Use of Spiking Neural Networks over Augmented EEG Dataset
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F49777513%3A23520%2F23%3A43970948" target="_blank" >RIV/49777513:23520/23:43970948 - isvavai.cz</a>
Result on the web
<a href="https://ieeexplore.ieee.org/document/10385680" target="_blank" >https://ieeexplore.ieee.org/document/10385680</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1109/BIBM58861.2023.10385680" target="_blank" >10.1109/BIBM58861.2023.10385680</a>
Alternative languages
Result language
angličtina
Original language name
Use of Spiking Neural Networks over Augmented EEG Dataset
Original language description
The relatively small size of EEG datasets impacts the use of traditional and spiking neural networks as EEG data classifiers. Since getting a larger number of EEG recordings requires much laborious laboratory work, using data augmentation methods and techniques seems beneficial. This paper deals with the experiments with, in particular, spiking neural networks over the augmented P300 dataset. Augmentation methods for EEG data are shortly presented; generative adversarial network models and sliding windows of various sizes are used to augment the original P300 dataset. The classification results over the original and augmented P300 datasets are compared, noting that classification accuracy increased by almost 27%.
Czech name
—
Czech description
—
Classification
Type
D - Article in proceedings
CEP classification
—
OECD FORD branch
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Result continuities
Project
—
Continuities
S - Specificky vyzkum na vysokych skolach
Others
Publication year
2023
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
2023 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)
ISBN
979-8-3503-3748-8
ISSN
2156-1125
e-ISSN
2156-1133
Number of pages
5
Pages from-to
2488-2492
Publisher name
IEEE
Place of publication
Piscataway
Event location
Istanbul
Event date
Dec 5, 2023
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
—