An algorithm using R-Q-S series from ECG tracings can accurately reconstruct respiration signals, offering a potential method for monitoring breathing frequency without additional sensors.
This study presents a method for reconstructing respiration signals from ECG tracings based on average electrical-cardiac-axis theory with heart rate variability. The algorithm is simplified to use QRS characteristic points and subsequent spectrum analysis. The experiments were conducted on eight healthy patients during rest with spontaneous (voluntarily) and paced breathings. Five QRS characteristic series are constructed, and the corresponding electrocardiography (ECG)-derived respiration (EDR) is compared with measured data. The experiment results show the R-Q-S series-derived respiration exhibited superior correlation with the original respiration from the perspective of breathing frequency.
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Lin et al. (2013) studied this question.
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