It is well-known that sleep apnea affects the respiration and the heart rate (HR), and studies have shown that the cardiorespiratory coupling is also compromised during obstructive sleep apnea (OSA). Furthermore, the classification of hypopneas is challenging, in particular when only ECG-derived features are used. In this context, this study investigates how different ECG-derived respiratory (EDR) signals resemble the respiratory effort during different types of apneas, and how the amount of information transferred from respiration to HR varies according to the respiratory signal used, real or ECG-derived. ECG and respiratory signals of 10 patients suffering from sleep apnea were analysed, and three different EDR algorithms were used to estimate the respiratory effort. The information transfer was quantified using information dynamics on HR and both the real and estimated respiratory signals. Results suggest that the information transfer is reduced during all types of apneas/hypopneas, and they indicate that the EDR might not capture all variations in cardiorespiratory dynamics during hypopneas. As a result, the information transfer computed using the real respiratory signal achieve accuracies of up to 85% in the detection of sleep apnea with 76% of hypopneas correctly detected, compared to 79% achieved using the EDR with only 63% of correctly identified hypopneas.
Varon, C., Faes, L., Testelmans, D., Buyse, B., Van Huffel, S. (2016). Information transfer between respiration and heart rate during sleep apnea. In 2016 Computing in Cardiology Conference (CinC) (pp.845-848). IEEE Computer Society [10.22489/CinC.2016.245-293].
Information transfer between respiration and heart rate during sleep apnea
Faes, Luca;
2016-01-01
Abstract
It is well-known that sleep apnea affects the respiration and the heart rate (HR), and studies have shown that the cardiorespiratory coupling is also compromised during obstructive sleep apnea (OSA). Furthermore, the classification of hypopneas is challenging, in particular when only ECG-derived features are used. In this context, this study investigates how different ECG-derived respiratory (EDR) signals resemble the respiratory effort during different types of apneas, and how the amount of information transferred from respiration to HR varies according to the respiratory signal used, real or ECG-derived. ECG and respiratory signals of 10 patients suffering from sleep apnea were analysed, and three different EDR algorithms were used to estimate the respiratory effort. The information transfer was quantified using information dynamics on HR and both the real and estimated respiratory signals. Results suggest that the information transfer is reduced during all types of apneas/hypopneas, and they indicate that the EDR might not capture all variations in cardiorespiratory dynamics during hypopneas. As a result, the information transfer computed using the real respiratory signal achieve accuracies of up to 85% in the detection of sleep apnea with 76% of hypopneas correctly detected, compared to 79% achieved using the EDR with only 63% of correctly identified hypopneas.File | Dimensione | Formato | |
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