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Towards a reliable PWM based LED visual stimulus for improved SSVEP response with minimal visual fatigue

Mouli, Surej, Palaniappan, Ramaswamy (2017) Towards a reliable PWM based LED visual stimulus for improved SSVEP response with minimal visual fatigue. Journal of Engineering, . ISSN 2051-3305. E-ISSN 2051-3305. (doi:10.1049/joe.2016.0314) (KAR id:59671)

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Steady state visual evoked response (SSVEP) is widely used in visual based diagnosis and applications such as brain-computer interfacing due to its high information transfer rate and the capability to activate commands through simple gaze control. However, one major impediment in using flashing visual stimulus to obtain SSVEP is eye fatigue that prevents continued long term use preventing practical deployment. This combined with the difficulty in establishing precise pulse width modulation (PWM) that results in poorer accuracy warrants the development of appropriate approach to solve these issues. Various studies have suggested the usage of high frequencies of visual stimulus to reduce the visual fatigue for the user but this results in poor response performance. Here, we study the use of extremely high duty cycles in the stimulus in the hope of solving these constraints. Electroencephalogram (EEG) data was recorded with PWM duty cycles of 50-95% generated by a precise custom made LED hardware and tested ten subjects responded that increasing duty cycles had less visual strain for all the frequency values and the SSVEP exhibited a subject independent peak response for duty cycle of 85%. This could pave the way for increased usage of SSVEP for practical applications.

Item Type: Article
DOI/Identification number: 10.1049/joe.2016.0314
Uncontrolled keywords: Brain–computer interface, duty cycle, LED visual stimulus, steady-state visual evoked potential, visual fatigue
Subjects: Q Science > QA Mathematics (inc Computing science) > QA 75 Electronic computers. Computer science
R Medicine > RZ Other systems of medicine
T Technology > TK Electrical engineering. Electronics. Nuclear engineering > TK7800 Electronics
Divisions: Faculties > Sciences > School of Computing > Data Science
Depositing User: Palaniappan Ramaswamy
Date Deposited: 13 Dec 2016 15:03 UTC
Last Modified: 09 Jul 2019 11:18 UTC
Resource URI: (The current URI for this page, for reference purposes)
Palaniappan, Ramaswamy:
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