%0 Conference Proceedings
%4 sid.inpe.br/sibgrapi/2020/09.29.23.53
%2 sid.inpe.br/sibgrapi/2020/09.29.23.53.31
%@doi 10.1109/SIBGRAPI51738.2020.00031
%T Capturing Pictures from Human Vision Using SSVEP and Lock-in Amplifier
%D 2020
%A Garcia, Danson Evan,
%A Zheng, Kai Wen,
%A Tao, Yi,
%A Liu, Yi,
%A Mann, Steve,
%@affiliation University of Toronto
%@affiliation University of Toronto
%@affiliation University of Toronto
%@affiliation University of Toronto
%@affiliation University of Toronto
%E Musse, Soraia Raupp,
%E Cesar Junior, Roberto Marcondes,
%E Pelechano, Nuria,
%E Wang, Zhangyang (Atlas),
%B Conference on Graphics, Patterns and Images, 33 (SIBGRAPI)
%C Porto de Galinhas (virtual)
%8 7-10 Nov. 2020
%I IEEE Computer Society
%J Los Alamitos
%S Proceedings
%K Signal processing, visual field reconstruction, brain-computer interfaces (BCI), steady-state visually evoked potential (SSVEP), lock-in amplifier, pattern recognition.
%X We present a novel way of using one's eye to capture an image of what it "sees" through the use of steady-state visually-evoked potentials (SSVEP). Existing methods leveraging response patterns for SSVEP visual image reconstruction show lossy reconstruction and have a lengthy scanning process. With our signal acquisition procedure, data collection requirements are significantly decreased while still improving the signal clarity. The data for image reconstruction was collected from the Oz positioned electrode using a low-cost, wearable electroencephalography (EEG) device. For image reconstruction, software-defined lock-in amplifier (LIA) and discrete Fourier transform (DFT) signal processing methods are analyzed.
%@language en
%3 PID6607063.pdf