Geodesic photogrammetry for localizing sensor positions in dense-array EEG

Russell, Gerald S.; Eriksen, K. Jeffrey; Poolman, Pieter; Luu, Phan; Tucker, Don M.

doi:10.1016/j.clinph.2004.12.022

Cited by 102 publications

(104 citation statements)

References 13 publications

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“…5,38 The photogrammetric method seems to be a fast, remote, patient specific, repeatable procedure, and it is less prone to human error. To date, it is found that there are two photogrammetric methods presented for the determination of measurement electrodes.…”

Section: Introductionmentioning

confidence: 99%

“…3,27,31,43 Nowadays, photogrammetric measurements are performed mostly with digital cameras and the images are obtained by using (i) a single camera (either the camera is moved along a linear or curved path while the object is stationary or the camera is fixed and the object is moved as described in Gussekloo et al 19 and Heimonen et al 23 ); (ii) two cameras (stereo-photogrammetry); or (iii) multiple cameras. 5,38 The condition when the object size and the camera-to-object distance are both less than 100 m (330 ft) is called close-range photogrammetry, an approach where images are acquired around an object with highly convergent camera orientations, generally pointing toward the center of the object. 3,13 Close range photogrammetry has found many application areas in archaeology, architecture, anthropology, automotive and engineering (aerospace, mechanical, civil, medical, coastal), accident reconstruction, forensic sciences, as well as life sciences, and medical disciplines.…”

Section: Introductionmentioning

confidence: 99%

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Single Camera Photogrammetry System for EEG Electrode Identification and Localization

Baysal

Şengül

2010

Ann Biomed Eng

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In 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 mum 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.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Single Camera Photogrammetry System for EEG Electrode Identification and Localization

Baysal

Şengül

2010

Ann Biomed Eng

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“…The skull was segmented from the CT images. Subject bEIT session specific electrode positions for the 128 (for subjects AM, CA, and AA) and 256 (for subject S256) high density EGI sensor nets were determined by using the Geodesic Photogrammetry System (GPS), and coregistered to the CT space with EGI's image software core [62], [63]. Electrodes were added to the segmented volumetric image as 1cm in diameter and 0.7cm in height cylinders of a new tissue corresponding to the conductive gel.…”

Section: A Mri and Ct Data Collection And Segmentationmentioning

confidence: 99%

Skull Modeling Effects in Conductivity Estimates Using Parametric Electrical Impedance Tomography

Fernandez-Corazza

Turovets

Luu

et al. 2018

IEEE Trans. Biomed. Eng.

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Abstract-Objective: To estimate scalp, skull, compact bone and marrow bone electrical conductivity values based on Electrical Impedance Tomography (EIT) measurements, and to determine the influence of skull modeling details on the estimates. Methods: We collected EIT data with 62 current injection pairs and built five 6-8 million finite element (FE) head models with different grades of skull simplifications for four subjects, including three whose head models serve as Atlas in the scientific literature and in commercial equipment (Colin27 and EGI's Geosource atlases). We estimated electrical conductivity of the scalp, skull, marrow bone and compact bone tissues for each current injection pair, each model, and each subject. We also provide subject specific conductivity estimates for widely used Atlas head models.

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“…The scalp potentials were acquired and their amplitude extracted using a 256-channel EGI EEG 300 system [3,16], as well as electrode to scalp impedances. Sensor positions were determined using the Geodesic Photogrammetry System (GPS) [17].…”

Section: A Beit Data Collectionmentioning

confidence: 99%

Effects of Head Model Inaccuracies on Regional Scalp and Skull Conductivity Estimation Using Real EIT Measurements

Fernandez-Corazza

Turovets²,

Govyadinov

et al. 2016

IFMBE Proceedings

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Abstract-we estimate the scalp and skull conductivities on two healthy adults, based on bounded (or parametric) Electrical Impedance Tomography (bEIT) measurements, and using 62 current injection pairs of a high dense 128 sensor array. We compare the estimates obtained with three different electrode models: pointwise, volumetric, and the Complete Electrode Model (CEM). We also analyze the influence of the skull details and the cerebrospinal fluid (CSF). The estimated scalp (skull) conductivities for these two subjects were ~0.4 and ~0.3 S/m (~0.0045 and ~0.005 S/m), similar for all three electrode models (within 8%). Volumetric and CEM models resulted in a better fit to real data. A model of nested and closed surfaces (no skull holes) resulted in a significant overestimation (~23%) of the skull conductivity. Moreover, neglecting the CSF resulted in an extra 28% overestimation of the skull conductivity. This clearly shows the need of precise head modeling for bEIT.

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Geodesic photogrammetry for localizing sensor positions in dense-array EEG

Cited by 102 publications

References 13 publications

Single Camera Photogrammetry System for EEG Electrode Identification and Localization

Single Camera Photogrammetry System for EEG Electrode Identification and Localization

Skull Modeling Effects in Conductivity Estimates Using Parametric Electrical Impedance Tomography

Effects of Head Model Inaccuracies on Regional Scalp and Skull Conductivity Estimation Using Real EIT Measurements

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