Modifications of unsupervised neural networks for single trial P300 detection

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F49777513%3A23520%2F18%3A43950915" target="_blank" >RIV/49777513:23520/18:43950915 - isvavai.cz</a>
Result on the web
<a href="http://dx.doi.org/10.14311/nnw.2018.28.001" target="_blank" >http://dx.doi.org/10.14311/nnw.2018.28.001</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.14311/nnw.2018.28.001" target="_blank" >10.14311/nnw.2018.28.001</a>

Result language
angličtina
Original language name
Modifications of unsupervised neural networks for single trial P300 detection
Original language description
P300 brain-computer interfaces (BCIs) have been gaining attention in recent years. To achieve good performance and accuracy, it is necessary to optimize both feature extraction and classification algorithms. This article aims at verifying whether supervised learning models based on self-organizing maps (SOM) or adaptive resonance theory (ART) can be useful for this task. For feature extraction, the state-of-the-art Windowed means paradigm was used. For classification, proposed classifiers were compared with state-of-the-art classifiers used in BCI research, such as Bayesian Linear Discriminant Analysis, or shrinkage LDA. Publicly available datasets from 15 healthy subjects were used for the experiments. The results indicated that SOM-based models yield better results than ART-based models. The best performance was achieved by the LASSO model that was comparable to state-of-the-art BCI classifiers. Further possibilities for improvements are discussed
Czech name
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Czech description
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Type
J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database
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)

Project
<a href="/en/project/LO1506" target="_blank" >LO1506: Sustainability support of the centre NTIS - New Technologies for the Information Society</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)<br>S - Specificky vyzkum na vysokych skolach

Publication year
2018
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

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