A comparison of algorithms for estimation of a respiratory signal from the surface electrocardiogram

• Published in: Computers in biology and medicine Vol. 37; no. 3; pp. 305 - 314
• Main Authors: O’Brien, Ciara, Heneghan, Conor
• Format: Journal Article
• Language: English
• Published: United States Elsevier Ltd 01.03.2007; Elsevier Limited
• Subjects: Adult; Aged; Algorithms; AMEA; Diagnosis, Computer-Assisted; ECG; Electrocardiography - methods; Female; Fourier Analysis; Humans; Internal Medicine; Linear discriminant classification; Male; Middle Aged; Other; Plethysmography - methods; Polysomnography - methods; Posture - physiology; Pulmonary Ventilation - physiology; Reference Values; Respiration; Sensitivity and Specificity; Signal Processing, Computer-Assisted; Sleep Apnea Syndromes - diagnosis; Sleep Apnea Syndromes - physiopathology; Sleep disordered breathing; Software; Statistics as Topic; ECG; Respiration; AMEA; Sleep disordered breathing; Linear discriminant classification
• ISSN: 0010-4825; 1879-0534
• DOI: 10.1016/j.compbiomed.2006.02.002

We provide a quantitative comparison between two new methods for deriving a respiratory signal from a single lead electrocardiogram, and the published technique of Behbehani et al. [An investigation of the mean electrical axis angle and respiration during sleep, in: Proceedings of the Second Joint EMBS/BMES Conference Houston, TX, USA, October 2002]. We conclude that (a) single ECG lead methods for estimating the respiratory signal are well correlated with inductance plethysmographs (correlation coefficients of approximately 0.75), (b) single lead estimates are more robust than methods based on the mean electrical axis, (c) body position has little impact on measurement accuracy and (d) single lead respiratory estimates can classify epochs of sleep disordered respiration with approximately 82% accuracy.