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Title: Automated processing of the single lead electrocardiogram for the detection of obstructive sleep apnoea
Sponsor: Health Research Board
Author's Homepage:
Keywords: Electrocardiogram
estimated respiration
heart rate variability
pattern recognition
sleep apnoea
Issue Date: 2003
Publisher: IEEE
Citation: de Chazal P., Heneghan C., Sheridan E., Reilly R., Nolan P., O Malley M., Automated processing of the single lead electrocardiogram for the detection of obstructive sleep apnoea, IEEE Trans. of Biomedical Engineering, 50, (6), 2003, p686-696
Series/Report no.: IEEE Trans. of Biomedical Engineering
50 (6)
Abstract: A method for the automatic processing of the electrocardiogram (ECG) for the detection of obstructive apnoea is presented. The method screens nighttime single-lead ECG recordings for the presence of major sleep apnoea and provides a minute-by-minute analysis of disordered breathing. A large independently validated database of 70 ECG recordings acquired from normal subjects and subjects with obstructive and mixed sleep apnoea, each of approximately eight hours in duration, was used throughout the study. Thirty-five of these recordings were used for training and 35 retained for independent testing. A wide variety of features based on heartbeat intervals and an ECG-derived respiratory signal were considered. Classifiers based on linear and quadratic discriminants were compared. Feature selection and regularization of classifier parameters were used to optimize classifier performance. Results show that the normal recordings could be separated from the apnoea recordings with a 100% success rate and a minute-by-minute classification accuracy of over 90% is achievable.
Description: PUBLISHED
Appears in Collections:Administrative Staff Authors (Scholarly Publications)

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