Quantitative electroencephalography
Quantitative electroencephalography is a field concerned with the numerical analysis of electroencephalography data and associated behavioral correlates.
Details
Techniques used in digital signal analysis are extended to the analysis of electroencephalography. These include wavelet analysis and Fourier analysis, with new focus on shared activity between rhythms including phase synchrony and magnitude synchrony.The analog signal comprises a microvoltage time series of the EEG, sampled digitally and sampling rates adequate to over-sample the signal. Modern EEG amplifiers use adequate sampling to resolve the EEG across the traditional medical band from DC to 70 or 100 Hz, using sample rates of 250/256, 500/512, to over 1000 samples per second, depending on the intended application.
QEEG can be performed by open-source toolboxes such as EEGLAB or the Neurophysiological Biomarker Toolbox.
Several QEEG products have received Class 2 FDA medical device clearance and the method has received some medical acceptance for use in epilepsy patients. However QEEG has not been endorsed by the American Academy of Neurology or the American Clinical Neurophysiology Society.
Fourier analysis of EEG
The Fourier decomposes the EEG time series into a voltage by frequency spectral graph commonly called the "power spectrum", with power being the square of the EEG magnitude, and magnitude being the integral average of the amplitude of the EEG signal, measured from peak-to-, across the time sampled, or epoch. The epoch length determines the frequency resolution of the Fourier, with a 1-second epoch providing a 1 Hz resolution, and a 4-second epoch providing 0.25 Hz, or ±0.125 Hz resolution.Where ξ = frequency
Wavelet analysis of EEG
A wavelet is a time-frequency transformation that allows analysis of EEG signals in the time extension that is not possible with Fourier analysis.Where a = scaling; b = time