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Recent Advances in Electrical & Electronic Engineering

Editor-in-Chief

ISSN (Print): 2352-0965
ISSN (Online): 2352-0973

Review Article

Brain-computer Interface Systems for Smart Homes - A Review Study

Author(s): Masoud Maleki*, Negin Manshouri and Temel Kayikcioglu

Volume 14, Issue 2, 2021

Published on: 27 July, 2020

Page: [144 - 155] Pages: 12

DOI: 10.2174/2352096513999200727175948

Price: $65

Abstract

Brain-computer Interface (BCI) systems, usually using signals taken from users' brain through electroencephalography (EEG), control various devices around and provide the user's command by interacting. Improving the quality of life of people with disabilities is the main goal of BCI systems. The importance of BCI-based smart home systems is further increasing as a smart home system directly affects the life of a disabled individual. On the other hand, few BCI systems can be run directly using smart home systems. The importance of the BCI-based smart home and the few existing systems require more work in this vital field. In addition, no reviews have described BCI systems in a smart home. In this study, we reviewed all the papers on BCI-based smart home systems published in the last 6 years. These studies investigated and evaluated BCI systems from nine different perspectives. In addition, all studies were examined in terms of signal processing methods. Finally, the problems and challenges of these systems were discussed and new solutions were proposed.

Keywords: Electroencephalography, brain-computer interface, BCI applications, smart home, BCI challenges, single-photon emission.

