Comparing methods for decoding movement trajectory from ECoG in chronic stroke patients

Biosystems and Biorobotics

Volumn 12, Issue , 2016, Pages 125-139

  Spüler, Martin ^a   Grimm, Florian ^b   Gharabaghi, Alireza ^b   Bogdan, Martin ^c   Rosenstiel, Wolfgang ^a  

^a UNIVERSITY OF TÜBINGEN   (Germany)

^b UNIVERSITY HOSPITAL TÜBINGEN   (Germany)

^c UNIVERSITY OF LEIPZIG   (Germany)

Author keywords

[No Author keywords available]

Indexed keywords

EID: 85007015016     PISSN: 21953562     EISSN: 21953570     Source Type: Book Series    
DOI: 10.1007/978-3-319-26242-0_9     Document Type: Chapter

References (34)

1. Cramer, S., Nelles, G., Benson, R., Kaplan, J., Parker, R., Kwong, K., Kennedy, D., Finklestein, S., Rosen, B.: A functional MRI study of subjects recovered from hemiparetic stroke. Stroke 28, 2518–2527 (1997)
2. Kwakkel, G., Kollen, B.J., van der Ground, J., Prevo, A.J.: Probability of regaining dexterity in the flaccid upper limb impact of severity of paresis and time since onset in acute stroke. Stroke 34, 2181–2186 (2003)
3. Yanagisawa, T., Hirata, M., Saitoh, Y., Goto, T., Kishima, H., Fukuma, R., Yokoi, H., Kamitani, Y., Yoshimine, T.: Real-time control of a prosthetic hand using human electrocorticography signals: technical note. J. Neurosurg. 114, 1715–1722 (2011)
4. Buch, E., Weber, C., Cohen, L., Braun, C., Dimyan, M., Ard, T., Mellinger, J., Caria, A., Soekadar, S., Fourkas, A., Birbaumer, N.: Think to move: a neuromagnetic brain-computer interface (BCI) system for chronic stroke. Stroke 39, 910–917 (2008)
5. Broetz, D., Braun, C., Weber, C., Soekadar, S., Caria, A., Birbaumer, N.: Combination of brain-computer interface training and goal-directed physical therapy in chronic stroke: a case report. Neurorehabil. Neural Repair 24, 674–679 (2010)
6. Ramos-Murguialday, A., Broetz, D., Rea, M., Läer, L., Yilmaz, Ö., Brasil, F.L., Liberati, G., Curado, M.R., Garcia-Cossio, E., Vyziotis, A., et al.: Brain-machine interface in chronic stroke rehabilitation: a controlled study. Ann. Neurol. 74, 100–108 (2013)
7. Spüler, M., Walter, A., Ramos-Murguialday, A., Naros, G., Birbaumer, N., Gharabaghi, A., Rosenstiel, W., Bogdan, M.: Decoding of motor intentions from epidural ECoG recordings in severely paralyzed chronic stroke patients. J. Neural Eng. 11, 066008 (2014)
8. Gharabaghi, A., Kraus, D., Leao, M.T., Spüler, M., Walter, A., Bogdan, M., Rosenstiel, W., Naros, G., Ziemann, U.: Coupling brain-machine interfaces with cortical stimulation for brain-state dependent stimulation: enhancing motor cortex excitability for neurorehabilitation. Front. Hum. Neurosci. 8 (2014)
9. Gharabaghi, A., Naros, G., Khademi, F., Jesser, J., Spüler, M., Walter, A., Bogdan, M., Rosenstiel, W., Birbaumer, N.: Learned self-regulation of the lesioned brain with epidural electrocorticography. Front. Behav. Neurosci. 8 (2014)
10. Silvoni, S., Ramos-Murguialday, A., Cavinato, M., Volpato, C., Cisotto, G., Turolla, A., Piccione, F., Birbaumer, N.: Brain-computer interface in stroke: a review of progress. Clin. EEG Neurosci. 42, 245–252 (2011)
11. Cirstea, M., Levin, M.F.: Compensatory strategies for reaching in stroke. Brain 123, 940–953 (2000)
12. Lee, M.Y., Park, J.W., Park, R.J., Hong, J.H., Son, S.M., Ahn, S.H., Cho, Y.W., Jang, S.H.: Cortical activation pattern of compensatory movement in stroke patients. NeuroRehabilitation 25, 255–260 (2009)
13. Bin, G., Gao, X., Yan, Z., Hong, B., Gao, S.: An online multi-channel SSVEP-based brain-computer interface using a canonical correlation analysis method. J. Neural Eng. 6, 046002 (2009)
14. Spüler, M., Rosenstiel, W., Bogdan, M.: Online adaptation of a c-VEP Brain-Computer Interface (BCI) based on Error-related potentials and unsupervised learning. PLoS ONE 7, e51077 (2012)
