Abstract
The article describes design process of a controlling an electric DC motor based on Electrooculography (EOG). In first paragraph authors presented information about Electroencephalography (EEG) and Electrooculography (EOG). Authors performed a literature overview concerning on that two techniques. In the next step, authors implemented simplified mathematical model of DC motor and PID controller. The system was built with used of the bioactive sensors mounted on the head, which was triggered by the signal from eyes movement and facial expressions. The built interface has been tested. Three experiments were created. In all three experiments, three people aged 25–35 were involved. Each of them conducted from 5 to 10 attempts each scenario. Between attempts respondent had a 1-min break. Each scenario was more difficult than before. The investigators attempted to enter a virtual red dot into the green square using only eyes movement and blinking.
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References
Hennessey, C., Fiset, J.: Long range eye tracking: bringing eye tracking into the living room. In: Proceedings of the Symposium on Eye Tracking Research and Applications, New York, NY, USA, pp. 249–252 (2012)
Arief, Z., Sulistijono, I.A., Ardiansyah, R.A.: Comparison of five time series EMG features extractions using Myo Armband. In: 2015 International Electronics Symposium (IES), pp. 11–14 (2015)
Kubacki, A., Jakubowski, A., Sawicki, L.: Detection of artefacts from the motion of the eyelids created during EEG research using artificial neural network. In: Advances in Intelligent Systems and Computing, vol. 440, pp. 267–275 (2016)
Wolpaw, J.R., Birbaumer, N., McFarland, D.J., Pfurtscheller, G., Vaughan, T.M.: Brain–computer interfaces for communication and control. Clini. Neurophysiol. 113(6), 767–791 (2002)
Bi, L., Fan, X.A., Jie, K., Teng, T., Ding, H., Liu, Y.: Using a head-up display-based steady-state visually evoked potential brain-computer interface to control a simulated vehicle. IEEE Trans. Intell. Trans. Syst. 15(3), 959–966 (2014)
Varadan, V.K., Oh, S., Kwon, H., Hankins, P.: Wireless point-of-care diagnosis for sleep disorder with dry nanowire electrodes. J. Nanotechnol. Eng. Med. 1(3), 031012 (2010)
O’Regan, S., Faul, S., Marnane, W.: Automatic detection of EEG artefacts arising from head movements. In: 2010 Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), pp. 6353–6356 (2010)
Duchowski, A.: Eye Tracking Methodology Theory and Practice, pp. 70–74. Springer, London (2007)
Soleymani, M., Asghari-Esfeden, S., Fu, Y., Pantic, M.: Analysis of EEG signals and facial expressions for continuous emotion detection. IEEE Trans. Affect. Comput. 7(1), 17–28 (2016)
Gupta, S.S., Soman, S., Raj, P.G., Prakash, R., Sailaja, S., Borgohain, R.: Detecting eye movements in EEG for controlling devices. In: 2012 IEEE International Conference on Computational Intelligence and Cybernetics (CyberneticsCom), pp. 69–73 (2012)
Champaty, B., Jose, J., Pal, K., Thirugnanam, A.: Development of EOG based human machine interface control system for motorized wheelchair. In: 2014 Annual International Conference on Emerging Research Areas: Magnetics, Machines and Drives (AICERA/iCMMD), pp. 1–7 (2014)
Aungsakun, S., Phinyomark, A., Phukpattaranont, P., Limsakul, C.: Development of robust electrooculography (EOG)-based human-computer interface controlled by eight-directional eye movements. IJPS 7(14), 2196–2208 (2012)
English, E., Hung, A., Kesten, E., Latulipe, D., Jin, Z.: EyePhone: a mobile EOG-based human-computer interface for assistive healthcare. In: 2013 6th International IEEE/EMBS Conference on Neural Engineering (NER), pp. 105–108 (2013)
Kim, M., Kim, B.H., Jo, S.: Quantitative evaluation of a low-cost noninvasive hybrid interface based on EEG and eye movement. IEEE Trans. Neural Syst. Rehabil. Eng. 23(2), 159–168 (2015)
Emotiv EPOC+ Specification. http://emotiv.com/
Mathematical Modeling of Engineering Systems. http://www.profjrwhite.com/system_dynamics/sdyn/s6/s6fmathm/s6fmathm.html
Acknowledgements
The work described in this paper was funded from 02/23/DS-PB/120 (Nowe techniki w urządzeniach mechatronicznych).
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Kubacki, A., Owczarek, P., Lindner, T. (2018). Use of Electrooculography (EOG) and Facial Expressions as Part of the Brain-Computer Interface (BCI) for Controlling an Electric DC Motor. In: Szewczyk, R., Zieliński, C., Kaliczyńska, M. (eds) Automation 2018. AUTOMATION 2018. Advances in Intelligent Systems and Computing, vol 743. Springer, Cham. https://doi.org/10.1007/978-3-319-77179-3_8
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DOI: https://doi.org/10.1007/978-3-319-77179-3_8
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