Graphical Abstract
[1]
J.B. van Erp, F. Lotte, and M. Tangermann, "Brain-computer Interfaces: Beyond medical applications", Comput. (Long. Beach. Calif), vol. 45, no. 4, pp. 26-34, 2012.
[http://dx.doi.org/10.1109/MC.2012.107]
[2]
S.N. Abdulkader, A. Atia, and M-S.M. Mostafa, "Brain computer interfacing: Applications and challenges, Egypt", Informatics J., vol. 16, no. 2, pp. 213-230, 2015.
[http://dx.doi.org/10.1016/j.eij.2015.06.002]
[3]
H.S. Anupama, N.K. Cauvery, and G.M. Lingaraju, "Brain computer interface and its types-A sStudy", Int. J. Adv. Eng. Technol., vol. 3, no. 2, pp. 739-745, 2019. Available at: http://www.e-ijaet.org/media/0001/78I8-IJAET0805886-BRAIN-COMPUTER-INTERFACE.pdf [Online].
[4]
G. Schalk, and E.C. Leuthardt, "Brain-computer interfaces using electrocorticographic signals", IEEE Rev. Biomed. Eng., vol. 4, pp. 140-154, 2011.
[http://dx.doi.org/10.1109/RBME.2011.2172408] [PMID: 22273796]
[5]
M. Wasim, M. Sajjad, F. Ramzan, U. Ghani, and W. Mahmood, "A review and classification of widely used offline brain datasets", Int. J. Adv. Comput. Sci. Appl., vol. 9, no. 2, 2018.
[http://dx.doi.org/10.14569/IJACSA.2018.090254]
[6]
S. Moghimi, A. Kushki, A.M. Guerguerian, and T. Chau, "A review of EEG-based brain-computer interfaces as access pathways for individuals with severe disabilities", Assist. Technol., vol. 25, no. 2, pp. 99-110, 2013.
[http://dx.doi.org/10.1080/10400435.2012.723298] [PMID: 23923692]
[7]
J. Mellinger, "An MEG-based brain-computer interface (BCI)", Neuroimage, vol. 36, no. 3, pp. 581-593, 2019. Available: http://www.ncbi.nlm.nih.gov/pubmed/17475511 [Online].
[8]
S.V. Raut, and D.M. Yadav, A Review on fMRI Signal Analysis and Brain Mapping Methodologies:, Springer: Singapore, 2017, pp. 309-320.
[http://dx.doi.org/10.1007/978-981-10-2471-9_30]
[9]
R. Deore, R.D. Chaudhari, and S.C. Mehrotra, "Comparative study of brain imaging techniques in BCI system", Int. J. Sci. Eng. Technol. Res., vol. 2, no. 9, pp. 2278-7798, 2013. [Online]. Available From: https://pdfs.semanticscholar.org/2ae1/9529ba279d03834da95
[10]
Y. Chellappa, N.N. Joshi, and V. Bharadwaj, "Driver fatigue detection system", In: IEEE International Conference on Signal and Image Processing (ICSIP), 2016, pp. 655-660.
[http://dx.doi.org/10.1109/SIPROCESS.2016.7888344]
[11]
N. Naseer, and K-S. Hong, "fNIRS-based brain-computer interfaces: a review", Front. Hum. Neurosci., vol. 9, p. 3, 2015.
[http://dx.doi.org/10.3389/fnhum.2015.00003] [PMID: 25674060]
[12]
M. Spezialetti, L. Cinque, J.M.R.S. Tavares, and G. Placidi, "Towards EEG-based BCI driven by emotions for addressing BCI-Illiteracy: A meta-analytic review", Behav. Inf. Technol., vol. 37, no. 8, pp. 855-871, 2018.
[http://dx.doi.org/10.1080/0144929X.2018.1485745]
[13]
I. Lazarou, S. Nikolopoulos, P.C. Petrantonakis, I. Kompatsiaris, and M. Tsolaki, "EEG-based brain-computer interfaces for communication and rehabilitation of people with motor impairment: A novel approach of the 21st century", Front. Hum. Neurosci., vol. 12, p. 14, 2018.
[http://dx.doi.org/10.3389/fnhum.2018.00014] [PMID: 29472849]
[14]
R. Palaniappan, "Electroencephalogram-based Brain–Computer Interface: An Introduction", In: Guide to Brain-Computer Music Interfacing:, Springer London: London, 2014, pp. 29-41.
[15]
J.R. Wolpaw, D.J. McFarland, and T.M. Vaughan, "Braincomputer interface research at the Wadsworth Center", IEEE Trans. Rehabil. Eng., vol. 8, no. 2, pp. 222-226, 2019. [Online]. Available From: http://www.ncbi.nlm.nih.gov/pubmed/10896194
[16]
P.R. Kennedy, R.A.E. Bakay, M.M. Moore, K. Adams, and J. Goldwaithe, "Direct control of a computer from the human central nervous system", IEEE Trans. Rehabil. Eng., vol. 8, no. 2, pp. 198-202, 2000.
[http://dx.doi.org/10.1109/86.847815] [PMID: 10896186]
[17]
A. Pinegger, H. Hiebel, S.C. Wriessnegger, and G.R. Müller-Putz, "Composing only by thought: Novel application of the P300 brain-computer interface", PLoS One, vol. 12, no. 9, 2017.e0181584
[http://dx.doi.org/10.1371/journal.pone.0181584] [PMID: 28877175]