15. Spüler, M., Walter, A., Rosenstiel, W., Bogdan, M.: Spatial filtering based on canonical correlation analysis for classification of evoked or event-related potentials in EEG data. IEEE Trans. Neural Syst. Rehabil. Eng. 22, 1097–1103 (2014)
16. Hotelling, H.: Relations between two sets of variates. Biometrika 28, 321–377 (1936)
17. Hastie, T., Buja, A., Tibshirani, R.: Penalized discriminant analysis. Ann. Stat. 73–102 (1995)
18. Bishop, C.M., et al.: Pattern recognition and machine learning, vol. 1. Springer, New York (2006)
19. Sun, L., Ji, S., Ye, J.: A least squares formulation for canonical correlation analysis. In: Proceedings of the 25th International Conference on Machine Learning. ACM, pp. 1024–1031 (2008)
20. Walter, A., Murguialday, A.R., Spüler, M., Naros, G., Leão, M.T., Gharabaghi, A., Rosenstiel, W., Birbaumer, N., Bogdan, M.: Coupling BCI and cortical stimulation for brain-state-dependent stimulation: methods for spectral estimation in the presence of stimulation after-effects. Front. Neural Circuits 6 (2012)
21. Fugl-Meyer, A., Jääskö, L., Leyman, I., Olsson, S., Steglind, S.: The post-stroke hemiplegic patient. a method for evaluation of physical performance. Scand. J. Rehabil. Med. 7, 13–31 (1975)
22. Burg, J.P.: Maximum entropy spectral analysis. In: 37th Annual International Meeting., Society of Exploration Geophysics (1967)
23. Spüler, M., Rosenstiel, W., Bogdan, M.: A fast feature selection method for high-dimensional MEG BCI data. In: Proceedings of the 5th International Brain-Computer Interface Conference, pp. 24–27. Graz (2011)
24. Phinyomark, A., Chujit, G., Phukpattaranont, P., Limsakul, C., Hu, H.: A preliminary study assessing time-domain EMG features of classifying exercises in preventing falls in the elderly. In: 2012 9th International Conference on Electrical Engineering/Electronics, Computer, Telecommunications and Information Technology (ECTI-CON), pp. 1–4 (2012)
25. Chang, C.C., Lin, C.J.: LIBSVM: a library for support vector machines. ACM Trans. Intell. Syst. Technol. (TIST) 2, 27 (2011)
26. Dunteman, G.H.: Principal components analysis. No. 69. Sage, Newbury Park (1989)
27. Sheikh, H., McFarland, D.J., Sarnacki, W.A., Wolpaw, J.R.: Electroencephalographic (EEG)- based communication: EEG control versus system performance in humans. Neurosci. Lett. 345, 89–92 (2003)
28. Schalk, G., Kubanek, J., Miller, K., Anderson, N., Leuthardt, E., Ojemann, J., Limbrick, D., Moran, D., Gerhardt, L., Wolpaw, J.: Decoding two-dimensional movement trajectories using electrocorticographic signals in humans. J. Neural Eng. 4, 264 (2007)
29. Waldert, S., Pistohl, T., Braun, C., Ball, T., Aertsen, A., Mehring, C.: A review on directional information in neural signals for brain-ymachine interfaces. J. Physiol. Paris 103, 244–254 (2009)
30. Schalk, G., Miller, K., Anderson, N., Wilson, J., Smyth, M., Ojemann, J., Moran, D., Wolpaw, J., Leuthardt, E.: Two-dimensional movement control using electrocorticographic signals in humans. J. Neural Eng. 5, 75–84 (2008)
31. Pistohl, T., Ball, T., Schulze-Bonhage, A., Aertsen, A., Mehring, C.: Prediction of arm movement trajectories from ECoG-recordings in humans. J. Neurosci. Methods 167, 105–114 (2008)
32. Nakanishi, Y., Yanagisawa, T., Shin, D., Fukuma, R., Chen, C., Kambara, H., Yoshimura, N., Hirata, M., Yoshimine, T., Koike, Y.: Prediction of three-dimensional arm trajectories based on ECoG signals recorded from human sensorimotor cortex. PLoS ONE 8, e72085 (2013)
33. Wright, Z.A., Rymer, W.Z., Slutzky, M.W.: Reducing abnormal muscle coactivation after stroke using a myoelectric-computer interface a pilot study. Neurorehabil. Neural Repair 28, 443–451 (2014)
34. Spüler, M., Rosenstiel, W., Bogdan, M.: Predicting wrist movement trajectory from ipsilesional ECoG in chronic stroke patients. In: Proceedings of 2nd International Congress on Neurotechnology, Electronics and Informatics (NEUROTECHNIX), pp. 38–45 (2014)