Continuous non-invasive extraction of hemodynamic variables from thoracocardiographic signals using the ensemble averaging technique: validation in anesthetized rats without ventilatory support

<i>Objective</i>. Hemodynamic monitoring is essential in preclinical research. Currently available techniques are either invasive or complex to implement. Inductive plethysmography (IP) provides an alternative for estimating stroke volume and cardiac output, as the IP signal includes ventilatory and cardiogenic oscillations (COS). COS monitoring, also defined as thoracocardiography (TCG), has been validated in humans and large laboratory animals. A recent study demonstrated proof of concept in COS extraction from the TCG signal recorded during respiratory pauses in mechanically-ventilated laboratory rats using a high-resolution IP device. The present study aims to develop an ensemble averaging (EA) algorithm, triggered by the electrocardiogram (ECG)<i>R</i>-peak, to extract COS from TCG signals in rats and continuously estimate stroke volume and cardiac output.<i>Approach</i>. After an evaluation of the IP device using the EA technique on a mechanical test bench, the applicability of the EA technique was tested in anesthetized rats without ventilatory support during a pharmacological challenge. The ability of the algorithm to track stroke volume and cardiac output changes during the hemodynamic test was also evaluated.<i>Main results</i>. Metrological evaluation of the IP device using the EA technique demonstrated linearity across the physiological operating range and resolution sufficient to detect volume changes of less than 10% of typical physiological values. Although the assumptions underlying the use of EA cannot be fully satisfied for COS extraction-due to quasi-synchrony with the ECG<i>R</i>-peak and signal non-stationarities-the method enabled extraction of satisfactory average COS waveforms, from which the system reliably captured positive and negative inotropic effects consistent with reference measurements during the pharmacological protocol.<i>Significance</i>. The evaluated algorithm demonstrates advancement over previous studies by enabling hemodynamic monitoring under usage conditions. Further studies are needed to extend its applicability to complex and physiologically relevant scenarios, positioning this technology as a potential non-invasive tool for preclinical research.