[18]
S. Das, D. Tripathy, and J.L. Raheja, Real-time BCI system design to control arduino based speed controllable robot using EEG:, Springer, : Singapore, 2019.
[http://dx.doi.org/10.1007/978-981-13-3098-8]
[19]
R. Chai, S.H. Ling, G.P. Hunter, Y. Tran, and H.T. Nguyen, "Brain-computer interface classifier for wheelchair commands using neural network with fuzzy particle swarm optimization", IEEE J. Biomed. Health Inform., vol. 18, no. 5, pp. 1614-1624, 2014.
[http://dx.doi.org/10.1109/JBHI.2013.2295006] [PMID: 25192573]
[20]
J.J. Shih, D.J. Krusienski, and J.R. Wolpaw, "Brain-computer interfaces in medicine", Mayo Clin. Proc., vol. 87, no. 3, pp. 268-279, 2012.
[http://dx.doi.org/10.1016/j.mayocp.2011.12.008] [PMID: 22325364]
[21]
J.N. Mak, and J.R. Wolpaw, "Clinical applications of brain-computer interfaces: Current state and future prospects", IEEE Rev. Biomed. Eng., vol. 2, pp. 187-199, 2009.
[http://dx.doi.org/10.1109/RBME.2009.2035356] [PMID: 20442804]
[22]
D.P-O. Bos, "Human-computer interaction for BCI games: Usability and user experience", In: 2010 International Conference on Cyberworlds, 2010, pp. 277-281.
[http://dx.doi.org/10.1109/CW.2010.22]
[23]
D. Marshall, D. Coyle, S. Wilson, and M. Callaghan, "Games, gameplay, and BCI: The state of the art", IEEE Trans. Comput. Intell. AI games, vol. 5, no. 2, pp. 82-99, 2013.
[http://dx.doi.org/10.1109/TCIAIG.2013.2263555]
[24]
A. Nijholt, BCI for Games: A ‘State of the Art’ Survey:, Springer: Berlin, Heidelberg, 2008, pp. 225-228.
[25]
H. Gürkök, Towards multiplayer BCI games, 2010. [Online]. Available From: https://pdfs.semanticscholar.org/101f/c6db863605f9be9ed93a8d879 c122c15a6f3.pdf
[26]
M.A. Lopez-Gordo, R. Ron-Angevin, and F. Pelayo, Authentication of Brain-Computer Interface Users in Network Applications:, Springer: Cham, 2015, pp. 124-132.
[http://dx.doi.org/10.1007/978-3-319-19258-1_11]
[27]
A.A. Navarro, "Context-awareness as an enhancement of brain-computer interfaces", In: International Workshop on Ambient Assisted Living, 2011, pp. 216-223.
[http://dx.doi.org/10.1007/978-3-642-21303-8_30]
[28]
J.H. Yang, Z-H. Mao, L. Tijerina, T. Pilutti, J.F. Coughlin, and E. Feron, "Detection of driver fatigue caused by sleep deprivation", IEEE Trans. Syst. Man Cybern. A Syst. Hum., vol. 39, no. 4, pp. 694-705, 2009.
[http://dx.doi.org/10.1109/TSMCA.2009.2018634]
[29]
B. Kerous, F. Skola, and F. Liarokapis, "EEG-based BCI and video games: A progress report", Virtual Real. (Walth. Cross), vol. 22, no. 2, pp. 119-135, 2018.
[http://dx.doi.org/10.1007/s10055-017-0328-x]
[30]
A. Rezeika, M. Benda, P. Stawicki, F. Gembler, A. Saboor, and I. Volosyak, "Brain-computer interface spellers: A review", Brain Sci., vol. 8, no. 4, p. 57, 2018.
[http://dx.doi.org/10.3390/brainsci8040057] [PMID: 29601538]
[31]
F. Lotte, L. Bougrain, A. Cichocki, M. Clerc, M. Congedo, A. Rakotomamonjy, and F. Yger, "A review of classification algorithms for EEG-based brain-computer interfaces: A 10 year update", J. Neural Eng., vol. 15, no. 3, 2018. 031005
[http://dx.doi.org/10.1088/1741-2552/aab2f2] [PMID: 29488902]
[32]
R.A. Ramadan, and A.V. Vasilakos, "Brain computer interface: Control signals review", Neurocomputing, vol. 223, pp. 26-44, 2017.
[http://dx.doi.org/10.1016/j.neucom.2016.10.024]
[33]
D.J. McFarland, and D.J. Krusienski, "BCI Signal Processing: Feature Translation", In: Brain–Computer Interfaces Principles and Practice:, Oxford University Press, 2012, pp. 148-163.
[http://dx.doi.org/10.1093/acprof:oso/9780195388855.003.0008]
[34]
J.R. Wolpaw, N. Birbaumer, D.J. McFarland, G. Pfurtscheller, and T.M. Vaughan, "Brain-computer interfaces for communication and control", Clin. Neurophysiol., vol. 113, no. 6, pp. 767-791, 2019. [Online]. Available From: http://www.ncbi.nlm.nih.gov/pubmed/12048038
[35]
J.R. Wolpaw, H. Ramoser, D.J. McFarland, and G. Pfurtscheller, "EEG-based communication: improved accuracy by response verification", IEEE Trans. Rehabil. Eng., vol. 6, no. 3, pp. 326-333, 1998.
[http://dx.doi.org/10.1109/86.712231] [PMID: 9749910]
