Lossy Compression Techniques for EEG Signals

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aut.publication.placeHo Chi Minh City, Vietnamen_NZ
aut.relation.endpage6
aut.relation.startpage1
aut.researcherLi, Xuejun
dc.contributor.authorDao, PTen_NZ
dc.contributor.authorLi, XJen_NZ
dc.contributor.authorDo, HNen_NZ
dc.date.accessioned2018-10-18T03:23:27Z
dc.date.available2018-10-18T03:23:27Z
dc.date.copyright2015en_NZ
dc.date.issued2015en_NZ
dc.description.abstractElectroencephalogram (EEG) signal has been widely used to analyze brain activities so as to diagnose certain brain-related diseases. They are usually recorded for a fairly long interval with adequate resolution, which requires considerable amount of memory space for storage and transmission. Compression techniques are necessary to reduce the signal size. As compared to lossless compression techniques, lossy compression techniques would provide much higher compression ratio (CR) by taking advantage of the limitation of human perception. However, that is achieved at the cost of introducing more compression distortion, which reduces the fidelity of EEG signals. How to select a suitable lossy EEG compression technique? This motivates us to survey those existing lossy compression algorithms reported in the last two decades. We attempt to analyze the algorithms and provide a qualitative comparison among them.
dc.identifier.citationIn Advanced Technologies for Communications (ATC), 2015 International Conference on (pp. 154-159). IEEE.
dc.identifier.doi10.1109/ATC.2015.7388309
dc.identifier.urihttps://hdl.handle.net/10292/11886
dc.publisherIEEE
dc.relation.urihttps://ieeexplore.ieee.org/document/7388309
dc.rightsCopyright © 2016 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
dc.rights.accessrightsOpenAccessen_NZ
dc.subjectElectroencephalogram signal; Data compression; Compression ratio; Percentage root-mean-square difference
dc.titleLossy Compression Techniques for EEG Signalsen_NZ
dc.typeConference Contribution
pubs.elements-id195194
pubs.organisational-data/AUT
pubs.organisational-data/AUT/Design & Creative Technologies
pubs.organisational-data/AUT/Design & Creative Technologies/School of Engineering
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