Supervised Learning Used in Automatic EEG Graphoelements Classification
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21460%2F15%3A00235196" target="_blank" >RIV/68407700:21460/15:00235196 - isvavai.cz</a>
Alternative codes found
RIV/00064211:_____/15:N0000004
Result on the web
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DOI - Digital Object Identifier
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Alternative languages
Result language
angličtina
Original language name
Supervised Learning Used in Automatic EEG Graphoelements Classification
Original language description
The comparison of supervised (k-nearest neighbors) and unsupervised (k-means) methods for automatic classification of EEG grapholements is presented here. The resulting classes should distinguish EEG impulse artifacts, epileptic EEG, EMG activity, normalEEG and many more. The classified EEG graphoelements are visualized in the original multi-channel EEG recording by coloring the EEG graphoelements itselves according to the class they belong to. The temporal profiles of the EEG recording are plotted. The whole procedure of classification begins with adaptive segmentation of EEG graphoelements and feature extraction followed by classification. This data processing approach ends in colored graphoelements according to class directly in the EEG recording,which is suggested to the electroencephalographer for more effective multi-channel EEG analysis.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
FS - Medical facilities, apparatus and equipment
OECD FORD branch
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Result continuities
Project
<a href="/en/project/NT14072" target="_blank" >NT14072: Predictive immunological markers in patients with hepatitis C viral infection</a><br>
Continuities
S - Specificky vyzkum na vysokych skolach
Others
Publication year
2015
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
The 5th IEEE International Conference on E-Health and Bioengineering
ISBN
978-1-4673-7545-0
ISSN
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e-ISSN
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Number of pages
4
Pages from-to
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Publisher name
Gr. T. Popa University of Medicine and Pharmacy
Place of publication
Iasi
Event location
Iasi
Event date
Nov 19, 2015
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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