[36]
B. Shilpa, S.G. Hiremath, and G. Thippeswamy, "Neural network based characterization and reliable routing of data in wireless body sensor networks", Commun. Comput. Inf. Sci., vol. 801, pp. 239-247, 2018.
[http://dx.doi.org/10.1007/978-981-10-9059-2_22]
[37]
S.I. Dimitriadis, and A.D. Marimpis, "Enhancing performance and bit rates in a brain-computer interface system with phase-to-amplitude cross-frequency coupling: Evidences from traditional c-VEP, Fast c-VEP, and SSVEP Designs", Front. Neuroinform., vol. 12, p. p 19, 2018.
[http://dx.doi.org/10.3389/fninf.2018.00019] [PMID: 29867425]
[38]
"BCI: Machine Learning and Signal Processing for Brain-Computer Interfaces", MMSPG, Swiss National Science Foundation, 2020. Available at: https://www.epfl.ch/labs/mmspg/research/page-58351-en-html/page-58354-en-html/May 06, 2020
[39]
B. Wittevrongel, E.V. Wolputte, and M.M.V. Hulle, "Code-modulated visual evoked potentials using fast stimulus presentation and spatiotemporal beamformer decoding", Available From: https://kuleuven.app.box.com/v/CVEPMay 2020
[40]
"MAMEM SSVEP Database v1.0.0", Available at: https://physionet.org/content/mssvepdb/1.0.0/May 06, 2020
[41]
U. Masud, M.I. Baig, F. Akram, and T-S. Kim, "A P300 brain computer interface based intelligent home control system using a random forest classifier", In: IEEE Symposium Series on Computational Intelligence (SSCI), 2017, pp. 1-5.
[http://dx.doi.org/10.1109/SSCI.2017.8285449]
[42]
D. Achanccaray, C. Flores, C. Fonseca, and J. Andreu-Perez, "A P300-based brain computer interface for smart home interaction through an ANFIS ensemble", In: IEEE International Conference on Fuzzy Systems (FUZZ-IEEE), 2017, pp. 1-5.
[http://dx.doi.org/10.1109/FUZZ-IEEE.2017.8015770]
[43]
U. Hoffmann, J-M. Vesin, T. Ebrahimi, and K. Diserens, "An efficient P300-based brain-computer interface for disabled subjects", J. Neurosci. Methods, vol. 167, no. 1, pp. 115-125, 2008.
[http://dx.doi.org/10.1016/j.jneumeth.2007.03.005] [PMID: 17445904]
[44]
M.H.F. Zakaria, W. Mansor, and K.Y. Lee, "Time-frequency analysis of executed and imagined motor movement EEG signals for neuro-based home appliance system", TENCON 2017 - 2017 IEEE Region 10 Conference, pp. 1657-1660, 2017.
[http://dx.doi.org/10.1109/TENCON.2017.8228124]
[45]
S.F. Anindya, H.H. Rachmat, and E. Sutjiredjeki, "A prototype of SSVEP-based BCI for home appliances control", In: 2016 1st International Conference on Biomedical Engineering (IBIOMED), Yogyakarta, Indonesia, 2016.
[http://dx.doi.org/10.1109/IBIOMED.2016.7869810]
[46]
"AVI SSVEP Dataset – Adnan Vilic", Available From: https://www.setzner.com/avi-ssvep-dataset/May 06, 2020
[47]
H. Bakardjian, and T. Tanaka, A. C.-N. letters, and undefined 2010, “Optimization of SSVEP brain responses with application to eightcommand brain–computer interface”, Elsevier, 2020. [Online]. Available From: https://www.sciencedirect.com/science/article/pii/S0304394009015201?casa_token=8txJMMXTGRUAAAAA:j-IfdSVp_QaUz_aPJPlc10FGnYFaagD47m8BsuNIGcZF5Ac9eUZsH_-yOYQd3ouqXUrss9hr6Q
[48]
K. Belwafi, F. Ghaffari, R. Djemal, and O. Romain, "A hardware/software prototype of EEG-based BCI System for home device control", J. Signal Process. Syst., vol. 89, no. 2, pp. 263-279, 2017.
[http://dx.doi.org/10.1007/s11265-016-1192-8]
[49]
G. Dornhege, B. Blankertz, G. Curio, and K.R. Muller, "Boosting bit rates in noninvasive EEG single-trial classifications by feature combination and multiclass paradigms", IEEE Transact. Biomed. Eng., vol. 51, no. 6, 2004. [Online]. Available From: https://ieeexplore.ieee.org/abstract/document/1300794/?casa_token=4V5sxGCe0g4AAAAA:CJd4XKSunfib3waXJxnX9cRJhTUV2SH77CRGmE0U8S-wk63OPsES39suXGz7m2XG36LSVrpMVQ
[50]
M. Naeem, C. Brunner, R. Leeb, B. Graimann, and G. Pfurtscheller, "Seperability of four-class motor imagery data using independent components analysis", J. Neur. Eng., vol. 3, no. 3, 2006. [Online]. Available From: https://iopscience.iop.org/article/10.1088/1741-2560/3/3/003/meta
[51]
