SYNERGIES BETWEEN STATISTICAL DATA ANALYSIS AND NEURAL NETWORKS IN THE CONTROL OF ROTARY BLOOD PUMPS

In this paper we report the application of multilayer perceptrons MLPs to three important tasks in the control of rotary blood pumps, namely the estimation of left atrium pressure and the indication of suction as well as danger of suction, in the left atrium. In order to select those tasks for which MLPs as nonlinear classifiers are truly appropriate, conventional techniques for statistical data analysis, such as principal component analysis PCA , were applied. Eleven parameters derived from actual measurements during the performance of the pump were available as input for the three tasks.