REAL TIME EMG DETECTION IN THERAPEUTIC GAME
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26220%2F20%3APU143931" target="_blank" >RIV/00216305:26220/20:PU143931 - isvavai.cz</a>
Result on the web
<a href="https://www.eeict.cz/eeict_download/archiv/sborniky/EEICT_2020_sbornik_2.pdf" target="_blank" >https://www.eeict.cz/eeict_download/archiv/sborniky/EEICT_2020_sbornik_2.pdf</a>
DOI - Digital Object Identifier
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Alternative languages
Result language
angličtina
Original language name
REAL TIME EMG DETECTION IN THERAPEUTIC GAME
Original language description
This 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%.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
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OECD FORD branch
20601 - Medical engineering
Result continuities
Project
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Continuities
S - Specificky vyzkum na vysokych skolach
Others
Publication year
2020
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
Proceedings II of the 26th Conference STUDENT EEICT 2020
ISBN
978-80-214-5868-0
ISSN
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e-ISSN
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Number of pages
4
Pages from-to
68-71
Publisher name
Brno University of Technology, Faculty of Electrical Engineering and
Place of publication
Brno, Czech Republic
Event location
BRNO
Event date
Apr 23, 2020
Type of event by nationality
CST - Celostátní akce
UT code for WoS article
000598376500018