Estimating underlying neuronal activity from EEG using an iterative sparse technique

Abbas Sohrabpour, Yunfeng Lu, Bin He

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Scopus citations

Abstract

In this paper a novel technique for solving the bio-electromagnetic inverse problem is proposed. This method provides information about the location and extent of underlying neuronal activity. This is essential for the presurgical planning for partial epilepsy patients who are resistant to anti-epileptic drugs. The proposed algorithm takes advantage of the fact that neuronal activity transparent to EEG, arises from a spatially extended brain region. This spatial coherence is modeled within the framework of sparse signal processing techniques and makes better use of the limited number of EEG recordings. An iterative data-driven weighting is also introduced to better the extent estimation as well as eliminating the need to threshold estimated solutions.

Original languageEnglish (US)
Title of host publication2015 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2015
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages634-637
Number of pages4
ISBN (Electronic)9781424492718
DOIs
StatePublished - Nov 4 2015
Event37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2015 - Milan, Italy
Duration: Aug 25 2015Aug 29 2015

Publication series

NameProceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS
Volume2015-November
ISSN (Print)1557-170X

Other

Other37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2015
CountryItaly
CityMilan
Period8/25/158/29/15

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