An EEG mobile device as a game controller

Dawid, Aleksander; Buchwald, Paweł

doi:10.34808/tq2021/25.4/b

Artykuł - szczegóły

Tytuł artykułu

An EEG mobile device as a game controller

Autorzy

Dawid Aleksander , Buchwald Paweł

Treść / Zawartość

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DOI

10.34808/tq2021/25.4/b

Warianty tytułu

Języki publikacji

Abstrakty

In this work the real-time control of computer games was explored by a single elec-trode mobile electroencephalography (EEG) device with a Bluetooth interface. The amplitudevariation in the two frequency bands of 4-12 Hz and 60-200 Hz was selected as the real-timecontrol parameter. The frequency-domain of a raw EEG signal was calculated using the discreteFourier transform. The time-dependent signal samples equal to 512, 1024, and 2048 time pointsin size were used in our research. The well-known classic Pong game was used to try out ourcontroller. The developed software handles communication with the device and real-time gamerendering. The .NET Framework with the C# programming language was used as a develop-ment tool. 50 gameplay trials were made for each controller setup. The obtained results arepromising for the possible use of the device in real-time communication with computer devicesfor people with hand disabilities.

Słowa kluczowe

EEG EEG signal disturbance signal processing amplitude driven control game controllers

EEG zakłócenia sygnału EEG przetwarzanie sygnału sterowanie amplituda kontrolery gier

Wydawca

Politechnika Gdańska

Czasopismo

TASK Quarterly : scientific bulletin of Academic Computer Centre in Gdansk

Rocznik

2021

Tom

Vol. 25, No 4

Strony

397--407

Opis fizyczny

Bibliogr. 25 poz., rys.

Twórcy

autor

Dawid Aleksander

adawid@wsb.edu.pl

Department of Transport and Computer Science, WSB University, Cieplaka 1c, 41-300 Dąbrowa Górnicza, Poland

autor

Buchwald Paweł

Department of Transport and Computer Science, WSB University, Cieplaka 1c, 41-300 Dąbrowa Górnicza, Poland

