Sensitivity and specificity of upper extremity movements decoded from electrocorticogram

Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS

Volumn , Issue , 2013, Pages 5618-5621

  Do, An H ^a   Wang, Po T ^b   King, Christine E ^b   Schombs, Andrew ^b   Lin, Jack J ^a   Sazgar, Mona ^a   Hsu, Frank P K ^b   Shaw, Susan J ^c,d   Millett, David E ^c,d   Liu, Charles Y ^e,f   Szymanska, Agnieszka A ^b   Chui, Luis A ^a   Nenadic, Zoran ^b  

^a UNIVERSITY OF CALIFORNIA   (United States)

^b UNIVERSITY OF CALIFORNIA   (United States)

^c RANCHO LOS AMIGOS NATIONAL REHABILITATION CENTER   (United States)

^d UNIVERSITY OF SOUTHERN CALIFORNIA   (United States)

^e Dept of Neurosurgery   (United States)

^f UNIVERSITY OF SOUTHERN CALIFORNIA   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ARM MOVEMENTS; ELECTROCORTICOGRAM; ELECTROCORTICOGRAM (ECOG); EPILEPSY SURGERY; INDEPENDENT FUNCTIONS; SENSITIVITY AND SPECIFICITY; UPPER EXTREMITY MOVEMENTS;

BRAIN COMPUTER INTERFACE; DECODING;

ELECTROPHYSIOLOGY;

ADULT; ARM; BRAIN COMPUTER INTERFACE; ELECTROENCEPHALOGRAPHY; FEMALE; HUMAN; LIMB PROSTHESIS; MOVEMENT (PHYSIOLOGY); PHYSIOLOGY; SIGNAL PROCESSING; YOUNG ADULT;

ADULT; ARTIFICIAL LIMBS; BRAIN-COMPUTER INTERFACES; ELECTROENCEPHALOGRAPHY; FEMALE; HUMANS; MOVEMENT; SIGNAL PROCESSING, COMPUTER-ASSISTED; UPPER EXTREMITY; YOUNG ADULT;

EID: 84886451886     PISSN: 1557170X     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/EMBC.2013.6610824     Document Type: Conference Paper

References (17)

1. J. Kub́anek, K.J. Miller, J.G. Ojemann, J.R. Wolpaw, and G. Schalk. Decoding flexion of individual fingers using electrocorticographic signals in humans. J. Neural Eng., 6(6):66001, 2009.
2. Z. Wang, Q. Ji, K.J. Miller, and G. Schalk. Prior knowledge improves decoding of finger flexion from electrocorticographic signals. Front Neurosci, 5:127, 2011.
3. N. Liang and L. Bougrain. Decoding finger flexion from band-specific ECoG signals in humans. Front Neurosci, 6:91, 2012.
4. Z. Wang, A. Gunduz, P. Brunner, A.L. Ritaccio, Q. Ji, and G. Schalk. Decoding onset and direction of movements using electrocorticographic (ECoG) signals in humans. Front Neuroeng, 5:15, 2012.
5. C.M. Chin, M.R. Popovic, A. Thrasher, T. Cameron, A. Lozano, and R. Chen. Identification of arm movements using correlation of electrocorticographic spectral components and kinematic recordings. J Neural Eng, 4(2):146-158, 2007.
6. T. Yanagisawa, M. Hirata, Y. Saitoh, H. Kishima, K. Matsushita, T. Goto, R. Fukuma, H. Yokoi, Y. Kamitani, and T. Yoshimine. Electrocorticographic control of a prosthetic arm in paralyzed patients. Ann Neurol, 71(3):353-361, 2012.
7. J. Wright. The FIMTM, The Center for Outcome Measurement in Brain Injury., 2000. http://www.tbims.org/combi/FIM.
8. P.T. Wang, C.E. King, A.H. Do, and Z. Nenadic. A durable, low-cost electrogoniometer for dynamic measurement of joint trajectories. Med Eng Phys, 33(5):546-552, 2011.
9. A.H. Do, P.T. Wang, A. Abiri, C.E. King, and Z. Nenadic. Braincomputer interface controlled functional electrical stimulation system for ankle movement. J Neuroeng Rehabil, 8(49), 2011.
10. K.J. Miller, M. denNijs, P. Shenoy, J.W. Miller, R.P.N. Rao, and J.G. Ojemann. Real-time functional brain mapping using electrocorticography. Neuroimage, 37(2):504-507, 2007.
11. K.J. Miller, E.C. Leuthardt, G. Schalk, R.P.N. Rao, N.R. Anderson, D.W. Moran, J.W. Miller, and J.G. Ojemann. Spectral changes in cortical surface potentials during motor movement. J Neurosci, 27(9):2424-2432, 2007.
12. K. Das, S. Osechinskiy, and Z. Nenadic. A classwise PCA-based recognition of neural data for brain-computer interfaces. In Proc. 29th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, pages 6519-6522, 2007.
13. K. Das and Z. Nenadic. An efficient discriminant-based solution for small sample size problem. Pattern Recogn, 42(5):857-866, 2009.
14. K. Das and Z. Nenadic. Approximate information discriminant analysis: A computationally simple heteroscedastic feature extraction technique. Pattern Recogn, 41(5):1548-1557, 2008.
15. Z. Nenadic. Information discriminant analysis: Feature extraction with an information-theoretic objective. IEEE Trans. Pattern Anal. Machine Intell., 29(8):1394-1407, 2007.
16. Z. Nenadic, D.S. Rizzuto, R.A. Andersen, and J.W. Burdick. Advances in cognitive neural prosthesis: Recognition of neural data with an information-theoretic objective. In G. Dornhege, J.d.R. Milĺan, T. Hinterberger, D.J. McFarland, and K.-R. Müller, editors, Toward Brain Computer Interfacing, chapter 11, pages 175-190. The MIT Press, 2007.
17. R. Kohavi. A study of cross-validation and bootstrap for accuracy estimation and model selection. In Int. Joint C. Art. Int., pages 1137- 1145, 1995.