Journal ArticleDOI
Automated processing of the single-lead electrocardiogram for the detection of obstructive sleep apnoea
TLDR
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.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.read more
Citations
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Journal ArticleDOI
Support Vector Machines for Automated Recognition of Obstructive Sleep Apnea Syndrome From ECG Recordings
TL;DR: The results suggest superior performance of SVMs in OSAS recognition supported by wavelet-based features of ECG and demonstrate considerable potential in applying SVM in an ECG-based screening device that can aid a sleep specialist in the initial assessment of patients with suspected OSAS.
Journal ArticleDOI
Apnea MedAssist: Real-time Sleep Apnea Monitor Using Single-Lead ECG
TL;DR: A low-cost, real-time sleep apnea monitoring system that uses patient's single channel nocturnal ECG to extract feature sets, and uses the support vector classifier (SVC) to detect apnea episodes with a high degree of accuracy for both home and clinical care applications.
Journal ArticleDOI
A Novel Algorithm for the Automatic Detection of Sleep Apnea From Single-Lead ECG
TL;DR: These results indicate that the use of only ECG sensors can achieve good accuracies in the detection of sleep apnea, and the contamination level of each ECG segment can be used to automatically detect artefacts, and to highlight segments that require further visual inspection.
Journal ArticleDOI
Cardiorespiratory-based sleep staging in subjects with obstructive sleep apnea
TL;DR: It is concluded that the cardiorespiratory signals provide moderate sleep-staging accuracy, however, features exhibit significant subject dependence which presents potential limits to the use of these signals in a general subject-independent sleep staging system.
Journal ArticleDOI
Use of Sample Entropy Approach to Study Heart Rate Variability in Obstructive Sleep Apnea Syndrome
TL;DR: The sample entropy approach does not show major improvement over the existing methods, and in fact, its accuracy in detecting sleep apnea is relatively low in the well classified data of the physionet.
References
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Book
Neural networks for pattern recognition
TL;DR: This is the first comprehensive treatment of feed-forward neural networks from the perspective of statistical pattern recognition, and is designed as a text, with over 100 exercises, to benefit anyone involved in the fields of neural computation and pattern recognition.
Journal ArticleDOI
Heart rate variability: standards of measurement, physiological interpretation and clinical use. Task Force of the European Society of Cardiology and the North American Society of Pacing and Electrophysiology.
Alan John Camm,Marek Malik,J. T. Bigger,G. Breithardt,Sergio Cerutti,Richard J. Cohen,Philippe Coumel,Ernest L. Fallen,H.L. Kennedy,Robert E. Kleiger,Federico Lombardi,Alberto Malliani,Arthur J. Moss,Jeffrey N. Rottman,Georg Schmidt,Peter J. Schwartz,D.H. Singer +16 more
Journal ArticleDOI
Heart rate variability. Standards of measurement, physiological interpretation, and clinical use
Marek Malik,J. Thomas Bigger,A. John Camm,Robert E. Kleiger,Alberto Malliani,Arthur J. Moss,Peter J. Schwartz +6 more
Book ChapterDOI
Neural Networks for Pattern Recognition
Suresh Kothari,Heekuck Oh +1 more
TL;DR: The chapter discusses two important directions of research to improve learning algorithms: the dynamic node generation, which is used by the cascade correlation algorithm; and designing learning algorithms where the choice of parameters is not an issue.
Journal ArticleDOI
PhysioBank, PhysioToolkit, and PhysioNet: components of a new research resource for complex physiologic signals.
Ary L. Goldberger,Luís A. Nunes Amaral,Leon Glass,Jeffrey M. Hausdorff,Plamen Ch. Ivanov,Roger G. Mark,Joseph E. Mietus,George B. Moody,Chung-Kang Peng,H. Eugene Stanley +9 more
TL;DR: The newly inaugurated Research Resource for Complex Physiologic Signals (RRSPS) as mentioned in this paper was created under the auspices of the National Center for Research Resources (NCR Resources).