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.

A Novel Point-of-Care Smartphone Based System for Monitoring the Cardiac and Respiratory Systems

“…Thereafter, we used previously developed algorithms for the estimation of the RR23, TV22 and ischemic index21, which were modified for the cvrPhone described above, and for which we first confirmed that their JAVA implementation for the Android was equivalent to the previously developed one in MATLAB (see Supplement, Figures S5–7). …”

On Deriving Tidal Volume From Electrocardiogram During Maximal Effort Test

“…Here, we have extended this concept to a very non-stationary situation, such as a maximum effort treadmill test, where TV is constantly varying. Lowest relative errors obtained in [9] were comprised between 7 and 10%. With the proposed method, we achieved relative errors around 7% in the best-performing lead and stage.…”

“…A previous step to this work was proposed in [9], although this study presented some limitations. First, mechanical controlled ventilation is a very invasive procedure.…”

“…To the best of our knowledge, previous studies focused on noninvasive TV estimation have mostly considered ECG-unrelated techniques, such as inductive [5] or opto-electronic plethysmography [6], traqueal sounds [7] or even image acquisition using a smarthpone camera [8]. However, proportionality between ECG-derived respiration (EDR) and TV was reported in [2], whereas in [9] they conducted a conceptual study for estimating TV from ECG or intra-cardiac signals [9] in mechanically ventilated swines, hence in a controlled environment. In this work, a method for TV estimation from ECG is proposed.…”

ECG‐derived Cheyne‐Stokes respiration and periodic breathing in healthy and hospitalized populations

“…11 Recently, Weiss et al, used an algorithm that selected the best leads to derive respiratory rate from either intracardiac or body surface ECG in intubated and mechanically ventilated swine; 12 furthermore, modulation in the ECG derived respiratory rate was used by the same group to derive tidal volume. 13 Alternatively, ECG data routinely collected during polysomnography has been used to derive apnea and hypopnea; 14–16 using cyclic variations of the heart rate 14 , or changes in the QRS complex, 15–16 and with an accuracy to detect the events of 89%, 84% and 85% respectively. 14–16 …”