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@inproceedings{Teversham:2022:10.1109/EMBC48229.2022.9871064,
author = {Teversham, J and Wong, SS and Hsieh, B and Rapeaux, A and Troiani, F and Savolainen, O and Zhang, Z and Maslik, M and Constandinou, TG},
doi = {10.1109/EMBC48229.2022.9871064},
pages = {208--213},
publisher = {IEEE},
title = {Development of an ultra low-cost SSVEP-based BCI device for real-time on-device decoding},
url = {http://dx.doi.org/10.1109/EMBC48229.2022.9871064},
year = {2022}
}

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TY  - CPAPER
AB  - This study details the development of a novel, approx. £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.
AU  - Teversham,J
AU  - Wong,SS
AU  - Hsieh,B
AU  - Rapeaux,A
AU  - Troiani,F
AU  - Savolainen,O
AU  - Zhang,Z
AU  - Maslik,M
AU  - Constandinou,TG
DO  - 10.1109/EMBC48229.2022.9871064
EP  - 213
PB  - IEEE
PY  - 2022///
SN  - 2694-0604
SP  - 208
TI  - Development of an ultra low-cost SSVEP-based BCI device for real-time on-device decoding
UR  - http://dx.doi.org/10.1109/EMBC48229.2022.9871064
UR  - https://www.ncbi.nlm.nih.gov/pubmed/36086083
UR  - https://ieeexplore.ieee.org/document/9871064
ER  -

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