• Login
    View Item 
    •   Home
    • Conference Proceedings
    • International Telemetering Conference
    • International Telemetering Conference Proceedings, Volume 57 (2022)
    • View Item
    •   Home
    • Conference Proceedings
    • International Telemetering Conference
    • International Telemetering Conference Proceedings, Volume 57 (2022)
    • View Item
    JavaScript is disabled for your browser. Some features of this site may not work without it.

    Browse

    All of UA Campus RepositoryCommunitiesTitleAuthorsIssue DateSubmit DateSubjectsPublisherJournalThis CollectionTitleAuthorsIssue DateSubmit DateSubjectsPublisherJournal

    My Account

    LoginRegister

    About

    AboutUA Faculty PublicationsUA DissertationsUA Master's ThesesUA Honors ThesesUA PressUA YearbooksUA CatalogsUA Libraries

    Statistics

    Most Popular ItemsStatistics by CountryMost Popular Authors

    Evaluation of JPEG-2000 Image Compression as Applied to Electroencephalography

    • CSV
    • RefMan
    • EndNote
    • BibTex
    • RefWorks
    Thumbnail
    Name:
    ITC_2022_22-12-02.pdf
    Size:
    2.599Mb
    Format:
    PDF
    Download
    Author
    Tellez, Joshua
    Advisor
    Creusere, Charles D.
    Affiliation
    Klipsch School of Electrical and Computer Engineering, New Mexico State University
    Issue Date
    2022-10
    
    Metadata
    Show full item record
    Citation
    Tellez, J. (2022). Evaluation of JPEG-2000 Image Compression as Applied to Electroencephalography. International Telemetering Conference Proceedings, 57.
    Publisher
    International Foundation for Telemetering
    Journal
    International Telemetering Conference Proceedings
    URI
    http://hdl.handle.net/10150/666964
    Additional Links
    http://www.telemetry.org/
    Abstract
    In this paper we present an experiment utilizing the JPEG-2000 image compression standard to compress multi-channel electroencephalographic (EEG) signals at a lossless quality. We employ multiple pre-processing methods and assess their performance based on achieved compression ratio, computational demand, feature set, and complexity relative to existing methods from several related published works. We propose a simple pre-processing method that arranges multi-channel EEG matrices into a blocked form which yields an average 2.267:1 lossless compression ratio for the Brain Computer Interface IV-1 (BCICIV-1) dataset.
    Type
    Proceedings
    text
    Language
    en
    ISSN
    1546-2188
    0884-5123
    0074-9079
    Sponsors
    International Foundation for Telemetering
    Collections
    International Telemetering Conference Proceedings, Volume 57 (2022)

    entitlement

     
    The University of Arizona Libraries | 1510 E. University Blvd. | Tucson, AZ 85721-0055
    Tel 520-621-6442 | repository@u.library.arizona.edu
    DSpace software copyright © 2002-2017  DuraSpace
    Quick Guide | Contact Us | Send Feedback
    Open Repository is a service operated by 
    Atmire NV
     

    Export search results

    The export option will allow you to export the current search results of the entered query to a file. Different formats are available for download. To export the items, click on the button corresponding with the preferred download format.

    By default, clicking on the export buttons will result in a download of the allowed maximum amount of items.

    To select a subset of the search results, click "Selective Export" button and make a selection of the items you want to export. The amount of items that can be exported at once is similarly restricted as the full export.

    After making a selection, click one of the export format buttons. The amount of items that will be exported is indicated in the bubble next to export format.