Differences in right-to-left vs left-to-right interventricular conduction times in patients indicated to cardiac resynchronization therapy.

INTRODUCTION: Differences in conduction times from right ventricle to left ventricle and from left ventricle to right ventricle respectively were observed during biventricular devices implantation when changing pacing vector direction. In this article the phenomenon of interventricular conduction time differences is described and assessed in relationship to various clinical and electrophysiological parameters. METHODS: In 62 consecutive patients (9 females) interventricular conduction times between right and left ventricle in both directions were measured during cardiac resynchronization therapy device implantation procedure. Complex pacing protocol was performed. RESULTS: Investigated individuals was divided into 3 subgroups according to type of interventricular conduction pattern and statistically tested with various clinical data. Substantial differences in right-to-left vs left-to-right conduction times (> 5 ms, range 7-72 ms) were observed in 24 (39%) of all patients. They were more common in patients with dilated cardiomyopathy (20 of 38, 53%) compared to 4 (17%) of 24 patients with coronary artery disease (p = 0.011). The phenomenon occurred more often in hypertensive patients (p = 0.012). Other tested factors were nonsignificant. CONCLUSIONS: There are almost no data on this topic. The occurrence of conduction difference phenomenon is quite common in dilated cardiomyopathy while it is rare in coronary artery disease. We assume the diffuse nature of the disease and the way of remodeling of myocardium play the main role. Knowledge of this phenomenon could be useful in personalized cardiac resynchronization therapy optimization.

Prediction of lower extremities' movement by angle-angle diagrams and neural networks.

In contemporary science, the analysis of human walking is extensively used. The prediction of leg motion, as well as rehabilitation, can be usable for orthosis and prosthesis programing. Our work is focused on predicting of human walking by angle-angle diagrams, also called cyclograms. The applications of cyclograms in conjunction with artificial intelligence offers wide area of applications in medicine. But until now, this approach has not been studied or applied in practice.