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Please use this identifier to cite or link to this item: http://hdl.handle.net/2328/25764

Title: Reconstruction of respiratory patterns from electrocardiographic signals
Authors: Nazeran, Homer
Behbehani, Khosrow
Yen, Fu-chung
Ray, Prameela
Keywords: Biomedical monitoring
Signal processing
Issue Date: 1998
Publisher: Institute of Electrical and Electronics Engineers Computer Society (IEEE Publishing)
Citation: Nazeran, H., Behbehani, K., Yen, F. and Ray, P. 1998. Proceedings of the 2nd International Conference on Bioelectromagnetism, 1998, 183-184.
Abstract: Presently there is lack of a reliable method for monitoring the respiratory cycles in ambulatory patients. Knowledge of respiratory pattern is useful in many clinical situations. With the ECG signal being the most frequently monitored biomedical signal, it is essential to extract the respiratory waveform from ordinary ECG tracings. Such a technique would permit reliable detection of respiratory efforts in healthy and diseased patients. Here, the authors present the result of a pilot study in which the ECG signals from lead II (LL+:RA-) and a modified chest lead I (V1+:LA-) were used to derive the respiration waveforms from the mean electrical axis of the heart. The ECG-derived respiratory patterns compared favorably with those obtained from airflow measurements.
URI: http://hdl.handle.net/2328/25764
ISBN: 0780338677
Appears in Collections:Computer Science, Engineering and Mathematics - Collected Works

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