Towards Serious Games for Improved BCI

Lance, B; Touryan, J; Wang, YK; Lu, SW; Chuang, CH; Khooshabeh, P; Sajda, P; Marathe, A; Jung, TP; Lin, CT; McDowell, K

Towards Serious Games for Improved BCI

Lance, B Touryan, J Wang, YK

Lu, SW Chuang, CH

Khooshabeh, P Sajda, P Marathe, A Jung, TP Lin, CT

McDowell, K

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Publisher:: Springer
Publication Type:: Chapter
Citation:: Handbook of Digital Games and Entertainment Technologies, 2015, pp. 1 - 28
Issue Date:: 2015-09-09

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Field	Value	Language
dc.contributor.author	Lance, B	en_US
dc.contributor.author	Touryan, J	en_US
dc.contributor.author	Wang, YK https://orcid.org/0000-0001-8390-2664	en_US
dc.contributor.author	Lu, SW	en_US
dc.contributor.author	Chuang, CH https://orcid.org/0000-0002-5043-8380	en_US
dc.contributor.author	Khooshabeh, P	en_US
dc.contributor.author	Sajda, P	en_US
dc.contributor.author	Marathe, A	en_US
dc.contributor.author	Jung, TP	en_US
dc.contributor.author	Lin, CT https://orcid.org/0000-0001-8371-8197	en_US
dc.contributor.author	McDowell, K	en_US
dc.contributor.editor	Nakatsu, R	en_US
dc.contributor.editor	Rauterberg, M	en_US
dc.contributor.editor	Ciancarini, P	en_US
dc.date.issued	2015-09-09	en_US
dc.identifier.citation	Handbook of Digital Games and Entertainment Technologies, 2015, pp. 1 - 28	en_US
dc.identifier.isbn	978-981-4560-52-8	en_US
dc.identifier.uri	http://hdl.handle.net/10453/88636
dc.description.abstract	Brain-computer interface (BCI) technologies, or technologies that use online brain signal processing, have a great promise to improve human interactions with computers, their environment, and even other humans. Despite this promise, there are no current serious BCI technologies in widespread use, due to the lack of robustness in BCI technologies. The key neural aspect of this lack of robustness is human variability, which has two main components: (1) individual differences in neural signals and (2) intraindividual variability over time. In order to develop widespread BCI technologies, it will be necessary to address this lack of robustness. However, it is currently unknown how neural variability affects BCI performance. To accomplish these goals, it is essential to obtain data from large numbers of individuals using BCI technologies over considerable lengths of time. One promising method for this is through the use of BCI technologies embedded into games with a purpose (GWAP). GWAP are a game-based form of crowdsourcing which players choose to play for enjoyment and during which the player performs key tasks which cannot be automated but that are required to solve research questions. By embedding BCI paradigms in GWAP and recording neural and behavioral data, it should be possible to much more clearly understand the differences in neural signals between individuals and across different time scales, enabling the development of novel and increasingly robust adaptive BCI algorithms.	en_US
dc.publisher	Springer	en_US
dc.relation.ispartof	Handbook of Digital Games and Entertainment Technologies	en_US
dc.relation.isbasedon	10.1007/978-981-4560-52-8_4-1	en_US
dc.title	Towards Serious Games for Improved BCI	en_US
dc.type	Chapter
utslib.location	Germany	en_US
utslib.for	0803 Computer Software	en_US
pubs.embargo.period	Not known	en_US
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology/School of Computer Science
pubs.organisational-group	/University of Technology Sydney/Strength - CAI - Centre for Artificial Intelligence
utslib.copyright.status	closed_access
pubs.consider-herdc	true	en_US
pubs.place-of-publication	Germany	en_US
pubs.publication-status	Published	en_US

Abstract:

Brain-computer interface (BCI) technologies, or technologies that use online brain signal processing, have a great promise to improve human interactions with computers, their environment, and even other humans. Despite this promise, there are no current serious BCI technologies in widespread use, due to the lack of robustness in BCI technologies. The key neural aspect of this lack of robustness is human variability, which has two main components: (1) individual differences in neural signals and (2) intraindividual variability over time. In order to develop widespread BCI technologies, it will be necessary to address this lack of robustness. However, it is currently unknown how neural variability affects BCI performance. To accomplish these goals, it is essential to obtain data from large numbers of individuals using BCI technologies over considerable lengths of time. One promising method for this is through the use of BCI technologies embedded into games with a purpose (GWAP). GWAP are a game-based form of crowdsourcing which players choose to play for enjoyment and during which the player performs key tasks which cannot be automated but that are required to solve research questions. By embedding BCI paradigms in GWAP and recording neural and behavioral data, it should be possible to much more clearly understand the differences in neural signals between individuals and across different time scales, enabling the development of novel and increasingly robust adaptive BCI algorithms.

Please use this identifier to cite or link to this item:

http://hdl.handle.net/10453/88636