Identification of onset, maximum and termination of obstructive sleep apnoea events in single lead ECG recordings

    Thumbnail
    Citations
    Scopus
    Web of Science
    Altmetric
    3
    2
    Author
    Karmakar, CK; Khandoker, AH; Palaniswami, M
    Date
    2008-01-01
    Source Title
    2008 30TH ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY, VOLS 1-8
    Publisher
    IEEE
    University of Melbourne Author/s
    KHANDOKER, AHSAN; Palaniswami, Marimuthu; Karmakar, Chandan
    Affiliation
    Electrical And Electronic Engineering
    Metadata
    Show full item record
    Document Type
    Conference Paper
    Citations
    Karmakar, C. K., Khandoker, A. H. & Palaniswami, M. (2008). Identification of onset, maximum and termination of obstructive sleep apnoea events in single lead ECG recordings. 2008 30TH ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY, VOLS 1-8, 2008, pp.1072-1075. IEEE. https://doi.org/10.1109/IEMBS.2008.4649345.
    Access Status
    This item is currently not available from this repository
    URI
    http://hdl.handle.net/11343/33141
    DOI
    10.1109/IEMBS.2008.4649345
    Description

    F1 - Full Written Papers Refereed
    Abstract
    Measuring the Apnoea Hypopnoea Index (AHI) is important for determining the severity of any apnoea patient. This study presents a method of screening each apnoea event separately based on the single lead Electrocardiogram (EGG) signal. The whole ECG of a subject was divided into Normal, Onset, OSA-maximum and Termination epochs with length of 5 seconds. PSD analysis was used for determining the features directly from the ECG. ROC area was calculated to determine the discrimination capability of each feature (or power in each frequency bin) found by PSD analysis. The maximum ROC area found between Normal vs. OSA-maximum was 0.81 in the frequency range of 52-72 Hz. The ROC area and significant frequency band for Normal vs. Onset and Normal vs. Termination were 0.78, 0.78 and 57-65 Hz, 52-66 Hz respectively.
    Keywords
    Biomedical Engineering not elsewhere classified; Pattern Recognition and Data Mining; Rehabilitation Engineering; Biomedical Engineering not elsewhere classified; Pattern Recognition; Rehabilitation Engineering ; Medical Instrumentation; Computer Equipment; Computer and Electronic Office Equipment; Medical Instruments

    Export Reference in RIS Format     

    Collections