Towards Accurate Browser-based SSVEP Stimuli Generation

Alison Camilleri, Chris Porter, Tracey Camilleri

Abstract

Breakthroughs in Brain-Computer Interfacing (BCI) have positively impacted the lives of individuals who suffer from highly-restrictive physical disabilities. BCIs based on Steady State Visually Evoked Potentials (SSVEPs) rely on a neuronal response which takes place in the brain’s visual cortex whenever a person focuses visual attention onto a flickering stimulus. Specialized hardware and software tools exist for stimuli generation, however little to no empirical evidence exists on the applicability of standard web technologies for producing accurate and stable stimuli, for use in BCI applications. With the aim of informing efforts for the development of lightweight, portable and low-cost browser-based BCIs, this paper produces initial evidence on the performance attained by widely-adopted web technologies, namely CSS and WebGL. Results demonstrate that for the square wave approximation method, CSS and WebGL are able to effectively render stable and accurate stimuli on both Google Chrome and Mozilla Firefox.

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