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Reference TypeConference Proceedings
Sitesibgrapi.sid.inpe.br
Identifier8JMKD3MGPEW34M/43BCTKE
Repositorysid.inpe.br/sibgrapi/2020/09.29.23.53
Last Update2020:10.01.15.10.24 danson.garcia@mail.utoronto.ca
Metadatasid.inpe.br/sibgrapi/2020/09.29.23.53.31
Metadata Last Update2020:10.28.20.46.56 administrator
Citation KeyGarciaZheTaoLiuMan:2020:CaPiHu
TitleCapturing Pictures from Human Vision Using SSVEP and Lock-in Amplifier
FormatOn-line
Year2020
DateNov. 7-10, 2020
Access Date2020, Dec. 04
Number of Files1
Size4548 KiB
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Author1 Garcia, Danson Evan
2 Zheng, Kai Wen
3 Tao, Yi
4 Liu, Yi
5 Mann, Steve
Affiliation1 University of Toronto
2 University of Toronto
3 University of Toronto
4 University of Toronto
5 University of Toronto
EditorMusse, Soraia Raupp
Cesar Junior, Roberto Marcondes
Pelechano, Nuria
Wang, Zhangyang (Atlas)
e-Mail Addressdanson.garcia@mail.utoronto.ca
Conference NameConference on Graphics, Patterns and Images, 33 (SIBGRAPI)
Conference LocationVirtual
Book TitleProceedings
PublisherIEEE Computer Society
Publisher CityLos Alamitos
History2020-10-01 15:10:24 :: danson.garcia@mail.utoronto.ca -> administrator :: 2020
2020-10-28 20:46:56 :: administrator -> danson.garcia@mail.utoronto.ca :: 2020
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Is the master or a copy?is the master
Document Stagecompleted
Document Stagenot transferred
Transferable1
Content TypeExternal Contribution
Tertiary TypeFull Paper
KeywordsSignal processing, visual field reconstruction, brain-computer interfaces (BCI), steady-state visually evoked potential (SSVEP), lock-in amplifier, pattern recognition.
AbstractWe 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.
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Languageen
Target FilePID6607063.pdf
e-Mail (login)danson.garcia@mail.utoronto.ca
User Groupdanson.garcia@mail.utoronto.ca
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Mirror Repositorysid.inpe.br/banon/2001/03.30.15.38.24
Next Higher Units8JMKD3MGPEW34M/43G4L9S
Host Collectionsid.inpe.br/banon/2001/03.30.15.38
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