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Development of an Online Home Appliance Control System for the Elderly Based on SSVEP-Based Brain-Computer Interface: A Feasibility Study

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dc.contributor.authorPark, Seonghun-
dc.contributor.authorHa, Jisoo-
dc.contributor.authorCha, Ho-Seung-
dc.contributor.authorLee, Kyeong-Gu-
dc.contributor.authorIm, Chang-Hwan-
dc.date.accessioned2021-07-30T08:10:10Z-
dc.date.available2021-07-30T08:10:10Z-
dc.date.created2021-07-20-
dc.date.issued2021-02-22-
dc.identifier.issn0000-0000-
dc.identifier.urihttps://scholarworks.bwise.kr/hanyang/handle/2021.sw.hanyang/6209-
dc.description.abstractBrain-computer interface (BCI) is a technology that provides a direct communication channel between a user and the external environment using the user's brain activity. For the past decades, however, most BCI systems were tested with young people, even though the elderly are the primary target users of the BCI systems. Moreover, it has been frequently reported that a BCI system with the elderly showed significantly lower performance than that with young people. In the present study, to evaluate the feasibility of a steady-state visual evoked potential (SSVEP)-BCI-based home appliance control system, seventeen people over the age of 65 were recruited in an offline experiment in which their SSVEP responses were recorded while the visual stimuli were presented in an augmented reality (AR) environment via a see-through head-mounted display (HMD). The average classification accuracy of 94.1% and an information transfer rate (ITR) of 46.5 bits/min were achieved with respect to the window size of 3 s. Based on the results from the offline experiment, we tested the proposed online home appliance control system with a 65-year-aged female while the online experiment is still ongoing, increasing the number of the participants. © 2021 IEEE.-
dc.language영어-
dc.language.isoen-
dc.publisherInstitute of Electrical and Electronics Engineers Inc.-
dc.titleDevelopment of an Online Home Appliance Control System for the Elderly Based on SSVEP-Based Brain-Computer Interface: A Feasibility Study-
dc.typeConference-
dc.contributor.affiliatedAuthorIm, Chang-Hwan-
dc.identifier.scopusid2-s2.0-85104844999-
dc.identifier.bibliographicCitation9th IEEE International Winter Conference on Brain-Computer Interface, BCI 2021, pp.1 - 2-
dc.relation.isPartOf9th IEEE International Winter Conference on Brain-Computer Interface, BCI 2021-
dc.relation.isPartOf9th IEEE International Winter Conference on Brain-Computer Interface, BCI 2021-
dc.citation.title9th IEEE International Winter Conference on Brain-Computer Interface, BCI 2021-
dc.citation.startPage1-
dc.citation.endPage2-
dc.citation.conferencePlaceKO-
dc.citation.conferencePlaceGangwon-
dc.citation.conferenceDate2021-02-22-
dc.type.rimsCONF-
dc.description.journalClass1-
dc.identifier.urlhttps://ieeexplore.ieee.org/document/9385365-
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