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Using High-Frequency Electroencephalogram in Visual and Auditory-Based Brain-Computer Interface Designs

Gupta, Cota Navin, Palaniappan, Ramaswamy (2012) Using High-Frequency Electroencephalogram in Visual and Auditory-Based Brain-Computer Interface Designs. EContact!, 14 (2). (The full text of this publication is not currently available from this repository. You may be able to access a copy if URLs are provided)

The full text of this publication is not currently available from this repository. You may be able to access a copy if URLs are provided. (Contact us about this Publication)
Official URL
https://econtact.ca/14_2/gupta-palaniappan_interfa...

Abstract

Evoked potentials obtained from brain’s electrical activity (i.e. electroencephalogram [EEG]) in response to both visual and auditory oddball paradigms have been used in brain-computer interface (BCI) designs, as a means of achieving external control directly from the brain. This is obviously useful for the severely disabled, but it can also be used for creative applications in music performance. We present here a novel approach that combines conventionally used low frequency information with higher frequency in gamma band to enhance the performance of such BCI designs. EEG data were obtained from three and two subjects for the visual and auditory paradigms, respectively. In the visual paradigm, the subjects perceived common pictures like TV, radio, lamp etc., while for the auditory paradigm, the subjects listened to simple computer-generated sounds like “ding”, “exclamation”, “chimes” etc. Recognition of target picture or sound focused by the subject using the EEG data allows a control mechanism to be designed, which can then be used to control the movement of a wheelchair, to trigger a sound sample, or to create harmonic variations over a synthesised piece of music. The results confirm that using the higher frequency gamma band, which has been mostly overlooked in BCI studies, along with low frequency in the P300 temporal region, give better classification accuracies for both paradigms. This study offers motivation warranting further exploration on the link between low and high frequency of evoked potentials from EEG for use in visual and auditory based BCI designs.

Item Type: Article
Additional information: Unmapped bibliographic data: JO - EContact!—Biotechnological Performance Practice [Field not mapped to EPrints]
Divisions: Faculties > Sciences > School of Computing
Faculties > Sciences > School of Computing > Data Science
Depositing User: Palaniappan Ramaswamy
Date Deposited: 14 Dec 2018 17:13 UTC
Last Modified: 30 May 2019 08:34 UTC
Resource URI: https://kar.kent.ac.uk/id/eprint/71047 (The current URI for this page, for reference purposes)
Palaniappan, Ramaswamy: https://orcid.org/0000-0001-5296-8396
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