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Anger-based BCI using fNIRS neurofeedback

Anger-based BCI using fNIRS neurofeedback

Aranyi, Gabor, Charles, Fred and Cavazza, Marc ORCID: 0000-0001-6113-9696 (2015) Anger-based BCI using fNIRS neurofeedback. In: Proceedings of the 28th Annual ACM Symposium on User Interface Software & Technology - UIST '15. ACM, New York, pp. 511-521. ISBN 9781450337793 (doi:https://doi.org/10.1145/2807442.2807447)

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Abstract

Functional near-infrared spectroscopy (fNIRS) holds increasing potential for Brain-Computer Interfaces (BCI) due to its portability, ease of application, robustness to movement artifacts, and relatively low cost. The use of fNIRS to support the development of affective BCI has received comparatively less attention, despite the role played by the prefrontal cortex in affective control, and the appropriateness of fNIRS to measure prefrontal activity. We present an active, fNIRS-based neurofeedback (NF) interface, which uses differential changes in oxygenation between the left and right sides of the dorsolateral prefrontal cortex to operationalize BCI input. The system is activated by users generating a state of anger, which has been previously linked to increased left prefrontal asymmetry. We have incorporated this NF interface into an experimental platform adapted from a virtual 3D narrative, in which users can express anger at a virtual character perceived as evil, causing the character to disappear progressively. Eleven subjects used the system and were able to successfully perform NF despite minimal training. Extensive analysis confirms that success was associated with the intent to express anger. This has positive implications for the design of affective BCI based on prefrontal asymmetry.

Item Type: Conference Proceedings
Title of Proceedings: Proceedings of the 28th Annual ACM Symposium on User Interface Software & Technology - UIST '15
Additional Information: The symposium was held at Charlotte, NC, USA from 11-15 November, 2015
Uncontrolled Keywords: Brain-Computer Interface; Approach Motivation; Neurofeedback; Functional Near-Infrared Spectroscopy
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Faculty / Department / Research Group: Faculty of Architecture, Computing & Humanities
Faculty of Architecture, Computing & Humanities > Department of Computing & Information Systems
Last Modified: 20 Jun 2019 15:36
Selected for GREAT 2016: None
Selected for GREAT 2017: None
Selected for GREAT 2018: None
Selected for GREAT 2019: None
URI: http://gala.gre.ac.uk/id/eprint/19796

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