots to provide daily life assistance to handicapped and elderly people. Several potential applications of BCI hold promise for rehabilitation and improving performance, such as treating emotional disorders (for example, depression or
7、 anxiety), easing chronic pain, and overcoming movement disabilities due to stroke. BCI can expand possibilities for advanced human computer interfaces (HCIs), making them more natural, flexible, efficient, secure, and user-friendly by enhancing the interaction between the brain, the eyes, the body,
8、 and a robot or a computer.,BCI Paradigms 2,Passive endogenous: specific mental imagination activity for example, motor imagery or mental arithmetic; active endogenous: active neurofeedback and unrestrictedmental imagination using the operant-conditioning principlea “no specifics” cognitive, “just d
9、o it” principle; passive exogenous: responses to externally driven stimuli to evoke specific brain responses called event-related potentials (ERPs); and active exogenous: consciously modified responses to external stimuli, often combined with neurofeedback.,Subjects use specific thoughts as password
10、s (called pass-thoughts).When someone tries to access a protected computer system or building, they think of their pass- thought.A headpiece with electrodes records the brain signals.The system extracts the signals features for computer processing,which includes identification of the feature subset
11、that best and most consistently represents the pass-thought.The biometric system then compares the subset to those recorded for authorized users.,Carleton Universitys proposed BCI-based biometric system 1,Current and future trends in noninvasive BCI 2,Unimodal to multimodal - that is, simultaneous m
12、onitoring of brain activity using several devices and combining BCI with multimodal HCIs; Simple signal-processing tools to more advanced machine learning and multidimensional data mining; Synchronous binary decision to multidegree control and asynchronous self-paced control; Open-loop to closed-loo
13、p control - neurofeedback combined with multimodal HCI; and Laboratory tests to practical trials in the noisy real world environment.,References,Sixto Ortiz Jr., “Brain-Computer Interfaces: Where Human and Machine Meet,“ Computer, vol. 40, no. 1, pp. 17-21, Jan., 2007 Andrzej Cichocki, Yoshikazu Was
14、hizawa, Tomasz Rutkowski, Hovagim Bakardjian, Anh-Huy Phan, Seungjin Choi, Hyekyoung Lee, Qibin Zhao, Liqing Zhang, Yuanqing Li, “Noninvasive BCIs: Multiway Signal-Processing Array Decompositions,“ Computer, vol. 41, no. 10, pp. 34-42, Oct., 2008 Anton Nijholt, Desney Tan, Gert Pfurtscheller, Clemen
15、s Brunner, Jos del R. Mill, Brendan Allison, Bernhard Graimann, Florin Popescu, Benjamin Blankertz, Klaus-R. M?, “Brain-Computer Interfacing for Intelligent Systems,“ IEEE Intelligent Systems, vol. 23, no. 3, pp. 72-79, May/Jun, 2008 1. F. Babiloni, A. Cichocki, and S. Gao, eds., special issue, “Brain-Computer Interfaces: Towards Practical Implementations and Potential Applications,” ComputationalIntelligence and Neuroscience, 2007; P. Sajda, K-R. Mueller, and K.V. Shenoy, eds., special issue, “Brain Computer Interfaces,” IEEE Signal Processing Magazine,Jan. 2008.,
