Human Cardiac Motion Research Articles

1-D Microwave Imaging of Human Cardiac Motion: An Ab-Initio Investigation

This paper presents an experimental investigation that demonstrates the possibility of 1-D imaging of human cardiac motion using a microwave Doppler sensor. Compared with the previous works that primarily monitored human respiration and heartbeat rates, the reconstruction of cardiac motion in this work will provide more information for time-domain clinical diagnosis. To fully recover the motion information from the backscattered microwave signal, an instrument-based digital-IF Doppler radar sensor employing a dc-offset removal and an extended differentiate and cross-multiply algorithm was used. A series of experiments were performed to investigate the effectiveness of the cardiac imaging from different orientations of a subject. Analysis on the experimental results indicates that in addition to the respiration and heartbeat rates, a 1-D time-domain cardiac motion that fits well with the known physiological description can be obtained. Our work reveals that substantial cardiac activity information is carried by the Doppler shifts of the backscattered microwave reflected from a human chest. The information can be reconstructed by properly designed hardware and algorithms. The possibility of noncontact cardiac imaging would have a great potential in clinical diagnosis and treatment of human heart diseases.

Left ventricular motion reconstruction based on elastic vector splines.

In medical imaging it is common to reconstruct dense motion estimates, from sparse measurements of that motion, using some form of elastic spline (thin-plate spline, snakes and other deformable models, etc.). Usually the elastic spline uses only bending energy (second-order smoothness constraint) or stretching energy (first-order smoothness constraint), or a combination of the two. These elastic splines belong to a family of elastic vector splines called the Laplacian splines. This spline family is derived from an energy minimization functional, which is composed of multiple-order smoothness constraints. These splines can be explicitly tuned to vary the smoothness of the solution according to the deformation in the modeled material/tissue. In this context, it is natural to question which members of the family will reconstruct the motion more accurately. We compare different members of this spline family to assess how well these splines reconstruct human cardiac motion. We find that the commonly used splines (containing first-order and/or second-order smoothness terms only) are not the most accurate for modeling human cardiac motion.