Title: Impact of insulin-stimulated glucose removal saturation on dynamic modelling and control of hyperglycaemia

Authors: J. Geoffrey Chase, Geoffrey M. Shaw, Jessica Lin, Carmen V. Doran, Maxim Bloomfield, Graeme C. Wake, Bob Broughton, Chris Hann, Thomas Lotz

Addresses: Centre for Bio-Engineering, Department of Mechanical Engineering, University of Canterbury, Private Bag 4800, Christchurch, New Zealand. Christchurch School of Medicine and Health Sciences, University of Otago, Christchurch, NZ ' Christchurch School of Medicine and Health Sciences, University of Otago, Christchurch, NZ Canterbury District Health Board, Department of Intensive Care Medicine, Christchurch Hospital, Christchurch, New Zealand. ' Department of Mechanical Engineering, Centre for Bio-Engineering, University of Canterbury, Private Bag 4800, Christchurch, New Zealand. ' Department of Mechanical Engineering, Centre for Bio-Engineering, University of Canterbury, Private Bag 4800, Christchurch, New Zealand. ' Christchurch School of Medicine and Health Sciences, University of Otago, Christchurch, New Zealand. ' Department of Mathematics and Statistics, University of Canterbury, Private Bag 4800, Christchurch, New Zealand and Massey University, Albany, New Zealand. ' Department of Mathematics and Statistics, University of Canterbury, Private Bag 4800, Christchurch, New Zealand. ' Department of Mechanical Engineering, Centre for Bio-Engineering, University of Canterbury, Private Bag 4800, Christchurch, New Zealand. ' Department of Mechanical Engineering, Centre for Bio-Engineering, University of Canterbury, Private Bag 4800, Christchurch, New Zealand

Abstract: Reported insulin-stimulated glucose removal saturation levels vary widely between individuals and trade off with insulin sensitivity in model-based control methods. A non-linear model and adaptive insulin infusion protocol enabled high-precision blood glucose control in critically ill patients using a constant insulin-stimulated glucose removal saturation parameter. Analysis of clinical trial results with and without saturation modelling indicates the significant impact of this saturation parameter on controller efficacy. Without accounting for saturation, the time-average prediction error during a five-hour trial was up to 17.6%. The average prediction error between the four patients examined in this study was reduced to 5.8% by approximating the saturation parameter. Hence, saturation is an important dynamic that requires good methods of estimation or identification to enable tight glycaemic control.

Keywords: adaptive control; saturation modelling; blood glucose control; glucose removal saturation; intensive care; drug infusion control; dynamic modelling; hyperglycaemia control; hyperglycaemia modelling; critically ill patients; insulin stimulation; biomechatronics; bioengineering.

DOI: 10.1504/IJISTA.2005.007308

International Journal of Intelligent Systems Technologies and Applications, 2005 Vol.1 No.1/2, pp.79 - 94

Published online: 05 Jul 2005 *

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