• Login
    View Item 
    •   Home
    • Theses and Dissertations
    • MS Theses
    • View Item
    •   Home
    • Theses and Dissertations
    • MS Theses
    • View Item
    JavaScript is disabled for your browser. Some features of this site may not work without it.

    Browse

    All of KAUSTCommunitiesIssue DateSubmit DateThis CollectionIssue DateSubmit Date

    My Account

    Login

    Quick Links

    Open Access PolicyORCID LibguideTheses and Dissertations LibguideSubmit an Item

    Statistics

    Display statistics

    Respiratory Information Extraction from Electrocardiogram Signals

    • CSV
    • RefMan
    • EndNote
    • BibTex
    • RefWorks
    Thumbnail
    Name:
    Gamal Amin Thesis-final2.pdf
    Size:
    5.843Mb
    Format:
    PDF
    Description:
    Main thesis in PDF format
    Download
    Type
    Thesis
    Authors
    Amin, Gamal El Din Fathy
    Advisors
    Kosel, Jürgen cc
    Committee members
    Al-Naffouri, Tareq Y. cc
    Alouini, Mohamed-Slim cc
    Program
    Electrical Engineering
    KAUST Department
    Computer, Electrical and Mathematical Science and Engineering (CEMSE) Division
    Date
    2010-12
    Embargo End Date
    2015-01-01
    Permanent link to this record
    http://hdl.handle.net/10754/133969
    
    Metadata
    Show full item record
    Access Restrictions
    At the time of archiving, the student author of this thesis opted to temporarily restrict access to it. The full text of this thesis became available to the public after the expiration of the embargo on 2015-01-01.
    Abstract
    The Electrocardiogram (ECG) is a tool measuring the electrical activity of the heart, and it is extensively used for diagnosis and monitoring of heart diseases. The ECG signal reflects not only the heart activity but also many other physiological processes. The respiratory activity is a prominent process that affects the ECG signal due to the close proximity of the heart and the lungs. In this thesis, several methods for the extraction of respiratory process information from the ECG signal are presented. These methods allow an estimation of the lung volume and the lung pressure from the ECG signal. The potential benefit of this is to eliminate the corresponding sensors used to measure the respiration activity. A reduction of the number of sensors connected to patients will increase patients’ comfort and reduce the costs associated with healthcare. As a further result, the efficiency of diagnosing respirational disorders will increase since the respiration activity can be monitored with a common, widely available method. The developed methods can also improve the detection of respirational disorders that occur while patients are sleeping. Such disorders are commonly diagnosed in sleeping laboratories where the patients are connected to a number of different sensors. Any reduction of these sensors will result in a more natural sleeping environment for the patients and hence a higher sensitivity of the diagnosis.
    Citation
    Amin, G. E. D. F. (2010). Respiratory Information Extraction from Electrocardiogram Signals. KAUST Research Repository. https://doi.org/10.25781/KAUST-HIEE8
    DOI
    10.25781/KAUST-HIEE8
    ae974a485f413a2113503eed53cd6c53
    10.25781/KAUST-HIEE8
    Scopus Count
    Collections
    MS Theses; Electrical and Computer Engineering Program; Computer, Electrical and Mathematical Science and Engineering (CEMSE) Division

    entitlement

     
    DSpace software copyright © 2002-2022  DuraSpace
    Quick Guide | Contact Us | KAUST University Library
    Open Repository is a service hosted 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. For anonymous users the allowed maximum amount is 50 search results.

    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.