Title

Detection Of Ventricular Suction In An Implantable Rotary Blood Pump Using Support Vector Machines.

Creator

No Author

Abstract

A new suction detection algorithm for rotary Left Ventricular Assist Devices (LVAD) is presented. The algorithm is based on a Lagrangian Support Vector Machine (LSVM) model. Six suction indices are derived from the LVAD pump flow signal and form the inputs to the LSVM classifier. The LSVM classifier is trained and tested to classify pump flow patterns into three states: No Suction, Approaching Suction, and Suction. The proposed algorithm has been tested using existing in vivo data. When compared to three existing methods, the proposed algorithm produced superior performance in terms of classification accuracy, stability, and learning speed. The ability of the algorithm to detect suction provides a reliable platform in the development of a pump speed controller that has the capability of avoiding suction.

Publication Date

12-1-2011

Publication Title

Conference proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Conference

Volume

2011

Number of Pages

3318-3321

Document Type

Article

Personal Identifier

scopus

Socpus ID

84055176631 (Scopus)

Source API URL

https://api.elsevier.com/content/abstract/scopus_id/84055176631

This document is currently not available here.

Share

COinS