A self-organizing maps classifier structure for brain computer interfaces
Bueno, Leandro; Bastos Filho, Teodiano Freire
http://dx.doi.org/10.1590/2446-4740.0753
Res. Biomed. Eng., vol.31, n3, p.232-240, 2015
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Abstract
Introduction: Brain Computer Interfaces provide an alternative communication path to severe paralyzed people and uses electrical signals related to brain activity in order to identify the user’s intention. In this paper a classifier based on a Self-Organizing Map is introduced. Methods: Electroencephalography signal is used on this work as a source for the user’s intention. This signal represents the brain activity and is processed in order to extract the frequency features presented to the classifier, which uses a Self-Organizing Map and a series of probability masks in order to identify the correct class. Results: The proposed structure was evaluated using a dataset of Electroencephalography with three mental tasks. The system was able to identify the different states of the users intention with an accuracy of 71.21% for a three-class problem using only 25 neurons for one of the users. Conclusion: The classifier proposed in this paper has an accuracy that is around the value of similar works in the literature, using the same data, but using a small time window for the classification, meaning the system can have a better time response for the user.
Keywords
Self-organizing map, Brain-Computer interface, BCI, SOM.
References
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Miranda RA, Casebeer WD, Hein AM, Judy JW, Krotkov EP, Laabs TL, Manzo JE, Pankratz KG, Pratt GA, Sanchez JC, Weber DJ, Wheeler TL, Ling GS. DARPA-funded efforts in the development of novel brain-computer interface technologies. Journal of Neuroscience Methods. 2015; 244:52-67. http://dx.doi.org/10.1016/j.jneumeth.2014.07.019. PMid:25107852.
Navarro KF. Wearable, wireless brain computer interfaces in augmented reality environments. In: ITCC 2004: Proceedings of the International Conference on Information Technology: Coding and Computing. IEEE; 2004. Vol. 2, p. 643-7. http://dx.doi.org/10.1109/ITCC.2004.1286726.
Nicolas-Alonso LF, Gomez-Gil J. Brain computer interfaces, a review. Sensors. 2012; 12(2):1211-79. http://dx.doi.org/10.3390/s120201211. PMid:22438708.
Pereira JR, Reis AM, Magalhães Z. Neuroanatomia funcional. Anatomia das áreas activáveis nos usuais paradigmas em ressonância magnética funcional. Acta Medica Portuguesa. 2003; 16(3):107-16. PMid:12868388.
Somervuo P, Kohonen T. Self-organizing maps and learning vector quantization for feature sequences. Neural Processing Letters. 1999; 10(2):151-9. http://dx.doi.org/10.1023/A:1018741720065.
Wolpaw JR, Birbaumer N, McFarland DJ, Pfurtscheller G, Vaughan TM. Brain-computer interfaces for communication and control. Clinical Neurophysiology. 2002; 113(6):767-91. http://dx.doi.org/10.1016/S1388-2457(02)00057-3. PMid:12048038.
Bashashati A, Fatourechi M, Ward RK, Birch GE. A survey of signal processing algorithms in brain-computer interfaces based on electrical brain signals. Journal of Neural Engineering. 2007; 4(2):R32-57. http://dx.doi.org/10.1088/1741-2560/4/2/R03. PMid:17409474.
Benevides AB, Bastos TF Fo, Sarcinelli M Fo. A pseudo-online brain-computer interface with automatic choice for EEG channel and frequency. In: ISCAS 2011: Proceedings of the 2011 IEEE International Symposium of Circuits and Systems. IEEE; 2011. p. 81-4. http://dx.doi.org/10.1109/ISCAS.2011.5937506.
Benevides AB, Bastos TF Fo, Sarcinelli M Fo. Pseudo-online classification of mental tasks using Kullback-Leibler symmetric divergence. Journal of Medical and Biological Engineering. 2012; 32(6):411-6. http://dx.doi.org/10.5405/jmbe.926.
Blankertz B, Müller K, Krusienski DJ, Schalk G, Wolpaw JR, Schlögl A, Pfurtscheller G, Millán J del R, Schröder M, Birbaumer N. The BCI competition. III: validating alternative approaches to actual BCI problems. IEEE Transactions on Neural Systems and Rehabilitation Engineering. 2006; 14(2):153-9. http://dx.doi.org/10.1109/TNSRE.2006.875642. PMID 16792282.
Blankertz B. BCI competition III - Final results [internet]. 2005. 20 p. [cited 2015 Feb 2]. Available from: http://www.bbci.de/competition/iii/results/index.html
Brunner C, Birbaumer N, Blankertz B, Guger C, Kübler A, Mattia D, Millán JDR, Miralles F, Nijholt A, Opisso E, Ramsey N, Salomon P, Müller-Putz GR. BNCI horizon 2020: towards a roadmap for the BCI community. Brain-Computer Interfaces. 2015; 37–41. http://dx.doi.org/10.1080/2326263X.2015.1008956.
