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- aggregation classification "A1".
- aggregation creator person.
- aggregation creator person.
- aggregation creator person.
- aggregation creator person.
- aggregation date "2011".
- aggregation format "application/pdf".
- aggregation hasFormat 2116185.bibtex.
- aggregation hasFormat 2116185.csv.
- aggregation hasFormat 2116185.dc.
- aggregation hasFormat 2116185.didl.
- aggregation hasFormat 2116185.doc.
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- aggregation hasFormat 2116185.txt.
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- aggregation hasFormat 2116185.yaml.
- aggregation isPartOf urn:issn:0018-9464.
- aggregation language "eng".
- aggregation rights "I have transferred the copyright for this publication to the publisher".
- aggregation subject "Technology and Engineering".
- aggregation title "EEG inverse problem solution using a selection procedure on a high number of electrodes with minimal influence of conductivity".
- aggregation abstract "The uncertain conductivity value of skull and brain tissue influences the accuracy of the electroencephalogram (EEG) inverse problem solution. Indeed, when the assumed conductivity in the numerical procedure is different from the actual conductivity then a source localization error is introduced. When using traditional least-squares minimization methods, the number of electrodes in the EEG cap does not influence the spatial resolution. A recently developed reduced conductivity dependence (RCD) methodology, based on the selection of electrodes, is able to increase the spatial resolution of the EEG inverse problem. This paper presents the implications of the RCD method when using a large number of electrodes in the EEG cap on the spatial resolution of the EEG inverse solutions. We show by means of numerical experiments that in contrast to traditional methods, the RCD method enables to increase the spatial resolution. The computations show that the EEG hardware should be modified with as large as possible electrodes.".
- aggregation authorList BK790518.
- aggregation endPage "877".
- aggregation issue "5".
- aggregation startPage "874".
- aggregation volume "47".
- aggregation aggregates 2117777.
- aggregation isDescribedBy 2116185.
- aggregation similarTo TMAG.2010.2072909.
- aggregation similarTo LU-2116185.