ANZCC 2019 Paper Abstract

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Paper FB1.9

Golesorkhie, Farya (Griffith University), Barnes, Zachary (Griffith University), Yang, Fuwen (Griffith University), Loree, Howard (Flow Forward Medical, Inc.), Franano, F. Nicholas (Flow Forward Medical, Inc.), Vlacic, Ljubo (Griffith University), Tansley, Geoff (Griffith University)

Data-Based Modelling of the Arteriovenous Fistula Eligibility (AFE) System for Wall Shear Stress Estimation

Scheduled for presentation during the Regular Session "Systems, Control, and Estimation" (FB1), Friday, November 29, 2019, 13:15−15:30, WZ Building Room WZ416

2019 Australian & New Zealand Control Conference (ANZCC), November 27-29, 2019, Auckland, New Zealand

This information is tentative and subject to change. Compiled on April 26, 2024

Keywords System Modelling and Identification, Estimation, Signal Processing

Abstract

The AFE System is a medical device intended to dilate the cephalic vein by increasing the blood flow and wall shear stress (WSS) in the vein over a period of 10-14 days prior to creation of an arteriovenous fistula (AVF) for haemodialysis as a means of increasing eligibility for AVF surgery and reducing rates of AVF failure. During treatment, maintaining WSS around 4 Pa in the treated vein is desirable to provide optimal vein wall stimulation while avoiding wall injury that could lead to venous stenosis. Developing a model of the AFE System and the related venous circulation could help design a control system for maintaining a WSS in the treated vein during the period of treatment when the vein is increasing in diameter. Using a broad application of the Hagen-Poiseuille law, WSS calculation could be based on differential pressure and the flow rate. The AFE System pump was characterised in a test rig utilising sensors and a data acquisition system for measuring mechanical parameters. A data-based model of the AFE pump has been developed and is presented in this paper which includes pump head estimation based on flow rate or electrical current, and motor speed measurements. All data fitted the developed relationships well, with a correlation coefficient of 93% or above.

 

 

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