Automatic classification of Sleep-Disordered Breathing using Cardiopulmonary Coupling Analysis

Reference:
Park J, Erdenebayar U, Jeong P, Lee K. Automatic classification of sleep disordered breathing using cardiopulmonary coupling analysis. Sleep Medicine 2015. DOI: 10.1016/j.sleep.2015.02.1495

Objectives:
This study proposed a method of automatically classifying sleep-disordered breathing (SDB) events based on cardiopulmonary coupling (CPC) analysis induced from a single-channel electrocardiogram (ECG).

Conclusions:

The classification performance showed sensitivity and positivity predictive values of 77.8% and 86.4% for SDB, respectively.

Practical Significance:

CPC analysis is feasible for a system to classify automatically SDB in a home environment without any other physiological signals.

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Automatic classification of Sleep-Disordered Breathing using Cardiopulmonary Coupling Analysis

Reference:
Park J, Erdenebayar U, Jeong P, Lee K. Automatic classification of sleep disordered breathing using cardiopulmonary coupling analysis. Sleep Medicine 2015. DOI: 10.1016/j.sleep.2015.02.1495

Objectives:
This study proposed a method of automatically classifying sleep-disordered breathing (SDB) events based on cardiopulmonary coupling (CPC) analysis induced from a single-channel electrocardiogram (ECG).

Conclusions:

The classification performance showed sensitivity and positivity predictive values of 77.8% and 86.4% for SDB, respectively.

Practical Significance:

CPC analysis is feasible for a system to classify automatically SDB in a home environment without any other physiological signals.

View Publication