EEG Analysis during Light Stimulus based on Morphological Multiresolution Analysis
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It is known that Electroencephalograph (EEG) signal shows specific responses according to the event (e.g. visual stimulus, cognition and motor imagery). Especially, by classifying short time EEG signal, features are used to control an electronic device (such system is called brain computer interface: BCI). Generally, in feature extraction from EEG signal, these features are extracted by using linear method such as FIR filter and wavelet transform etc. Though, linear method is not suitable because impulse noise distorts the important features. To avoid this, the morphological analysis method with non-linear characteristics has been used in this fields. In this paper, we propose a design method of structuring function that determine the filter characteristic of morphology. The morphological method is compared to discrete wavelet transform (DWT) from the view point of filter characteristics. We apply our method to real data observed from visual stimulation.
- Proceedings of the ISCIE International Symposium on Stochastic Systems Theory and its Applications
Proceedings of the ISCIE International Symposium on Stochastic Systems Theory and its Applications 2010(0), 113-118, 2010
The ISCIE Symposium on Stochastic Systems Theory and Its Applications