Bibliografia

[1] Berger H 1929 Über das Elektrenkephalogramm des Menschen, Arch. Für Psychiatr. Nervenkrankh 87 527-570 doi: https://doi.org/10.1007/BF01797193
[2] Vidal J J 1977 Real-time detection of brain events in EEG, Proc. IEEE. 65 633–641 doi: https://doi.org/10.1109/PROC.1977.10542
[3] Liu N H, Chiang C Y and Chu H C 2013 Recognizing the Degree of Human Attention Using EEG Signals from Mobile Sensors, Sensors 13 10273–10286 doi: https://doi.org/10.3390/s130810273
[4] Durka P J, Kuś R, Żygierewicz J, Michalska M, Milanowski P, Łabęcki M, Spustek T, Laszuk D, Duszyk A and Kruszyński M 2012 User-centered design of brain-computer interfaces: OpenBCI.pl and BCI Appliance, Bull. Pol. Acad. Sci. Tech. Sci. 60 427–431 doi: https://doi.org/10.2478/v10175-012-0054-1
[5] Mohammadi G, Shoushtari P, Molaee Ardekani B and Shamsollahi M B 2006 Person Identification by Using AR Model for EEG Signals, Proceeding World Acad. Sci. Eng. Technol. 11 281–285
[6] Poulos M, Rangoussi M, Alexandris N and Evangelou A 2002 Person identification from the EEG using nonlinear signal classification, Methods Inf. Med. 41 64–75
[7] Dawid A 2019 PSR-based research of feature extraction from one-second EEG signals: a neural network study, SN Appl. Sci. 1 1536, doi: https://doi.org/10.1007/s42452-019-1579-9
[8] Alakus T B, Gonen M and Turkoglu I Database for an emotion recognition system based on EEG signals and various computer games – GAMEEMO, Biomed. Signal Process. Control. 60 101951 doi: https://doi.org/10.1016/j.bspc.2020.101951
[9] Parafita R, Pires G, Nunes U and Castelo-Branco M 2013 A spacecraft game controlled with a brain-computer interface using SSVEP with phase tagging, IEEE 2nd Int. Conf. Serious Games Appl. Health SeGAH 1-6 doi: https://doi.org/10.1109/SeGAH.2013.6665309
[10] Martinez P, Bakardjian H and Cichocki A 2007 Fully Online Multicommand Brain-Computer Interface with Visual Neurofeedback Using SSVEP Paradigm, Comput. Intell. Neurosci. e94561 doi: https://doi.org/10.1155/2007/94561
[11] Chumerin N, Manyakov N V, van Vliet M, Robben A, Combaz A and Hulle M M V 2013 Steady-State Visual Evoked Potential-Based Computer Gaming on a Consumer-Grade EEG Device, IEEE Trans. Comput. Intell. AI Games 5 100–110 doi: https://doi.org/10.1109/ TCIAIG.2012.2225623
[12] van Vliet M, Robben A, Chumerin N, Manyakov N V, Combaz A and Hulle M MV 2012 Designing a brain-computer interface controlled video-game using consumer grade EEG hardware, ISSNIP Biosignals Biorobotics Conf. Biosignals Robot. Better Safer Living BRC 1–6 doi: https://doi.org/10.1109/BRC.2012.6222186
[13] Finke A, Lenhardt A and Ritter H 2009 The MindGame: A P300-based brain–computer interface game, Neural Netw. 22 1329–1333 doi: https://doi.org/10.1016/j.neunet.2009.07.003
[14] Cabañero L, Hervás R, González I, Fontecha J, Mondéjar T and Bravo J 2020 Characterisation of mobile-device tasks by their associated cognitive load through EEG data processing, Future Gener. Comput. Syst. 113 380–390 doi: https://doi.org/10.1016/j.future.2020.07.013
[15] Pong Game, (n.d.) (accessed December 24, 2020) doi: https://www.ponggame.org/
[16] Rostański M, Buchwald P, Mączka K, Kostka P and Nawrat Z 2015 The development of internetwork channel emulation platform for surgical robot telemanipulation control system (INSeRT), Fed. Conf. Comput. Sci. Inf. Syst. FedCSIS 1081–1085 doi: https://doi.org/10.15439/2015F239
[17] NeuroSky, EEG Sensors - EEG Headsets | NeuroSky, (n.d.) (accessed September 7, 2018) doi: http://neurosky.com/biosensors/eeg-sensor/biosensors/
[18] Oostenveld R and Praamstra P 2001 The five percent electrode system for high-resolution EEG and ERP measurements, Clin. Neurophysiol. 112 713–719 doi: https://doi.org/10.1016/S1388-2457(00)00527-7
[19] Duhamel P 1990 Algorithms meeting the lower bounds on the multiplicative complexity of length-2/sup n/ DFTs and their connection with practical algorithms, IEEE Trans. Acoust. Speech Signal Process. 38 1504–1511 doi: https://doi.org/10.1109/29.60070
[20] Jain A, Bansal R, Kumar A and Singh K 2015 A comparative study of visual and auditory reaction times on the basis of gender and physical activity levels of medical first year students, Int. J. Appl. Basic Med. Res. 5 124–127 doi: https://doi.org/10.4103/2229-516X.157168
[21] Thompson P D, Colebatch J G, Brown P, Rothwell J C, Day B L, Obeso J A and Marsden C D 1992 Voluntary stimulus-sensitive jerks and jumps mimicking myoclonus or pathological startle syndromes, Mov. Disord. Off. J. Mov. Disord. Soc. 7 257–262 doi: https://doi.org/10.1002/mds.870070312
[22] Math.NET Numerics, (n.d.) (accessed December 27, 2020) doi: https://numerics.mathdotnet.com/
[23] Cattani C and Rushchitsky J 2007 Wavelet and Wave Analysis as Applied to Materials with Micro or Nanostructure, WORLD SCIENTIFIC doi: https://doi.org/10.1142/6497
[24] Pang T 2006, An Introduction to Computational Physics 2 edition, Cambridge University Press, Cambridge; New York
[25] Atkinson K 1989, An Introduction to Numerical Analysis, 2nd edition, Wiley, New York

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