DocumentCode :
973106
Title :
Relationship between dipole parameter estimation errors and measurement conditions in magnetoencephalography
Author :
Ogura, Yukiko ; Sekihara, Kensuke
Author_Institution :
Hitachi Ltd., Tokyo, Japan
Volume :
40
Issue :
9
fYear :
1993
Firstpage :
919
Lastpage :
924
Abstract :
In this study, a model in a computer simulation uses a single current dipole in a spherical homogeneous medium. Dipole parameters are estimated using a moving dipole procedure. Signal-to-noise ratio (SNR) is defined as the square-root of the ratio of the average signal power to the average noise power over all measurement points. At SNR>20, accurate estimation can be carried out independently of dipole depth and coil size. At SNR<20, dipole depth influences estimation error. When the dipole is located near the center of the sphere, the measurement region should include both extrema of the magnetic field to minimize estimation error. However, when the dipole is not so deep, the position of the measurement region does not influence estimation error. When SNR<4, estimation error increases as coil size increases. Coil size minimizing estimation error is determined by the ratio of environmental magnetic field noise to electrical noise. For a constant size of measurement region, increasing the number of measurement points decreases estimation error to a certain level. This error level depends on SNR.
Keywords :
bioelectric potentials; biomagnetism; biomedical measurement; brain; measurement errors; medical signal processing; parameter estimation; Monte Carlo simulation; SNR dependence; coil size; computer simulation; dipole parameter estimation errors; electrical noise; environmental magnetic field noise; magnetoencephalography; measurement conditions; moving dipole procedure; single current dipole; spherical homogeneous medium; Coils; Computer errors; Estimation error; Magnetic field measurement; Magnetic noise; Magnetoencephalography; Parameter estimation; Signal to noise ratio; Size measurement; Working environment noise; Computer Simulation; Electromagnetic Fields; Humans; Magnetoencephalography; Models, Neurological; Monte Carlo Method; Signal Processing, Computer-Assisted;
fLanguage :
English
Journal_Title :
Biomedical Engineering, IEEE Transactions on
Publisher :
ieee
ISSN :
0018-9294
Type :
jour
DOI :
10.1109/10.245613
Filename :
245613
Link To Document :
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