Detection of finger flexions based on decision tree
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27240%2F18%3A10241738" target="_blank" >RIV/61989100:27240/18:10241738 - isvavai.cz</a>
Result on the web
<a href="https://link.springer.com/chapter/10.1007%2F978-3-319-60834-1_7" target="_blank" >https://link.springer.com/chapter/10.1007%2F978-3-319-60834-1_7</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1007/978-3-319-60834-1_7" target="_blank" >10.1007/978-3-319-60834-1_7</a>
Alternative languages
Result language
angličtina
Original language name
Detection of finger flexions based on decision tree
Original language description
Analysis and classification of Electroencephalography (EEG) Data are still a big challenge. This kind if data is very sensitive and complex. EEG data plays a big role not only in medicine. The EEG data can be used as control commands of an external device, e.g. wheelchair, prosthesis, and many others. To do this, we need to establish models which can correctly classify captured EEG data. This paper presents a model based on Butterworth IIR filter, Fast Fourier transform (FFT), Singular Value Decomposition (SVD) and Decision Tree (DT) as a classifier. It can classify finger flexions with accuracy up to 92.241% for three fingers. (C) 2018, Springer International Publishing AG.
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
<a href="/en/project/GJ16-25694Y" target="_blank" >GJ16-25694Y: Multi-paradigm data mining algorithms based on information retrieval, fuzzy, and bio-inspired methods</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)
Others
Publication year
2018
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
Advances in intelligent systems and computing. Volume 565
ISBN
978-3-319-60833-4
ISSN
2194-5357
e-ISSN
neuvedeno
Number of pages
11
Pages from-to
57-67
Publisher name
Springer
Place of publication
Berlin
Event location
Marrákeš
Event date
Nov 21, 2016
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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