D2.1 Requirements and Specification - CORBYS
D2.1 Requirements and Specification - CORBYS
D2.1 Requirements and Specification - CORBYS
Create successful ePaper yourself
Turn your PDF publications into a flip-book with our unique Google optimized e-Paper software.
<strong>D2.1</strong> <strong>Requirements</strong> <strong>and</strong> <strong>Specification</strong><br />
BioEra, n.d. BioEra - visual designer for biofeedback. [online] Available at<br />
[Accessed 13 May 2011].<br />
BioExplorer, n.d. BioExplorer . [online] Available at [Accessed 13<br />
May 2011].<br />
BioSig Project, n.d. The BioSig Project. [online] Available athttp://biosig.sourceforge.net/ [Accessed 13<br />
May 2011].<br />
Birbaumer, N. et al. (1999). A spelling device for the paralysed. Nature, 398:297–298.<br />
Bladon, P., Hall, R. J., Wright, W. A. (2002). Situation Assessment using Graphical Models, Proceedings<br />
of the Fifth International Conference on Information Fusion, Vol. 2, Pages 886-893.<br />
Blahut, R. (1972). Computation of channel capacity <strong>and</strong> rate distortion functions. IEEE Transactions on<br />
Information Theory, 18(4):460–473.<br />
Blanc-Garin, J. (1994). Patterns of recovery from hemiplegia following stroke. Neuropsychological<br />
rehabiliation, 4(4):359385.<br />
Blankertz, B., Curio, G. <strong>and</strong> Mller, K.-R. (2002). Classifying single trial eeg: Towards brain computer<br />
interfacing. In Advances in Neural Inf. Proc. Systems (NIPS 01), 14:157–164.<br />
Blankertz, B., Dornhege, G., Schäfer, C., Krepki, R., Kohlmorgen, J., Müller, K.R., Kunzmann, V., Losch,<br />
F., <strong>and</strong> Curio, G. (2003). Boosting bit rates <strong>and</strong> error detection for the classification of fastpaced motor<br />
comm<strong>and</strong>s based on single-trial eeg analysis. IEEE Trans. Neural Syst. Rehabil. Eng., 11:127–131.<br />
Blasch, E <strong>and</strong> S. Plano, JDL Level 5 fusion model: user refinement issues <strong>and</strong> applications in group<br />
tracking, SPIE Vol 4729, Aerosense, 2002, pp. 270 – 279.<br />
Blaya, J. A. <strong>and</strong> Herr, H. (2004). Adaptive control of a variable-impedance ankle-foot orthosis to assist<br />
drop-foot gait, IEEE Transactions on Neural Systems <strong>and</strong> Rehabilitation Engineering, vol. 12, no. 1, pp.<br />
24-31.<br />
Bolt, R.A. (1980). Put-that-there: Voice <strong>and</strong> gesture at the graphic interface. Computer Graphics,<br />
14(3):262-270.<br />
Bosman, P. A. N. <strong>and</strong> Poutré, H. L. (2007). Learning <strong>and</strong> anticipation in online dynamic optimization with<br />
evolutionary algorithms: The stochastic case. In Proc. GECCO 2007, pages 1165–1172, New York. ACM<br />
Press.<br />
Botvinick, M. M., Braver, T. S., Barch, D. M., Carter, C. S., Cohen, J. D., (2001). Conflict monitoring <strong>and</strong><br />
cognitive control. Psychological Review, 108:624–652.M.S.<br />
Brainterface, n.d. BF++ 2.0: The Body Language Framework. [online] Available<br />
at [Accessed 13 May 2011].<br />
Brenner, N., Bialek, W., <strong>and</strong> de Ruyter van Steveninck, R. (2000). Adaptive rescaling optimizes<br />
information transmission. Neuron, 26:695–702.<br />
Brooks, R. A., (1986). A Robust Layered Control System for a Mobile Robot, IEEE Journal of Robotics<br />
<strong>and</strong> Automation, Vol. 2, No. 1, pp. 14–23.<br />
Brooks, R. A. (1991). Intelligence without representation. Artificial Intelligence, 47(1–3):139–159.<br />
Brown, B. (1970). Recognition of aspects of consciousness through association with eeg alpha activity<br />
represented by a light signal. Psychophysiology, 6:442–452.<br />
Brown, J. <strong>and</strong> Frank, J. (1987). Influence of event anticipation on postural actions accompanying<br />
voluntary movement. Exp. Brain Res., 67:645–650.<br />
Brown, M., Harris, C., (1994). Neurofuzzy Adaptive Modeling <strong>and</strong> Control, Prentice-Hall: Englewood<br />
Cliffs.<br />
Browne, M. <strong>and</strong> Cutmore, T. R. (2002). Low-probability event-detection <strong>and</strong> separation via statistical<br />
wavelet thresholding: an application to psychophysiological denoising. Clin. Neurophysiol., 113(9):1403–<br />
180