Waveform selection for electrical impedance tomography

Abstract

Electrical Impedance Tomography (EIT) is a non– invasive method that can be used to estimate the electrical conductivity of the head tissues. It is based on the measurement of electric potential on the scalp generated by the injection of a small electric current. If the generated electric potential distribution is measured with an Electroencephalography (EEG) equipment, the neural activity of the brain will produce signals that may affect the EIT measurements. In the present work we propose a method to reduce the effect of these signals and show a procedure to obtain the minimum number of samples that is needed to neglect the effect of the brain activity. The method requires the obtention of the optimum waveform for the applied current to minimize the variance of the electric potential estimation. As an example, the method is applied to two sets of EEG measurements of two patients, and we determine the optimum waveform and minimum number of samples for each measurement set. We also show that the replacement of the optimum waveform by a sinusoid with arbitrary phase does not significantly affect the estimations, but a previous spectral analysis of the brain activity must be performed in order to determine convenient frequencies.