DocumentCode :
2539875
Title :
Power spectral analysis for identifying the onset and termination of obstructive sleep apnoea events in ECG recordings
Author :
Khandoker, Ahsan H. ; Karmakar, Chandan K. ; Palaniswami, Marimuthu
Author_Institution :
Dept. of Electr. & Electron. Eng., Univ. of Melbourne, Melbourne, VIC
fYear :
2008
fDate :
20-22 Dec. 2008
Firstpage :
96
Lastpage :
100
Abstract :
The high prevalence of obstructive sleep apnoea (OSA) requires a simplified, unattended screening device that would be useful for diagnosis at the early stage. This study presents a method for screening individual OSA event based on sleep ECG signal. The overnight ECG recordings were divided into 5-second epochs containing normal (N) breathing and onset (O), maximum (M) & termination (T) of OSA events. Power spectral analysis of ECG epochs was employed to extract features. The area under receiver operating characteristics curve was estimated to determine the discrimination capability of each feature (or power in each frequency bin). The maximum ROC areas for N/O, N/M and N/T were found to be 0.78, 0.81,0.71 in the ranges of powers of 57-65 Hz, 52-72 Hz, 52-66 Hz bands respectively. An heuristic rule was applied to recognize the individual OSA events from spectral features of N,O,M,T epochs. Results show good agreement with the original annotations in an overnight sleep study. These results, therefore, could have considerable potential in ECG based screening and can aid sleep specialist in the assessment of patients with suspected sleep apnoea syndrome.
Keywords :
electrocardiography; feature extraction; medical signal detection; medical signal processing; sensitivity analysis; sleep; spectral analysis; ECG power spectral analysis; ECG signals; ECG spectral features; OSA event maximum detection; OSA event onset detection; OSA event termination detection; OSA screening device; area under ROC curve; early stage OSA diagnosis; frequency 52 Hz to 72 Hz; heuristic rule; normal breathing; obstructive sleep apnoea event; overnight ECG recordings; receiver operating characteristics; Cardiovascular diseases; Electrocardiography; Feature extraction; Frequency estimation; Power engineering and energy; Power engineering computing; Sleep apnea; Spectral analysis; Termination of employment; Tongue;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Electrical and Computer Engineering, 2008. ICECE 2008. International Conference on
Conference_Location :
Dhaka
Print_ISBN :
978-1-4244-2014-8
Electronic_ISBN :
978-1-4244-2015-5
Type :
conf
DOI :
10.1109/ICECE.2008.4769180
Filename :
4769180
Link To Document :
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