Identifikasi dan Klasifikasi Sinyal EEG terhadap Rangsangan Suara dengan Ekstraksi Wavelet dan Spektral Daya | Zendy

Esmeralda C. Djamal | Zendy; Harijono A. Tjokronegoro | Zendy

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Identifikasi dan Klasifikasi Sinyal EEG terhadap Rangsangan Suara dengan Ekstraksi Wavelet dan Spektral Daya

Author(s) -

Esmeralda C. Djamal,

Harijono A. Tjokronegoro

Publication year - 2005

Publication title -

itb journal of sciences

Language(s) - English

Resource type - Journals

ISSN - 1978-3043

DOI - 10.5614/itbj.sci.2005.37.1.5

Subject(s) - pattern recognition (psychology) , electroencephalography , wavelet transform , wavelet , artificial intelligence , computer science , speech recognition , continuous wavelet transform , discrete wavelet transform , psychology , psychiatry

In this research the development of identification and classification technique of three wave components of EEG signal, named alpha, beta and theta, is considered. The technique is combination of wavelet transform and power spectral analysis. Wavelet transform was used to extract the wave components so it reduces the data without loss of the information. The wavelet transform also reduces the aspects of non-stationary of the EEG signal. The EEG's wave classification was based on the appearance of the wave, synchronization between symmetric hemispheres, and the wave energy

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