Dynamic-goal state equations for tracking reaching movements using neural signals

Proceedings of the First IEEE/RAS-EMBS International Conference on Biomedical Robotics and Biomechatronics, 2006, BioRob 2006

Volumn 2006, Issue , 2006, Pages 758-762

  Srinivasan, Lakshminarayan ^a,b,c   Brown, Emery N ^b,c,d  

^a USA   (United States)

^b HARVARD MIT DIVISION OF HEALTH SCIENCES AND TECHNOLOGY   (United States)

^c MASSACHUSETTS GENERAL HOSPITAL   (United States)

^d MASSACHUSETTS INSTITUTE OF TECHNOLOGY   (United States)

Author keywords

Estimation; Goal directed; Motor; Neural prosthetics; State equation

Indexed keywords

MOTOR PROSTHETIC ALGORITHMS; NEURAL PROSTHETICS;

ALGORITHMS; NEUROLOGY; PROBABILISTIC LOGICS; PROSTHETICS; TRACKING (POSITION);

EQUATIONS OF STATE;

EID: 33845568739     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/BIOROB.2006.1639181     Document Type: Conference Paper

References (12)

1. Carmena, J. M., Lebedev, M. A., Crist, R. E., O'Doherty, J. E., Santucci, D. M., Dimitrov, D. F., Patil, P. G., Henriquez, C. S., & Nicolelis, M. A. L. (2003). Learning to control a brain-machine interface for reaching and grasping by primates. Public Library of Science Biology, 1(2), 193-208.
2. Taylor, D. M., Tillery, S. I. H., & Schwartz, A. B. (2002). Direct cortical control of 3D neuroprosthetic devices. Science, 296, 1829-1832.
3. th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, San Francisco, CA
4. Mussallam, S., Corneil, B. D., Greger, B., Scherberger, H., & Andersen, R. A. (2004). Cognitive control signals for neural prosthetics. Science, 305, 258-262.
5. Santhanam, G., Ryu, S. I., Yu, B. M., Afshar, A., Shenoy, K. V. (In Press). A high performance neurally-controlled cursor positioning system. IEEE Engineering in Medicine and Biology (EMBS) 2nd International Conference on Neural Engineering.
6. Srinivasan, L, Eden, U. T., Willsky, A. S., & Brown, E. N. (2005). Goal-directed state equation for tracking reaching movements using neural signals. Proceedings of the 2nd International IEEE EMBS Conference on Neural Engineering, Arlington, VA, p. 352.
7. Cowan, T. M., Taylor, D. M. (2005). Predicting reach goal in a continuous workspace for command of a brain-controlled upper-limb neuroprosthesis. Proceedings of the 2nd International IEEE EMBS Conference on Neural Engineering, Arlington VA, p. 74.
8. Yu, B. M., Santhanam, G., Ryu, S. I., & Shenoy, K. V. (2005). Feedback-directed state transition for recursive Bayesian estimation of goal-directed trajectories. Computational and Systems Neuroscience (COSYNE) meeting, Salt Lake City, UT.
9. Kemere, C., & Meng, T. H. (2005). Optimal estimation of feed-forward-controlled linear systems. IEEE International Conference on Acoustics, Speech and Signal Processing, Philadelphia, PA.
10. Eden, U. T., Frank, L. M., Barbieri, R., Solo, V., & Brown, E. N. (2004). Dynamic analyses of neural encoding by point process adaptive filtering. Neural Computation, 16(5), 971-998.
11. Brockwell, A.E., Rojas, A.L., & Kass, R.E. (2004). Recursive bayesian decoding of motor cortical signals by particle filtering. J. Neurophysiology, 91(4):1899-1907.
12. rd Edition, Vol. 1, Athena Scientific.