Estimation of echocardiogram parameters with the aid of impedance cardiography and artificial neural networks.

The advent of cardiovascular diseases as a disease of mass catastrophy, in recent years is alarming. It is expected to spread as an epidemic by 2030. Present methods of determining the health of one's heart include doppler based echocardiogram, MDCT (Multi Detector Computed Tomography), among various other invasive and non-invasive hemodynamic monitoring techniques. These methods require expert supervision and costly clinical set-ups, and cannot be employed by a common individual to perform a self diagnosis of one's cardiac health, unassisted. In this work, the authors propose a novel methodology using impedance cardiography (ICG), for the determination of a person's cardio-vascular health. The recorded ICG signal helps in extraction of features which are used for estimating parameters for cardiac health monitoring. The proposed methodology with the aid of artificial neural network is able to determine Stroke Volume (SV), Left Ventricular End Systolic Volume (LVESV), Left Ventricular End Diastolic Volume (LVEDV), Left Ventricular Ejection Fraction (LVEF), Iso Volumetric Contraction Time (IVCT), Iso Volumetric Relaxation Time (IVRT), Left Ventricular Ejection Time (LVET), Total Systolic Time (TST), Total Diastolic Time (TDT), and Myocardial Performance Index (MPI), with error margins of ±8.9%, ±3.8%, ±1.4%, ±7.8%, ±16.0%, ±9.0%, ±9.7%, ±6.9%, ±6.2%, and ±0.9%, respectively. The proposed methodology could be used in screening of precursors to cardiac ailments, and to keep a check on the cardio-vascular health.

Stroke Volume, Ejection Fraction and Cardiac Health Monitoring using Impedance Cardiography.

In recent years occurrence of cardiac ailments have seen an exponential rise. In view of this it is highly important to monitor one's cardiac health. Currently employed methods for cardiac health monitoring are costly, require expert supervision and are available only at central hospitals. In order to overcome these obstacles, we have proposed a novel, non-invasive, cardiac health monitoring mechanism based on Impedance Cardiography (ICG). In this work we have proposed a methodolgy for determination of stroke volume (SV), left ventricular ejection fraction (LVEF), left ventricular end systolic volume (LVESV), and iso-volumetric relaxation time (IVRT), based on ICG. The proposed models report $\mathrm{r}^{2}$ values of 0.86, 0.97, 0.99, and 0.96 for SV, LVESV, LVEF, and IVRT, respectively. The proposed methodology also provides us an insight into the use of ICG for cardiac health monitoring, and diagnosis of critical cardiac ailments.