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Brain-computer interface for mobile devices

Treść / Zawartość
Identyfikatory
Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
The article presents the results of research in controlling the mobile application with the EEG signals and eye blinking. Authors proposed a prototype solution of a brain-computer interface that can be used by people with total motor impairment to control chosen mobile application on their mobile phone. There was a NeuroSky MindWave Mobile device used during experiments. Two software tools for mobile devices were specially implemented. First one helps to analyse the EEG signals and recognize eye blinks, second one - interprets them and executes assigned actions. Different configurations of settings were used during the studies. They included: single blink or double blink, level of focus, period of focus. Experiments results show that a man equipped with a personal EEG sensor and eye blinking detector can remotely touchless use mobile applications installed on smartphones or tablets.
Rocznik
Tom
Strony
215--222
Opis fizyczny
Bibliogr. 25 poz., rys., tab.
Twórcy
autor
  • Institute of Informatics, Silesian University of Technology, 16 Akademicka Str., 44-100 Gliwice
autor
  • Institute of Informatics, Silesian University of Technology, 16 Akademicka Str., 44-100 Gliwice
Bibliografia
  • [1] CAMPBELL A., CHOUDHURY T., HU S., LU H., MUKERJEE M. K., RABBI M., RAIZADA R. D. Neurophone: Brainmobile phone interface using a wireless eeg headset. Proceedings of the Second ACM SIGCOMM Workshop on Networking, Systems, and Applications on Mobile Handhelds, 2010, MobiHeld ’10. ACM, New York, NY, USA, pp. 3– 8.
  • [2] CECOTTI H. A self-paced and calibration-less ssvep-based braincomputer interface speller. IEEE Transactions on Neural Systems and Rehabilitation Engineering, 2010, Vol. 18. pp. 127–133.
  • [3] CHAPIN J., MOXON K., MARKOWITZ R., NICOLELIS M. Real-time control of a robot arm using simultaneously recorded neurons in the motor cortex. Nature Neuroscience, 1999, Vol. 2. pp. 664–670.
  • [4] EMOTIVSYSTEMS. Emotiv - brain computer interface technology. http://emotiv.com.
  • [5] FETZ E. Real-time control of a robotic arm by neuronal ensembles. Nature America Inc., 1999, Vol. 2. pp. 664–670.
  • [6] HWANG H., KIM S., CHOI S., IM C. Eeg-based brain-computer interfaces: A thorough literature survey. International Journal of HumanComputer Interaction, 2013, Vol. 29. pp. 814–826.
  • [7] HWANG H. J., LIM J. H., JUNG Y. J., CHOI H., LEE S. W., IM C. H. Development of an ssvep-based bci spelling system adopting a qwerty-style led keyboard. Journal of Neuroscience Methods, 2012, Vol. 208. pp. 59–65.
  • [8] LI K., SANKAR R., ARBEL Y., DONCHIN E. P300 based single trial independent component analysis on eeg signal. Foundations of Augmented Cognition. Neuroergonomics and Operational Neuroscience, 2009, Vol. 5638 of Lecture Notes in Computer Science. pp. 404–410.
  • [9] LIN C.-T., CHEN Y.-C., HUANG T.-Y., CHIU T.-T., KO L.-W., LIANG S.-F., HSIEH H.-Y., HSU S.-H., DUANN J.-R. Development of wireless brain computer interface with embedded multitask scheduling and its application on realtime drivers drowsiness detection and warning. Biomedical Engineering, IEEE Transactions, 2008, Vol. 55. pp. 1582–1591.
  • [10] LIN C.-T., KO L.-W., CHANG C.-J., WANG Y.-T., CHUNG C.-H., YANG F.-S., DUANN J.-R., JUNG T.-P., CHIOU J.-C. Wearable and wireless brain-computer interface and its applications. Foundations of Augmented Cognition. Neuroergonomics and Operational Neuroscience, 2009, Lecture Notes in Computer Science. Springer Berlin Heidelberg, pp. 741–748.
  • [11] LIN C.-T., LIN F.-C., CHEN S.-A., LU S.-W., CHEN T.-C., KO L.-W. Eeg-based braincomputer interface for smart living environment auto-adjustment. Journal of Medical and Biological Engineering, 2010, Vol. 30. pp. 237–245.
  • [12] LINDEN D. The p300: where in the brain is it produced and what does it tell us? The Neuroscientist, 2005, Vol. 11. pp. 563–576.
  • [13] LOTTE F., CONGEDO M., LCUYER A., LAMARCHE F., ARNALDI B. A review of classification algorithms for eeg-based brain-computer interfaces. Journal of Neural Engineering, 2007, Vol. 4. p. R1.
  • [14] MARSHALL D., COYLE D., WILSON S., CALLAGHAN M. Games, gameplay, and bci: The state of the art. Computational Intelligence and AI in Games, IEEE Transactions, 2013, Vol. 5. pp. 82–89.
  • [15] MCFARLAND D., KRUSIENSKI D., SARNACKI W., WOLPAW J. Emulation of computer mouse control with a noninvasive brain-computer interface. Journal of Neural Engineering, 2008, Vol. 5. pp. 101–110.
  • [16] NEUROSKY. Neurosky mindwave mobile. http://store.neurosky.com/products/brainwave-starter-kit.
  • [17] NIJHOLT A., BOS D., REUDERINK B. Turning shortcomings into challenges: Brain-computer interfaces for games. Entertainment Computing, 2009, Vol. 1. p. 8594.
  • [18] PEARLTREES. Comparison of consumer braincomputer interfaces. http://www.pearltrees.com/u/30767383-comparisonencyclopedia.
  • [19] PEREGOA P., TURCONIB A., ANDREONIA G., GAGLIARDIB C. Cognitive ability assessment by brain-computer interface ii: application of a bci-based assessment method for cognitive abilities. Brain-Computer Interfaces, 2014, Vol. 1. pp. 170– 180.
  • [20] POLI R., SALVARIS M., CINEL C. A genetic programming approach to the evolution of braincomputer interfaces for 2-d mousepointer control. Genetic Programming and Evolvable Machines, 2012, Vol. 13. pp. 377–405.
  • [21] STAMPS K., HAMAM Y. Towards inexpensive bci control for wheelchair navigation in the enabled environment - a hardware survey. Brain Informatics, 2010, Vol. 6334 of Lecture Notes in Computer Science. pp. 336–345.
  • [22] TAN D., NIJHOLT A. Brain-computer interaction: Applying our minds to human-computer interaction. 2010. SpringerVerlag.
  • [23] VOLOSYAK I. Ssvep-based bremen-bci interface-boosting information transfer rates. Journal of Neural Engineering, 2011, Vol. 8. p. 036020.
  • [24] WANG Y.-T., WANG Y., JUNG T.-P. A cell-phone-based braincomputer interface for communication in daily life. Journal of Neural Engineering, 2011, Vol. 8. p. 025018.
  • [25] WOLPAW J., MCFARLAND D. Control of a two-dimensional movement signal by a noninvasive brain-computer interface in humans. Proceedings of the National Academy of Sciences of the United States of America, 2004, Vol. 101. p. 1784917854.
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-7a9ae9a4-eb71-47f1-8a08-79c4beca1a6c
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