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Off-line Analysis of the P300 Event-Related Potential using Discrete Wavelet Transform

VAŘEKA, L., MAUTNER, P. Off-line Analysis of the P300 Event-Related Potential using Discrete Wavelet Transform. In TSP 2013. Piscataway: IEEE, 2013. s. 569-572. ISBN: 978-1-4799-0404-4
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The P300 component is an event-related potential associated with the process of decision making. Its accurate detection in electroencephalographic signal is essential for P300-based brain-computer interfaces. This paper proposes a new method for the P300 detection based on discrete wavelet transform. Its benefits were tested with five healthy subjects using voting classification algorithm. The accuracy of 74.4% was achieved for single trials and over 90% accuracy for averaging.

Model of Software and Hardware Infrastructure for Electrophysiology

JEŽEK, P., ŠTĚBETÁK, J., BRŮHA, P., MOUČEK, R. Model of Software and Hardware Infrastructure for Electrophysiology. In 6th International Conference on Health Informatics. Setúbal: SciTePress, 2013. s. 352-356. ISBN: 978-989-8565-37-2
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Large amounts of EEG/ERP (electroencephalography, event-related potential) data, various data formats and non-standardized domain description lead to incompatible results and interpretations of EEG/ ERP experimental data/metadata and to difficult communication between interested laboratories. Authors\' research group has solved these problems and has contributed to the building of a neuroinformatics infrastructure by developing and integrating data management and analytic tools for EEG/ERP research. The model of the software and hardware infrastructure for electrophysiology, and the context and architecture of the developed EEG/ERP Portal, serving to manage, share and process EEG/ERP experiments, are presented. Other additional tools are briefly described.

Portal for Research in Electrophysiology - Data Integration with Neuroscience Information Framework

BRŮHA, P., MOUČEK, R. Portal for Research in Electrophysiology - Data Integration with Neuroscience Information Framework. In BMEI 2012. Los Alamitos: IEEE, 2012. s. 1025-1028. ISBN: 978-1-4673-1182-3
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There is a problem with global search and data sharing. Our research group developed the EEG/ERP (electroencephalography, event-related potentials) portal; a system for storage and management of EEG/ERP resources - data, metadata, tools and materials related to EEG/ERP experiments. The EEG/ERP portal and existing solutions of data integration are presented. Authors registered the EEG/ERP portal as a source of neuroscience data and metadata within the world known project - Neuroscience Information Framework (NIF). Developed web services for harvesting EEG/ERP scenarios and experiments within NIF are presented.

The Event-Related Potential Data Processing Using ART 2 Network

VAŘEKA, L., MAUTNER, P. The Event-Related Potential Data Processing Using ART 2 Network. In BMEI 2012. Los Alamitos: IEEE, 2012. s. 467-471. ISBN: 978-1-4673-1182-3
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The event-related potentials (ERPs) obtained by stimulation are much weaker than the continuous electroencephalographic(EEG) signal. Therefore, the correct signal analysis is vital to detect the stimulation-driven signal components. This paper proposes the combination of matching pursuit for feature extraction and ART 2 neural network for clustering. Then, clusters are filtered and interpreted according to their statistical properties as ERP components or noise. The suggested method can be used to filter the EEG/ERP signal. Furthermore, its results lead to a method that improves averaging when compared to traditional approaches.

Analytic Tools and Workflows for EEG/ERP Domain

ŠTĚBETÁK, J., MOUČEK, R. Analytic Tools and Workflows for EEG/ERP Domain. In BMEI 2012. Los Alamitos: IEEE, 2012. s. 998-1000. ISBN: 978-1-4673-1182-3
Abstract PDF BibTeX

EEG/ERP (electroencephalography, event related potential) laboratories produce experimental data and metadata. Large amounts of data and various data formats lead to incompatible results and difficult communication among laboratories. Authors\' research group has contributed to the building of a neuroinformatics infrastructure by developing and integrating data management and analytic tools for EEG/ERP research. In addition, a module integrated within the EEG/ERP Portal allowing to process experimental data using analytic tools is developed. An integration of the EEG/ERP Portal with other systems is ensured using web services.

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