DC Field | Value | Language |
---|---|---|
dc.contributor.author | Lee, Kwang-Ryeol | ko |
dc.contributor.author | Chang, Won-Du | ko |
dc.contributor.author | Kim, Sungkean | ko |
dc.contributor.author | Im, Chang-Hwan | ko |
dc.date.accessioned | 2017-03-30T09:21:39Z | - |
dc.date.available | 2017-03-30T09:21:39Z | - |
dc.date.created | 2017-03-29 | - |
dc.date.created | 2017-03-29 | - |
dc.date.issued | 2017-01 | - |
dc.identifier.citation | IEEE TRANSACTIONS ON NEURAL SYSTEMS AND REHABILITATION ENGINEERING, v.25, no.1, pp.37 - 48 | - |
dc.identifier.issn | 1534-4320 | - |
dc.identifier.uri | http://hdl.handle.net/10203/222771 | - |
dc.description.abstract | Eye movements can be used as alternative inputs for human-computer interface (HCI) systems such as virtual or augmented reality systems as well as new communication ways for patients with locked-in syndrome. In this study, we developed a real-time electrooculogram (EOG)-based eye-writing recognition system, with which users can write predefined symbolic patterns with their volitional eye movements. For the "eye-writing" recognition, the proposed system first reconstructs the eye-written traces from EOG waveforms in real-time; then, the system recognizes the intended symbolic inputs with a reliable recognition rate by matching the input traces with the trained eye-written traces of diverse input patterns. Experiments with 20 participants showed an average recognition rate of 87.38% (F1 score) for 29 different symbolic patterns (26 lower case alphabet characters and three functional input patterns representing Space, Backspace, and Enter keys), demonstrating the promise of our EOG-based eye-writing recognition system in practical scenarios. | - |
dc.language | English | - |
dc.publisher | IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC | - |
dc.subject | HUMAN-COMPUTER INTERFACE | - |
dc.subject | EOG | - |
dc.subject | CLASSIFICATION | - |
dc.title | Real-Time "Eye-Writing" Recognition Using Electrooculogram | - |
dc.type | Article | - |
dc.identifier.wosid | 000396396900005 | - |
dc.identifier.scopusid | 2-s2.0-85011675588 | - |
dc.type.rims | ART | - |
dc.citation.volume | 25 | - |
dc.citation.issue | 1 | - |
dc.citation.beginningpage | 37 | - |
dc.citation.endingpage | 48 | - |
dc.citation.publicationname | IEEE TRANSACTIONS ON NEURAL SYSTEMS AND REHABILITATION ENGINEERING | - |
dc.identifier.doi | 10.1109/TNSRE.2016.2542524 | - |
dc.contributor.localauthor | Lee, Kwang-Ryeol | - |
dc.contributor.nonIdAuthor | Chang, Won-Du | - |
dc.contributor.nonIdAuthor | Kim, Sungkean | - |
dc.contributor.nonIdAuthor | Im, Chang-Hwan | - |
dc.description.isOpenAccess | N | - |
dc.type.journalArticle | Article | - |
dc.subject.keywordAuthor | Assistive devices | - |
dc.subject.keywordAuthor | biomedical signal processing | - |
dc.subject.keywordAuthor | electrooculography (EOG) | - |
dc.subject.keywordAuthor | human-computer interaction (HCI) | - |
dc.subject.keywordAuthor | pattern analysis | - |
dc.subject.keywordAuthor | rehabilitation | - |
dc.subject.keywordPlus | HUMAN-COMPUTER INTERFACE | - |
dc.subject.keywordPlus | EOG | - |
dc.subject.keywordPlus | CLASSIFICATION | - |
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