BCI Framework Based Mind-Wave Game Controller

Dr.V.Dhanakoti, Valliammai Engineering College, Chennai-603203; R.Raja ,Valliammai Engineering College, Chennai-603203

BCI, Electroencephalography, Computer interface

Human-Computer Interaction (HCI) systems may not be suitable for disabled or paralyzed peoples. Brain-Computer Interface (BCI) is an alternative method of communication for disabled or paralyzed peoples. Electroencephalography (EEG) is the non-invasive method of signal acquisition to measure the electrical activity of the brain. This neural oscillations is popularly called brain waves. To make a wireless transmission, the Bluetooth transmitter is integrated with EEG device. The EEG recognized signal may contain the artifacts and noise. To remove this artifacts by using filters and amplifiers is used to amplify the EEG signal. Then the processed EEG signal is transmitted to Bluetooth receiver, which is integrated with microcontroller. Microcontroller sends the control command to the computer system for corresponding EEG signal. Based upon the control command the direction of game is takeover. This device can act as like as the following keys, which is present in the keyboard. The keys are W, A, S and D. This device gives high end user experience of gaming.
    [1] Shitij Kumar, Ferat Sahin, “A framework for a real time intelligent and interactive Brain Computer Interface”, Elsevier, Computers and Electrical Engineering, PP.193–214. 2015. [2] Chin-Teng Lin, Yu-Chieh Chen, Teng-Yi Huang, Tien-Ting Chiu, Li-Wei Ko, Sheng-Fu Liang, Hung-Yi Hsieh, Shang-Hwa Hsu, Jeng-RenDuann, “Development of Wireless Brain Computer Interface With Embedded Multitask Scheduling and its Application on Real-Time Driver’s Drowsiness Detection and Warning”, IEEE transactions on biomedical engineering, Vol.55, Issue.5, PP.1582-1591, 2008. [3] Gerhard M. Friehs, Vasilios A. Zerris, Catherine L. Ojakangas, “Brain–Machine and Brain–Computer Interfaces ”, Stroke Journal, PP.2702-2705, 2004. [4] F. Pichiorri, F. Cincotti, F. De Vico Fallani1, I. Pisotta, G. Morone, M. Molinari, D. Mattia. “Towards a Brain Computer Interface-Based Rehabilitation: from Bench to Bedside”, 5th Int. BCI Conference , PP.268-271, 2011. [5] Lenhardt, A., Kaper, M., & Ritter, “An adaptive P300-based online Brain Computer interface”. IEEE Transactions on Neural Systems and Rehabilitation Engineering, PP.121-130, 2008. [6] Anupama. H.S, N.K.Cauvery, Lingaraju.G.M, “Brain computer interface and its types - a study ”, International Journal of Advances in Engineering & Technology, Vol. 3, Issue.2, PP. 739-745, 2012. [7] Antara Bhattacharya, Dr. N. G. Bawane, S. M. Nirkhi, “Brain Computer Interface Using EEG Signals”. [8] W. D. Penny, S. J. Roberts, E. A. Curran, and M. J. Stokes, “EEG-based communication: A pattern recognition approach”, IEEE Trans. Rehab.Eng., Vol. 8, PP. 214–215, 2000. [9] Rabie A. Ramadan, S. Refat, Marwa A. Elshahed and Rasha A. Ali, “Basics of Brain Computer Interface”, Springer International Publishing Switzerland, PP. 31-50, 2015. [10] Anton Nijholt & Chang S. Nam, “Arts and Brain-Computer Interfaces (BCIs)” , Brain-Computer Interfaces, Taylor & Francis group, Vol. 2, No. 2–3, PP. 57–59, 2015. [11] Gang Wang, ChaolinTeng, Kuo Li, Zhonglin Zhang, Xiangguo Yan, “The Removal of EOG Artifacts From EEG Signals Using Independent Component Analysis and Multivariate Empirical Mode Decomposition”, IEEE journal of biomedical and health informatics, Vol.20, Issue.5, PP.1301-1308, 2016. [12] Georg E. Fabiani, Dennis J. McFarland, Jonathan R. Wolpaw, GertPfurtscheller, “Conversion of EEG Activity Into Cursor Movement by a Brain–Computer Interface (BCI)”, IEEE transactions on neural systems and rehabilitation engineering, Vol.12, Issue.3, PP.331-338, 2004. [13] Miguel Almonacid, Julio Ibarrola, and Jose-Manuel Cano-Izquierdo, “Voting Strategy to Enhance Multi model EEG-Based Classifier Systems for Motor Imagery BCI”, IEEE systems journal, Vol.10, Issue.3, PP.1082-1088, 2016. [14] Ming Cheng, XiaorongGao, ShangkaiGao, DingfengXu, “Design and Implementation of a Brain-Computer Interface With High Transfer Rates”, IEEE transactions on biomedical engineering, Vol.49, Issue.10, PP.1181-1186, 2002. [15] SushilChandraa, GreeshmaSharmaa, Amritha Abdul Salamb, DevendraJhac, AlokPrakash Mittald, “Playing Action Video Games a Key to Cognitive Enhancement”, Procedia Computer Science, PP.115 – 122, 2016
Paper ID: GRDCF003020
Published in: Conference : National Conference on Computational Intelligence Systems (NCCIS - 2017)
Page(s): 95 - 104