Identification of onset, maximum and termination of obstructive sleep apnoea events in single lead ECG recordings
AuthorKarmakar, CK; Khandoker, AH; Palaniswami, M
Source TitleConference proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual Conference
AffiliationElectrical And Electronic Engineering
Document TypeConference Paper
CitationsKarmakar, 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.
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F1 - Full Written Papers Refereed
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.
KeywordsBiomedical 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
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