Comparison of Different
Methods of Time Shift
Measurement in EEG
P. JIRUŠKA1,2,3, J. PROKŠ4,
O. DRBAL4, P. SOVKA4, P. MARUSIČ5,
P. MAREŠ1
1Institute of Physiology, Academy of Sciences of the
Czech Republic, Departments of 2Physiology, 3Pediatric
Neurology, and 5Neurology, Charles University, Second
Faculty of Medicine and 4Department of Circuit
Theory, Czech Technical University, Faculty of Electrical
Engineering, Prague, Czech Republic
Received October 7, 2004
Accepted October 13, 2004
On-line available December 9, 2004
Summary
Digital signal processing techniques are often used for
measurement of small time shifts between EEG signals. In our
work we tested properties of linear cross-correlation and
phase/coherence method. The last mentioned method was used in
two versions. The first version used fast Fourier transform
(FFT) algorithm and the second was based on autoregressive
modeling with fixed or adaptive model order. Methods were
compared on several testing signals mimicking real EEG signals.
The accuracy index for each method was computed. Results showed
that for long signal segments all methods bring comparably good
results. Accuracy of FFT phase/coherence method significantly
decreased when very short segments were used and also decreased
with an increasing level of the additive noise. The best results
were obtained with autoregressive version of phase/coherence.
This method is more reliable and may be used with high accuracy
even in very short signals segments and it is also resistant to
additive noise.
Key words
EEG • Time shift • Signal processing • Cross-correlation •
Phase/coherence
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