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On the stimulus duty cycle in steady state visual evoked potential

Wilson, John J., Palaniappan, Ramaswamy (2014) On the stimulus duty cycle in steady state visual evoked potential. International Journal of Knowledge-Based and Intelligent Engineering Systems, 18 (2). pp. 73-79. ISSN 1327-2314. (doi:10.3233/KES-140287)

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http://dx.doi.org/10.3233/KES-140287

Abstract

Brain-computer interfaces (BCI) are useful devices that allow direct control of external devices using thoughts, i.e. brain's electrical activity. There are several BCI paradigms, of which steady state visual evoked potential (SSVEP) is the most commonly used due to its quick response and accuracy. SSVEP stimuli are typically generated by varying the luminance of a target for a set number of frames or display events. Conventionally, SSVEP based BCI paradigms use magnitude (amplitude) information from frequency domain but recently, SSVEP based BCI paradigms have begun to utilize phase information to discriminate between similar frequency targets. This paper will demonstrate that using a single frame to modulate a stimulus may lead to a bi-modal distribution of SSVEP as a consequence of a user attending both transition edges. This incoherence, while of less importance in traditional magnitude domain SSVEP BCIs becomes critical when phase is taken into account. An alternative modulation technique incorporating a 50% duty cycle is also a popular method for generating SSVEP stimuli but has a unimodal distribution due to user's forced attention to a single transition edge. This paper demonstrates that utilizing the second method results in significantly enhanced performance in information transfer rate in a phase discrimination SSVEP based BCI.

Item Type: Article
DOI/Identification number: 10.3233/KES-140287
Uncontrolled keywords: BCI; duty cycle; SSVEP; phase information
Subjects: Q Science > QA Mathematics (inc Computing science) > QA 76 Software, computer programming,
Q Science > QA Mathematics (inc Computing science) > QA 76 Software, computer programming, > QA76.76.E95 Expert Systems (Intelligent Knowledge Based Systems)
Divisions: Faculties > Sciences > School of Computing > Data Science
Depositing User: Palaniappan Ramaswamy
Date Deposited: 03 Sep 2015 17:06 UTC
Last Modified: 29 May 2019 15:59 UTC
Resource URI: https://kar.kent.ac.uk/id/eprint/50388 (The current URI for this page, for reference purposes)
Palaniappan, Ramaswamy: https://orcid.org/0000-0001-5296-8396
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