Title :
Compression-based similarity in EEG signals
Author :
Prilepok, Michal ; Platos, Jan ; Snasel, Vaclav ; Jahan, Ibrahim Salem
Author_Institution :
Dept. of Comput. Sci., VSB-Tech. Univ. of Ostrava, Ostrava, Czech Republic
Abstract :
The electrical activity of brain or EEG signal is very complex data system that may be used to many different applications such as device control using mind. It is not easy to understand and detect useful signals in continuous EEG data stream. In this paper, we are describing an application of data compression which is able to recognize important patterns in this data. The proposed algorithm uses Lampel-Ziv complexity for complexity measurement and it is able to successfully detect patterns in EEG signal.
Keywords :
brain-computer interfaces; data compression; electroencephalography; medical signal detection; pattern recognition; EEG signals; Lampel-Ziv complexity; brain; complex data system; complexity measurement; compression-based similarity; continuous EEG data stream; data compression; data patterns; device control; electrical activity; pattern detection; signal detection; Biology; Complexity theory; Silicon; BCI; EEG; EEG data; EEG waves group; Electroencephalography; LZ Complexity;
Conference_Titel :
Intelligent Systems Design and Applications (ISDA), 2013 13th International Conference on
Conference_Location :
Bangi
Print_ISBN :
978-1-4799-3515-4
DOI :
10.1109/ISDA.2013.6920743
