A Comparative Study of ECG-derived Respiration in Ambulatory Monitoring using the Single-lead ECG
Carolina Varon (TU Delft - Signal Processing Systems, Katholieke Universiteit Leuven)
Jesús Lázaro (Biomaterials and Nanomedicine (CIBER-BBN), University of Connecticut, Universidad de Zaragoza)
Michele Orini (University College London)
Margot Deviaene (Katholieke Universiteit Leuven)
Spyridon Kontaxis (Biomaterials and Nanomedicine (CIBER-BBN), Universidad de Zaragoza)
Dries Testelmans (University Hospital Leuven)
Bertien Buyse (University Hospital Leuven)
Pascal Borzée (University Hospital Leuven)
Leif Sörnmo (Lund University)
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Abstract
Cardiorespiratory monitoring is crucial for the diagnosis and management of multiple conditions such as stress and sleep disorders. Therefore, the development of ambulatory systems providing continuous, comfortable, and inexpensive means for monitoring represents an important research topic. Several techniques have been proposed in the literature to derive respiratory information from the ECG signal. Ten methods to compute single-lead ECG-derived respiration (EDR) were compared under multiple conditions, including different recording systems, baseline wander, normal and abnormal breathing patterns, changes in breathing rate, noise, and artifacts. Respiratory rates, wave morphology, and cardiorespiratory information were derived from the ECG and compared to those extracted from a reference respiratory signal. Three datasets were considered for analysis, involving a total 59 482 one-min, single-lead ECG segments recorded from 156 subjects. The results indicate that the methods based on QRS slopes outperform the other methods. This result is particularly interesting since simplicity is crucial for the development of ECG-based ambulatory systems.
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