Development of an Ultra Low-Cost SSVEP-based BCI Device for Real-Time On-Device Decoding
J. Teversham, S. Wong, B. Hsieh, A. Rapeaux, F. Troiani, O. Savolainen, Z. Zhang, M. Maslik, T. Constandinou
Abstract
This study details the development of a novel, approx. {pound}20 electroencephalogram (EEG)-based brain-computer interface (BCI) intended to offer a financially and operationally accessible device that can be deployed on a mass scale to facilitate education and public engagement in the domain of EEG sensing and neurotechnologies. Real-time decoding of steady-state visual evoked potentials (SSVEPs) is achieved using variations of the widely-used canonical correlation analysis (CCA) algorithm: multi-set CCA and generalised CCA. All BCI functionality is executed on board an inexpensive ESP32 microcontroller. SSVEP decoding accuracy of 95.56 {+/-} 3.74% with an ITR of 102 bits/min was achieved with modest calibration.
02 /Specification & Classification
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