Quantifying the performance of compressive sensing on scalp EEG signals

Amir M. Abdulghani, Alexander J. Casson, Esther Rodriguez-Villegas

    Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

    Abstract

    Compressive sensing is a new data compression paradigm that has shown significant promise in fields such as MRI. However, the practical performance of the theory very much depends on the characteristics of the signal being sensed. As such the utility of the technique cannot be extrapolated from one application to another. Electroencephalography (EEG) is a fundamental tool for the investigation of many neurological disorders and is increasingly also used in many non-medical applications, such as Brain-Computer Interfaces. This paper characterises in detail the practical performance of different implementations of the compressive sensing theory when applied to scalp EEG signals for the first time. The results are of particular interest for wearable EEG communication systems requiring low power, real-time compression of the EEG data. ©2010 IEEE.
    Original languageEnglish
    Title of host publication2010 3rd International Symposium on Applied Sciences in Biomedical and Communication Technologies, ISABEL 2010|Int. Symp. Appl. Sci. Biomed. Commun. Technol., ISABEL
    DOIs
    Publication statusPublished - 2010
    Event2010 3rd International Symposium on Applied Sciences in Biomedical and Communication Technologies, ISABEL 2010 - Roma
    Duration: 1 Jul 2010 → …

    Conference

    Conference2010 3rd International Symposium on Applied Sciences in Biomedical and Communication Technologies, ISABEL 2010
    CityRoma
    Period1/07/10 → …

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