X. Zhang, L. Yao, S. Zhang, S. Kanhere, M. Sheng, and Y. Liu, "Internet of things meets brain–computer interface: A unified deep learning framework for enabling human-thing cognitive interactivity", IEEE Internet Things J., vol. 6, no. 2, pp. 2084-2092, 2019.
[http://dx.doi.org/10.1109/JIOT.2018.2877786]
[52]
J. Tabbal, K. Mechref, and W. El-Falou, "Brain Computer Interface for smart living environment", In: 2018 9th Cairo International Biomedical Engineering Conference (CIBEC), Cairo, Egypt, 2018.
[http://dx.doi.org/10.1109/CIBEC.2018.8641827]
[53]
A.I.N. Alshbatat, P.J. Vial, P. Premaratne, and L.C. Tran, "EEG-based brain-computer interface for automating home appliances", J. Comput., vol. 9, no. 9, pp. 2159-2166, 2014. [Online]. Available From: https://ro.uow.edu.au/cgi/viewcontent.cgi?referer=https://www.google.com/&
[54]
W. Alrajhi, D. Alaloola, and A. Albarqawi, "Smart home: Toward daily use of BCI-based systems", In: 2017 International Conference on Informatics, Health & Technology (ICIHT), 2017, pp. 1-5.
[http://dx.doi.org/10.1109/ICIHT.2017.7899002]
[55]
C. Brennan, Accessing Tele-Services Using a Hybrid BCI Approach., Springer: Cham, 2015, pp. 110-123.
[http://dx.doi.org/10.1007/978-3-319-19258-1_10]
[56]
E.A. Aydın, Ö.F. Bay, and İ. Güler, "Implementation of an embedded web server application for wireless control of brain computer interface based home environments", J. Med. Syst., vol. 40, no. 1, p. 27, 2016.
[http://dx.doi.org/10.1007/s10916-015-0386-0] [PMID: 26547847]
[57]
E.A. Aydin, O.F. Bay, and I. Guler, "P300-based asynchronous brain computer interface for environmental control system", IEEE J. Biomed. Health Inform., vol. 22, no. 3, pp. 653-663, 2018.
[http://dx.doi.org/10.1109/JBHI.2017.2690801] [PMID: 28391211]
[58]
R. Corralejo, L.F. Nicolás-Alonso, D. Álvarez, and R. Hornero, "A P300-based brain-computer interface aimed at operating electronic devices at home for severely disabled people", Med. Biol. Eng. Comput., vol. 52, no. 10, pp. 861-872, 2014.
[http://dx.doi.org/10.1007/s11517-014-1191-5] [PMID: 25163823]
[59]
C-C. Lo, S-H. Tsai, and B-S. Lin, "Novel non-contact control system of electric bed for medical healthcare", Med. Biol. Eng. Comput., vol. 55, no. 3, pp. 517-526, 2017.
[http://dx.doi.org/10.1007/s11517-016-1533-6] [PMID: 27306537]
[60]
F. Miralles, E. Vargiu, S. Dauwalder, M. Solà, G. Müller-Putz, S.C. Wriessnegger, A. Pinegger, A. Kübler, S. Halder, I. Käthner, S. Martin, J. Daly, E. Armstrong, C. Guger, C. Hintermüller, and H. Lowish, "Brain computer interface on track to home", In: Scientific-WorldJournal, vol. 2015. 2015.
[http://dx.doi.org/10.1155/2015/623896] [PMID: 26167530]
[61]
N. Kosmyna, F. Tarpin-Bernard, N. Bonnefond, and B. Rivet, "Feasibility of BCI control in a realistic smart home environment", Front. Hum. Neurosci., vol. 10, p. p 416, 2016.
[http://dx.doi.org/10.3389/fnhum.2016.00416] [PMID: 27616986]
[62]
C-T. Lin, B-S. Lin, F-C. Lin, and C-J. Chang, "Brain computer interface-based smart living environmental auto-adjustment control system in UPnP home networking", IEEE Syst. J., vol. 8, no. 2, pp. 363-370, 2014.
[http://dx.doi.org/10.1109/JSYST.2012.2192756]
[63]
B. Allison, The I of BCIs: Next Generation Interfaces for Brain-Computer Interface Systems That Adapt to Individual Users:, Springer: Berlin, Heidelberg, 2009, pp. 558-568.
[64]
M. Maleki, N. Manshouri, and T. Kayikcioglu, "Fast and accurate classifier-based brain-computer interface system using single channel EEG data", In: 2018 26th Signal Processing and Communications Applications Conference (SIU), Izmir, Turkey, 2018.
[http://dx.doi.org/10.1109/SIU.2018.8404376]
[65]
A. Bertomeu-Motos, S. Ezquerro, J.A. Barios, L.D. Lledó, S. Domingo, M. Nann, S. Martin, S.R. Soekadar, and N. Garcia-Aracil, "User activity recognition system to improve the performance of environmental control interfaces: A pilot study with patients", J. Neuroeng. Rehabil., vol. 16, no. 1, p. 10, 2019.
[http://dx.doi.org/10.1186/s12984-018-0477-5] [PMID: 30646915]

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