Identification of onset, maximum and termination of obstructive sleep apnoea events in single lead ECG recordings.
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.
Karmakar
Chandan K
CK
Department of Electrical & Electronic Engineering, The University of Melbourne, Melbourne, VIC 3010, Australia. c.karmakar@ee.unimelb.edu.au
Khandoker
Ahsan H
AH
Palaniswami
Marimuthu
M
D000465:Algorithms; D001185:Artificial Intelligence; D003936:Diagnosis, Computer-Assisted / Q000379:methods*; D004562:Electrocardiography / Q000379:methods*; D004867:Equipment Design; D019544:Equipment Failure Analysis; D006801:Humans; D010363:Pattern Recognition, Automated / Q000379:methods*; D017286:Polysomnography / Q000379:methods*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D020181:Sleep Apnea, Obstructive / Q000175:diagnosis*