DocumentCode
40222
Title
Improving MEG Performance With Additional Tangential Sensors
Author
Nurminen, Jukka ; Taulu, Samu ; Nenonen, Jukka ; Helle, Lars ; Simola, Juha ; Ahonen, Antti
Author_Institution
BioMag Lab., Hosp. District of Helsinki & Uusimaa, Helsinki, Finland
Volume
60
Issue
9
fYear
2013
fDate
Sept. 2013
Firstpage
2559
Lastpage
2566
Abstract
Recently, the signal space separation (SSS) method, based on the multipole expansion of the magnetic field, has become increasingly important in magnetoencephalography (MEG). Theoretical arguments and simulations suggest that increasing the asymmetry of the MEG sensor array from the traditional, rather symmetric geometry can significantly improve the performance of the method. To test this concept, we first simulated addition of tangentially oriented standard sensor elements to the existing 306-channel Elekta Neuromag sensor array, and evaluated and optimized the performance of the new sensor configuration. Based on the simulation results, we then constructed a prototype device with 18 additional tangential triple-sensor elements and a total of 360 channels. The experimental results from the prototype are largely in agreement with the simulations. In application of the spatial SSS method, the 360-channel device shows an approximately 100% increase in software shielding capability, while residual reconstruction noise of evoked responses is decreased by 20%. Further, the new device eliminates the need for regularization while applying the SSS method. In conclusion, we have demonstrated in practice the benefit of reducing the symmetry of the MEG array, without the need for a complete redesign.
Keywords
magnetoencephalography; medical signal processing; neurophysiology; noise; signal reconstruction; Elekta Neuromag sensor array; MEG sensor array; SSS method; magnetoencephalography; residual reconstruction noise; signal space separation method; tangential triple-sensor elements; Calibration; Magnetic noise; Magnetic sensors; Noise; Sensor arrays; Biomagnetics; biomedical signal processing; magnetoencephalography; Adult; Algorithms; Computer Simulation; Head; Humans; Magnetoencephalography; Models, Theoretical; Reproducibility of Results; Signal Processing, Computer-Assisted;
fLanguage
English
Journal_Title
Biomedical Engineering, IEEE Transactions on
Publisher
ieee
ISSN
0018-9294
Type
jour
DOI
10.1109/TBME.2013.2260541
Filename
6509958
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