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Article Determination of Measurement Noise, Conductivity Errors and Electrode Mislocalization Effects To Somatosensory Dipole Localization(Biomedical Research, 2012) Şengül, Gökhan; Baysal, UğurCalculating the spatial locations, directions and magnitudes of electrically active sources of human brain by using the measured scalp potentials is known as source localization. An accu rate source localization method requires not only EEG data but also the 3-D positions and number of measurement electrodes, the numerical head model of the patient/subject and the conductivities of the layers used in the head model. In this study we computationally deter mined the effect of noise, conductivity errors and electrode mislocalizations for electrical sources located in somatosensory cortex. We first randomly selected 1000 electric sources in somatosensory cortex, and for these sources we simulated the surface potentials by using av erage conductivities given in the literature and 3-D positions of the electrodes. We then added random noise to measurements and by using noisy data; we tried to calculate the positions of the dipoles by using different electrode positions or different conductivity values. The esti mated electrical sources and original ones are compared and by this way the effect of meas urement noise, electrode mislocalizations and conductivity errors to somatosensory dipole lo calization is investigated. We conclude that for an accurate somatosensory source localization method, we need noiseless measurements, accurate conductivity values of scalp and skull lay ers and the accurate knowledge of 3-D positions of measurement sensors.Article Single Camera Photogrammetry System for Eeg Electrode Identification and Localization(Annals of Biomedical Engineering, 2010) Baysal, Uğur; Şengül, GökhanIn this study, photogrammetric coordinate measurement and color-based identification of EEG electrode positions on the human head are simultaneously implemented. A rotating, 2MP digital camera about 20 cm above the subject’s head is used and the images are acquired at predefined stop points separated azimuthally at equal angular displacements. In order to realize full automation, the electrodes have been labeled by colored circular markers and an electrode recognition algorithm has been developed. The proposed method has been tested by using a plastic head phantom carrying 25 electrode markers. Electrode locations have been determined while incorporating three different methods: (i) the proposed photogrammetric method, (ii) conventional 3D radiofrequency (RF) digitizer, and (iii) coordinate measurement machine having about 6.5 lm accuracy. It is found that the proposed system automatically identifies electrodes and localizes them with a maximum error of 0.77 mm. It is suggested that this method may be used in EEG source localization applications in the human brain.Article İnsan Kafasındaki Dokuların Öziletkenliklerinin İn Vivo E/meg Verileri ile Kestirilmesi ve Üç Değişik Kestirim Algoritma Sonuçlarının Karşılaştırılması(Signal Processing and Communications Applications Conference, 2004) Şengül, Gökhan; Baysal, Uğur; Haueısen, JensDoku öziletkenliklerinin bilinmesi, insan vücudunun güvenilir hacim iletken modellerinin oluşturulmasında ve ileri/ters biyoelektrik alan problemlerinin çözümünde gereklidir. Bu çalışmada, insan kafasindaki dokulann öziletkenliklerinin EEG ve MEG verileri kullanılarak in vivo kestirimi ipin üç farklı kestirim algoritmasi kullanılarak elde edilen sonuçlar karşılaştırılmıştır. Uygulanan bu algoritmalar; En Küçük Hatalar Karesi (E.K.H.K) kestirim algoritmasi, Bayesian MAP kestirim algoritmasi ve istatistiksel Kısıtlı Minimum Ortalama Hatalar Karesi (1.K.M.O.H.K) algoritmasıdır. Algoritmalar, geometrik yapı, ön bilgisi ile doku öziletkenlikleri ile doğrusallaştırma ve enstrümantasyon gürültüsünün istatistiksel ön bilgilerini girdi olarak kullanır. E/MEG verileri, medyan sinirin uyarıkdığı kaynak konumlandırma deneyinden sırasıyla 32 kanallı EEG ve 31 kanallı magnetometre ile somatosensory korteks üzerinden ölçülmüştür. Kafanın anatomik geometri bilgisi 256 adet TI ağırlıklı MRI görüntüden elde edilmiş ve kafa derisi, kafatası ve beyin olarak homojen üç bölgeye bölütlendirilmiştir. Sözkonusu algoritmalar kullanılarak kafa derisi, kafatası ve beyin öziletkenlikleri ve hata oranları üç farklı algoritma ile kestirilmiştir. Hata oranları E.K.H.K için %90, Bayesian Map kestirim algoriması için % 20.5 ve İ.K.M.O.H.K algoritması için %12.5 olarak hesaplanmıştır. Sonuçta İ.K.M.O.H.K algoritmasının diğer algoritmalara kıyasla daha düşük hata oranları verdiği gösterilmiştir.Article Effects of Anisotropy in a Physical Torso Phantom on Source Reconstructions From a Current Dipole(Noninvasive Functional Source Imaging of the Brain and Heart and the International Conference on Functional Biomedical Imaging, 2007) Lıehr, Mario; Şengül, Gökhan; Baysal, Uğur; Haueısen, JensIn this study, we investigated experimentally the influence of anisotropic compartments on source reconstruction using phantom measurements with an artificial current dipole as signal source. The anisotropic compartment was built from single skeins with a nine times higher conductivity than the surrounding solution. We placed the dipole at the lower borders of the anisotropic bulk and measured the magnetic field and the electric potential for each dipole location. The current dipole was rotated in relation to the anisotropic skeins and potentials and fields were recorded for different angles between anisotropic skeins and current dipole. We found that the estimated dipole orientations are strongly influenced by the anisotropy, while the reconstructed position of the dipole is not significantly influenced. We conclude that for bioelectric and biomagnetic source reconstruction, it is necessary to take into account anisotropic structures in the volume conductor if dipole orientations are of interest.
