Browsing by Author "Baysal,U."

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    Application of Kalman Filter for the Estimation of Human Head Tissue Conductivities;
    (2011) Şengül,G.; Baysal,U.
    In this study Extended Kalman Filtering is proposed for the estimation of human head tissue conductivities by using EEG data. The proposed method first linearizes the relationship between the tissue conductivities and surface potentials (EEG measurements) and then iteratively estimates the tissue conductivities. In the study the mathematical background of the proposed method is presented and then performance of the proposed method is investigated by a simulation study. In the simulation study a three layered realistic head model (composed of scalp, skull and brain compartments) obtained from MR images of a real patient is used. The surface potential is calculated by using an arbitrarily chosen conductivity distribution. Then conductivity estimation is iteratively performed by using the calculated potentials and at each iteration relative error rates are calculated by comparing the orginal conductivities and estimated ones. It is found that the relative error rates decrease below of 1% after five iterations. © 2011 IEEE.
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    A Fully Automatic Photogrammetric System Design Using a 1.3 Mp Web Camera To Determine Eeg Electrode Positions;
    (2010) Şengül,G.; Baysal,U.
    In this study a fully automatic fotogrammetric system is designed to determine the EEG electrode positions in 3D. The proposed system uses a 1.3 MP web camera rotating over the subject's head. The camera is driven by a step motor. The camera takes photos in every 7.20 angles during the rotation. In order to realize full automation, electrodes are labeled by colored circular markers and an electrode identification algorithm is develeoped for full automation. The proposed method is tested by using a realistic head phantom carrying 25 electrodes. The positions of the test electrodes are also measured by a conventional 3-D digitizer. The measurements are repeated 3 times for repeatibility purposes. It is found that 3-d digitizer localizes the electrodes with an average error of 8.46 mm, 7.63 mm and 8.32 mm, while the proposed system localizes the electrodes with an average error of 1.76 mm, 1.42 mm and 1.53 mm. ©2010 IEEE.