BCI Text Entry Us ing Hierarchical Keyboard With Probabilistically Dynamic Clustering

dc.contributor.authorHayet, Ishrak
dc.contributor.authorHaq, Tanveer Fahad
dc.date.accessioned2021-10-06T06:57:46Z
dc.date.available2021-10-06T06:57:46Z
dc.date.issued2017-11-15
dc.descriptionSupervised by Dr. Md. Kamrul Hasan, Associate Professor, Co supervisor, Hasan Mahmud, Assistant Professor, Department of Computer Science and Engineering (CSE), Islamic University of Technology (IUT), Board Bazar, Gazipur-1704, Bangladesh.en_US
dc.description.abstractThe ability to feel, adapt, reason, remember and communicate makes human a social being. Disabilities limit opportunities and capabilities to socialize. With the recent advancement in brain computer interface (BCI) technology, researchers are exploring if BCI can be augmented with human computer interaction (HCI) to give a new hope of restoring independence to disabled individuals. This motivates us to lay down our research objective, which is as follows. In this study, we propose to work with a hands free text entry application based on the brain signals, for the task of communication, where the user can select a letter or word based on the intentions of left or right hand movement, and left, right, up or down nodding movement. The three major challenges that have been addressed are (i) interacting with only four imagery signals (ii) how a low quality, noisy EEG signal can be competently processed and classified using novel combination of feature set to make the interface work efficiently, and (iii) using a language prediction model to increase characters per minute.en_US
dc.identifier.citation1. Microsoft, Type without using the key board (On Screen Keyboard). https://support.microsoft.com/en in/help/10762/windows use on screen keyboard 2. Emotiv EPOC, Software Development Kit (2010). http://www.emotiv.com/researchers 3. World report on disability, World Health Organization (2011). ht tp://www.who.int/disabilities/world report/2011/report/en 4. Alomari, M.H., Samaha, A., AlKamha, K.: Automated classification of L/R handmovement EEG signals using advanced feature extraction and machine learning. Int. J. Adv. Comput. Sci. Appl. 4(6) (2013 5. Bin, G., Gao, X., Wang, Y., Li, Y., Hong, B., Gao, S.: A high speed BCI based on code modulation VEP. J. Neural Eng. 8(2), 025015 (2011) 6. Crow, K.L.: Four types of disabilities: their impact on online learning. TechTrends 52(1), 51 55 ( 7. Farw ell, L.A., Donchin, E.: Talking off the top of your head: toward a mental prosthesis utilizing event related brain potentials. Electroencephalogr. Clin. Neurophysiol. 70(6), 510 523 (1988) 8. Graimann, B., Allison, B., Pfurtscheller, G.: Brain computer int erfaces: a gentle introduction. In: Graimann, B., Pfurtscheller, G., Allison, B. (eds.) Brain Computer Interfaces, pp. 1 27. Springer, Heidelberg (2009) 9. Guo, L., Wu, Y., Zhao, L., Cao, T., Yan, W., Shen, X.: Classification of mental task from EEG signal s using immune feature weighted support vector machines. IEEE Trans. Magn. 47(5), 866 869 ( 10. Long, J., Li, Y., Wang, H., Yu, T., Pan, J., Li, F.: A hybrid brain computer interface to control the direction and speed of a simulated or real wheelchair . IEEE Trans. Neural Syst. Rehabil. Eng. 20(5), 720 729 (2012) 11. Prasad, G., Herman, P., Coyle, D., McDonough, S., Crosbie, J.: Using motor imagery based brain computer interface for post stroke rehabilitation. In: 2009 4th International IEEE/EMBS Confer ence on Neural Engineering, pp. 258 262. IEEE (2009) 12. Renard, Y., Lotte, F., Gibert, G., Congedo, M., Maby, E., Delannoy, V., Bertrand, O., Lécuyer, A.: Openvibe: an open source software platform to design, test, and use brain computer interfaces in rea l and virtual environments. Presence 19(1), 35 53 (2010) 13. Ryan, D.B., Frye, G., Townsend, G., Berry, D., Mesa G, S., Gates, N.A., Sellers, E.W.: Predictive spelling with a P300 based brain computer interface: increasing the rate of communication. Int. J . Hum. Comput. Interact. 27(1), 69 84 (2010) References 40 14. Scherer, R., Muller, G., Neuper, C., Graimann, B., Pfurtscheller, G.: An asynchronously 14. Scherer, R., Muller, G., Neuper, C., Graimann, B., Pfurtscheller, G.: An asynchronously controlled EEGcontrolled EEG--based virtual keyboard: improvement of the spelling rate. IEEE Trans. Biomed. based virtual keyboard: improvement of the spelling rate. IEEE Trans. Biomed. Eng. 51(6), 979Eng. 51(6), 979––984 (2004)984 (2004) 15. Spalteholz, L., Li, K.F., Livingston, N., Hamidi, F.: Keysurf: a character controlled browser for 15. Spalteholz, L., Li, K.F., Livingston, N., Hamidi, F.: Keysurf: a character controlled browser for people with physical disabilities. In: Proceedings of the 17th international conference on World people with physical disabilities. In: Proceedings of the 17th international conference on World Wide Web, pp. 31Wide Web, pp. 31––40. ACM (2008)40. ACM (2008) 16. Wolpaw, J., Wolpaw, 16. Wolpaw, J., Wolpaw, E.W.: BrainE.W.: Brain--Computer Interfaces: Principles and Practice. OUP USA, New Computer Interfaces: Principles and Practice. OUP USA, New York (2012)York (2012) 17. Yong, X., Fatourechi, M., Ward, R.K., Birch, G.E.: The design of a point 17. Yong, X., Fatourechi, M., Ward, R.K., Birch, G.E.: The design of a point--andand--click system by click system by integrating a selfintegrating a self--paced brainpaced brain--computer interface with an eyecomputer interface with an eye--tracker. IEEE tracker. IEEE J. Emerg. Sel. Topics J. Emerg. Sel. Topics Circ. Syst. 1(4), 590Circ. Syst. 1(4), 590––602 (2011)602 (2011)en_US
dc.identifier.urihttp://hdl.handle.net/123456789/1110
dc.language.isoenen_US
dc.publisherDepartment of Computer Science and Engineering (CSE), Islamic University of Technology (IUT), Board Bazar, Gazipur-1704, Bangladeshen_US
dc.subjectBrain Computer Interface, Human Computer Interface, EEG, CSP, Hierarchical Keyboard, Proba bilistically Dynamic Clusteringen_US
dc.titleBCI Text Entry Us ing Hierarchical Keyboard With Probabilistically Dynamic Clusteringen_US
dc.typeThesisen_US

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