Evaluation of the optimal lengths and number of multiple windows for spectrogram estimation of SSVEP

Summary, in English

The purpose of this paper is to present the optimal number of

windows and window lengths using multiple window spectrogram for

estimation of non-stationary processes with shorter or longer

duration. Such processes could start in the EEG as a result of a

stimuli, e.g. steady-state visual evoked potentials (SSVEP). In many

applications the Welch method is used with standard set-ups for

window lengths and number of averaged spectra/spectrograms. This paper optimizes the

window lengths and number of windows of the Welch method and compare

the calculated mean squared error for this method with the optimal parameter choices of other more

recent, socalled, multiple window or multitaper methods. The results

could be useful in the choice of more optimal window functions for

spectrogram estimation in certain applications. Some examples of spectrogram estimation of

SSVEP are shown.

• Author: Maria Sandsten
• Department/s: Mathematical Statistics; Statistical Signal Processing Group
• Publishing year: 2010
• Language: English
• Pages: 372-383
• Publication/Series: Medical Engineering & Physics
• Volume: 32
• Issue: 4
• Links: http://dx.doi.org/10.1016/j.medengphy.2010.01.009
• Document type: Journal article
• Publisher: Elsevier
• Topic: Probability Theory and Statistics
• Keywords: Welch method; WOSA; Multiple Window Spectrogram; Peak Matched Multiple Windows; Time-Frequency analysis; EEG; SSVEP; Steady state visual evoked potentials; Locally Stationary Processes; Hermite functions.
• Status: Published
• Research group: Statistical Signal Processing; Stochastics in Medicine; Statistical Signal Processing Group
• ISBN/ISSN/Other: ISSN: 1873-4030