Stroke volume estimation by thoracocardiography is better when glottis is closed

A Wearable Technology Revisited for Cardio-Respiratory Functional Exploration

The objective of the present study is to extract new information from complex signals generated by Respiratory Inductive Plethysmography (RIP). This indirect cardio-respiratory (CR) measure is a well-known wearable solution. The authors applied time-scale analysis to estimate cardiac activity from thoracic volume variations, witnesses of CR interactions. Calibrated RIP signals gathered from 4 healthy volunteers in resting conditions are processed by Ensemble Empirical Mode Decomposition to extract cardiac volume signals and estimate stroke volumes. Averaged values of these stroke volumes (SVRIP) are compared with averaged values of stroke volumes determined simultaneously by electrical impedance cardiography (SVICG). There is a satisfactory correlation between SVRIP and SVICG (r=0.76, p<0.001) and the limits of agreement between the 2 types of measurements (±23%) satisfies the required criterion (±30%). The observed under-estimation (-58%) is argued. This validates the use of RIP for following stroke volume variations and suggests that one simple transducer can provide a quantitative exploration of both ventilatory and cardiac volumes.

Towards a suitable time-scale representation of cardio-respiratory signals through Empirical Mode Decomposition algorithms: a simulation and validation tool

To what extent is Empirical Mode Decomposition (EMD) able to differentiate the embedded components of a cardio-respiratory (CR) signal? We intend to answer this question by providing a tool which compares the performances of the original EMD algorithm with those of a noise-assisted version (CEEMD) on simulated CR signals, depending on the frequency and amplitude ratios between their respiratory and cardiac components. A statistical Bland & Altman test checks the matching of stroke volumes calculated from the extracted cardiac signal and those from the simulated one. CEEMD turns out to be better than EMD by yielding to reliable multiscale representation of simulated CR signals on a wider domain of frequency and amplitude ratios.

Empirical mode decomposition of respiratory inductive plethysmographic signals for stroke volume variations monitoring: respiratory protocol and comparison with impedance cardiography

We investigate Respiratory Inductive Plethysmography (RIP) to estimate cardiac activity from thoracic volume variations and study cardio-respiratory interactions. The objective of the present study is to evaluate the ability of RIP to monitor stroke volume (SV) variations, with reference to impedance cardiography (IMP). Five healthy volunteers in seated and supine positions were asked to blow into a manometer in order to induce significant SV decreases. Time-scale analysis was applied on calibrated RIP signals to extract cardiac volume signals. Averaged SV values, in quasi-stationary states at rest and during the respiratory maneuvers, were then estimated from these cardiac signals and from IMP signals simultaneously acquired. SV variations between rest and maneuvers were finally evaluated for both techniques. We show that SV values as well as SV variations are correlated between RIP and IMP estimations, suggesting that RIP could be used for SV variations monitoring.