Classification of Hand Movement in EEG using ERD/ERS and Multilayer Perceptron
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F49777513%3A23520%2F20%3A43960748" target="_blank" >RIV/49777513:23520/20:43960748 - isvavai.cz</a>
Result on the web
<a href="https://www.scitepress.org/Link.aspx?doi=10.5220/0009167007130717" target="_blank" >https://www.scitepress.org/Link.aspx?doi=10.5220/0009167007130717</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.5220/0009167007130717" target="_blank" >10.5220/0009167007130717</a>
Alternative languages
Result language
angličtina
Original language name
Classification of Hand Movement in EEG using ERD/ERS and Multilayer Perceptron
Original language description
Continuous EEG activity in the measured subjects includes different patterns depending on what activity the subject performed. ERD and ERS are examples of such patterns related to movement, for example of a hand, finger or foot. This article deals with the detection of motion based on the ERD/ERS patterns. By linking ERD/ERS, feature vectors which are later classified by neural network are created. The resulting neural network consists of one input and one output layer and two hidden layers. The first hidden layer contains 3,000 neurons and the second one 1,500 neurons. A training set of feature vectors is used for the training of this neural network and the back-propagation algorithm is used for the subsequent adjustment of the weights. With this setting and training, the neural network is able to classify motion in an EEG record with an average accuracy of 79.92%.
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
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
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
BIOSTEC 2020
ISBN
978-989-758-398-8
ISSN
2184-4305
e-ISSN
—
Number of pages
5
Pages from-to
713-717
Publisher name
SciTiPress
Place of publication
Setúbal
Event location
Valletta Malta
Event date
Feb 24, 2020
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
000571479400081