Bueno L, Pons JL. Un sistema de interfaz cerebro ordenador basado en redes neuronales auto-organizadas. In: Actas de la 28th Jornadas de Automática [internet]. Huelva, Spain: Comité Español de Automática; 2007. p. 1-7. [cited 2015 Feb 2]. Available from: http://www.ceautomatica.es/old/actividades/jornadas/XXVIII/documentos/1961-JA07-Bueno.pdf
Cotrina A, Benevides A, Ferreira A, Bastos T, Castillo J, Menezes ML, Pereira C. Towards an architecture of a hybrid BCI based on SSVEP-BCI and passive-BCI. In: Proceedings of the 36th Conference of the IEEE Engineering in Medicine and Biology Society. IEEE; 2014. p. 1342-5. http://dx.doi.org/10.1109/EMBC.2014.6943847. PMID 25570215.
Dornhege G, Blankertz B, Curio G, Müller K-R. Boosting bit rates in noninvasive EEG single-trial classifications by feature combination and multiclass paradigms. IEEE Transactions on Biomedical Engineering. 2004; 51(6):993-1002. http://dx.doi.org/10.1109/TBME.2004.827088. PMid:15188870.
Fabiani GE, McFarland DJ, Wolpaw JR, Pfurtscheller G. Conversion of EEG activity into cursor movement by a brain-computer interface (BCI). IEEE Transactions on Neural Systems and Rehabilitation Engineering. 2004; 12(3):331-8. http://dx.doi.org/10.1109/TNSRE.2004.834627. PMid:15473195.
Galán F, Oliva F, Guàrdia J. Using mental tasks transitions detection to improve spontaneous mental activity classification. Medical & Biological Engineering & Computing. 2007; 45(6):603-9. http://dx.doi.org/10.1007/s11517-007-0197-7. PMid:17541665.
Gao X, Xu D, Cheng M, Gao S. A BCI-based environmental controller for the motion-disabled. IEEE Transactions on Neural Systems and Rehabilitation Engineering. 2003; 11(2):137-40. http://dx.doi.org/10.1109/TNSRE.2003.814449. PMid:12899256.
Kohonen T. The self-organizing map. Proceedings of the IEEE. 1990; 78(9):1464-80. http://dx.doi.org/10.1109/5.58325.
Krepki R, Curio G, Blankertz B, Müller K-R. Berlin Brain–Computer Interface—The HCI communication channel for discovery. International Journal of Human-Computer Studies. 2007; 65(5):460-77. http://dx.doi.org/10.1016/j.ijhcs.2006.11.010.
Lebedev MA, Nicolelis MAL. Brain-machine interfaces: past, present and future. Trends in Neurosciences. 2006; 29(9):536-46. http://dx.doi.org/10.1016/j.tins.2006.07.004. PMid:16859758.
Malmivuo J, Plonsey R. Bioelectromagnetism: principles and aplications of bioelectric and biomagnetic fields. 1st ed. New York: Oxford University Press; 1995.
Millan JR. On the need for on-line learning in brain-computer interfaces. In: IEEE 2004: Proceedings of the International Joint Conference on Neural Networks. IEEE; 2004. p. 2877-82. http://dx.doi.org/10.1109/IJCNN.2004.1381116.
Miranda RA, Casebeer WD, Hein AM, Judy JW, Krotkov EP, Laabs TL, Manzo JE, Pankratz KG, Pratt GA, Sanchez JC, Weber DJ, Wheeler TL, Ling GS. DARPA-funded efforts in the development of novel brain-computer interface technologies. Journal of Neuroscience Methods. 2015; 244:52-67. http://dx.doi.org/10.1016/j.jneumeth.2014.07.019. PMid:25107852.
Navarro KF. Wearable, wireless brain computer interfaces in augmented reality environments. In: ITCC 2004: Proceedings of the International Conference on Information Technology: Coding and Computing. IEEE; 2004. Vol. 2, p. 643-7. http://dx.doi.org/10.1109/ITCC.2004.1286726.
Nicolas-Alonso LF, Gomez-Gil J. Brain computer interfaces, a review. Sensors. 2012; 12(2):1211-79. http://dx.doi.org/10.3390/s120201211. PMid:22438708.
Pereira JR, Reis AM, Magalhães Z. Neuroanatomia funcional. Anatomia das áreas activáveis nos usuais paradigmas em ressonância magnética funcional. Acta Medica Portuguesa. 2003; 16(3):107-16. PMid:12868388.
Somervuo P, Kohonen T. Self-organizing maps and learning vector quantization for feature sequences. Neural Processing Letters. 1999; 10(2):151-9. http://dx.doi.org/10.1023/A:1018741720065.
Wolpaw JR, Birbaumer N, McFarland DJ, Pfurtscheller G, Vaughan TM. Brain-computer interfaces for communication and control. Clinical Neurophysiology. 2002; 113(6):767-91. http://dx.doi.org/10.1016/S1388-2457(02)00057-3. PMid:12048038.
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