title: An optimized method for estimating the tidal volume from intracardiac or body surface electrocardiographic signals: implications for estimating minute ventilation.
abstract: The ability to accurately monitor tidal volume (TV) from electrocardiographic (ECG) signals holds significant promise for improving diagnosis treatment across a variety of clinical settings. The objective of this study was to develop a novel method for estimating the TV from ECG signals. In 10 mechanically ventilated swine, we collected intracardiac electrograms from catheters in the coronary sinus (CS), left ventricle (LV), and right ventricle (RV), as well as body surface electrograms, while TV was varied between 0 and 750 ml at respiratory rates of 7-14 breaths/min. We devised an algorithm to determine the optimized respirophasic modulation of the amplitude of the ECG-derived respiratory signal. Instantaneous measurement of respiratory modulation showed an absolute error of 72.55, 147.46, 85.68, 116.62, and 50.89 ml for body surface, CS, LV, RV, and RV-CS leads, respectively. Minute TV estimation demonstrated a more accurate estimation with an absolute error of 69.56, 153.39, 79.33, 122.16, and 48.41 ml for body surface, CS, LV, RV, and RV-CS leads, respectively. The RV-CS and body surface leads provided the most accurate estimations that were within 7 and 10% of the true TV, respectively. Finally, the absolute error of the bipolar RV-CS lead was significantly lower than any other lead configuration (P < 0.0001). In conclusion, we have demonstrated that ECG-derived respiratory modulation provides an accurate estimation of the TV using intracardiac or body surface signals, without the need for additional hardware.
authors.affiliation: Massachusetts General Hospital, Division of Cardiology, Harvard Medical School, Boston, Massachusetts;
authors.forename: Omid
authors.initials: O
authors.lastname: Sayadi
authors.affiliation: Institute for Medical Engineering and Science, Massachusetts Institute of Technology, Cambridge, Massachusetts; and.
authors.forename: Eric H
authors.initials: EH
authors.lastname: Weiss
authors.affiliation: Cardiology Division, Emory University School of Medicine, Atlanta, Georgia.
authors.forename: Faisal M
authors.initials: FM
authors.lastname: Merchant
authors.affiliation: Massachusetts General Hospital, Division of Cardiology, Harvard Medical School, Boston, Massachusetts;
authors.forename: Dheeraj
authors.initials: D
authors.lastname: Puppala
authors.affiliation: Massachusetts General Hospital, Division of Cardiology, Harvard Medical School, Boston, Massachusetts; Institute for Medical Engineering and Science, Massachusetts Institute of Technology, Cambridge, Massachusetts; and aarmoundas@partners.org.
authors.forename: Antonis A
authors.initials: AA
authors.lastname: Armoundas
mesh_terms: D000465:Algorithms; D000818:Animals; D018780:Body Surface Potential Mapping; D022062:Electrophysiologic Techniques, Cardiac; D008168:Lung / Q000502:physiology*; D008297:Male; D023421:Models, Animal; D011237:Predictive Value of Tests; D012123:Pulmonary Ventilation; D015203:Reproducibility of Results; D056152:Respiratory Rate; D012815:Signal Processing, Computer-Assisted; D013552:Swine; D013990:Tidal Volume; D013997:Time Factors
keywords: body surface; intracardiac electrograms; minute ventilation; percent modulation; tidal volume