Visualization of EEG Using Time-Frequency Distributions

B. Zhang Stiber; S. Sato

doi:10.1055/s-0038-1636881

Methods of Information in Medicine, Table of Contents

Methods Inf Med 1997; 36(04/05): 298-301
DOI: 10.1055/s-0038-1636881

Original Article

Schattauer GmbH

Visualization of EEG Using Time-Frequency Distributions

B. Zhang Stiber

¹Department of Computer Science, The Hong Kong University of Science and Technology, Hong Kong, Japan

,

S. Sato

²Department of Biophysical Engineering, Faculty of Engineering Science, Osaka University, Osaka, Japan

› Author Affiliations

Abstract

Abstract:

The EEG is a time-varying or nonstationary signal. Frequency and amplitude are two of its significant characteristics, and are valuable clues to different states of brain activity. Detection of these temporal features is important in understanding EEGs. Commonly, spectrograms and AR models are used for EEG analysis. However, their accuracy is limited by their inherent assumption of stationarity and their trade-off between time and frequency resolution. We investigate EEG signal processing using existing compound kernel time-frequency distributions (TFDs). By providing a joint distribution of signal intensity at any frequency along time, TFDs preserve details of the temporal structure of the EEG waveform, and can extract its time-varying frequency and amplitude features. We expect that this will have significant implications for EEG analysis and medical diagnosis.

Keywords:

EEG Processing - Time-Varying Spectra - Time-Frequency Distribution

Full Text

References

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