Real Time Emg Detection In Therapeutic Game

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but.event.date23.04.2020cs
but.event.titleStudent EEICT 2020cs
dc.contributor.authorVeselá, Cindy
dc.date.accessioned2021-07-15T13:12:38Z
dc.date.available2021-07-15T13:12:38Z
dc.date.issued2020cs
dc.description.abstractThis article focuses on real-time detection of activity in electromyographical signal. The study is based on controlling the therapeutic game through the muscle activity, called myofeedback. Many different algorithms can be used to detect EMG signal. Nowadays there is rapid development of artificial intelligence not only in biomedical engineering. In this paper there is implemented convolutional neural network for signal segmentation with accuracy 97,13%.en
dc.formattextcs
dc.format.extent68-71cs
dc.format.mimetypeapplication/pdfen
dc.identifier.citationProceedings II of the 26st Conference STUDENT EEICT 2020: Selected Papers. s. 68-71. ISBN 978-80-214-5868-0cs
dc.identifier.isbn978-80-214-5868-0
dc.identifier.urihttp://hdl.handle.net/11012/200622
dc.language.isoencs
dc.publisherVysoké učení technické v Brně, Fakulta elektrotechniky a komunikačních technologiícs
dc.relation.ispartofProceedings II of the 26st Conference STUDENT EEICT 2020: Selected papersen
dc.relation.urihttps://conf.feec.vutbr.cz/eeict/EEICT2020cs
dc.rights© Vysoké učení technické v Brně, Fakulta elektrotechniky a komunikačních technologiícs
dc.rights.accessopenAccessen
dc.subjectEMGen
dc.subjectUNETen
dc.subjectgameen
dc.subjectsignalen
dc.subjectbiofeedbacken
dc.titleReal Time Emg Detection In Therapeutic Gameen
dc.type.driverconferenceObjecten
dc.type.statusPeer-revieweden
dc.type.versionpublishedVersionen
eprints.affiliatedInstitution.departmentFakulta elektrotechniky a komunikačních technologiícs
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