Detection of ERP components - comparison of basic methods and their modifications

Tomas Rondik (Department of Computer Science and Engineering, University of West Bohemia), Jindřich Ciniburk (Department of Computer Science and Engineering, University of West Bohemia)

Department of Computer Science and Engineering, University of West Bohemia, Pilsen, Czech Republic

Our research group in cooperation with other partner institutions (Czech Technical University in Prague, University Hospital in Pilsen, Škoda Auto Inc ...) specializes in the research of attention, especially attention of drivers and seriously injured people. With regard to our research we widely use the methods of electroencephalography (EEG) and event related potentials (ERP). Within our partner network we are responsible for technical and scientific issues, e.g. EEG/ERP laboratory operation, development of advanced software tools for EEG/ERP research, or analysis and proposal of signal processing methods.

EEG and ERP experiments take usually long time and produce a lot of data. With the increasing number of experiments carried out in our laboratory we had to solve not only their long-term storage and management but also proposal and implementation of methods for their efficient analysis and processing. For example, it is a common task to look for a specific ERP component in the EEG signal to verify users’ reaction to a stimulus. It is a key aspect especially in brain-computer interface applications based on the ERP technique.

We compared four methods and their modifications suitable for ERP detection - continuous wavelet transform (CWT), discrete wavelet transform (DWT), matching pursuit algorithm (MP) and Hilbert–Huang transform (HHT). The comparative criterion is their ability to detect whether an ERP component is / is not present in the EEG signal. 

There are many ways to implement a specific algorithm (or its modification), usually with the same aim – to make the algorithm faster. However, then aim of this comparison was to select a suitable method for ERP detection. The method will be used in our research and demo-applications in the future.

Preferred presentation format: Poster
Topic: Brain machine interface

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