Application of compressive sensing for EEG source localization in Brain Computer Interfaces

Aleksandr Zaitcev, Greg Cook, Wei Liu, Martyn Paley, Elizabeth Milne

Research output: Chapter in book / Conference proceedingConference article published in proceeding or bookAcademic researchpeer-review

2 Citations (Scopus)

Abstract

Brain-Computer Interfaces (BCIs) provide a way to communicate without movement and can offer significant clinical benefits therefore. Electrical brain activity recorded using electroencephalography (EEG) can be automatically interpreted by supervised learning classifiers according to the descriptive features of the signal. Compressive sensing paradigm commonly used for array antenna design and signal processing can be used to solve the underdetermined EEG source localization problem in order to extract sparse cortical current topographies to be used as spatial features for classification. This paper investigates the performance of the novel feature extraction method based on sparse source localization.

Original languageEnglish
Title of host publication2014 Loughborough Antennas and Propagation Conference, LAPC 2014
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages272-276
Number of pages5
ISBN (Electronic)9781479936625
DOIs
Publication statusPublished - 23 Dec 2014
Event2014 10th Loughborough Antennas and Propagation Conference, LAPC 2014 - Loughborough, Leicestershire, United Kingdom
Duration: 10 Nov 201411 Nov 2014

Publication series

Name2014 Loughborough Antennas and Propagation Conference, LAPC 2014

Conference

Conference2014 10th Loughborough Antennas and Propagation Conference, LAPC 2014
Country/TerritoryUnited Kingdom
CityLoughborough, Leicestershire
Period10/11/1411/11/14

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Electrical and Electronic Engineering

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