Self-learning fuzzy logic control of neuromuscular block |
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Authors: | Ross J J; Mason D G; Linkens D A; Edwards N D |
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Institution: | University Department of Anaesthetics, Northern General Hospital, Sheffield, Herries Road, Sheffield S5 7AU; Department of Automatic Control and Systems Engineering, University of Sheffield, Mappin Street, Sheffield S1 3JD |
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Abstract: | We have assessed the performance of a "self-learning" fuzzy logic
controller to administer atracurium to a required depth of neuromuscular
block. We studied 20 ASA I and II patients undergoing surgery anticipated
to last longer than 90 min. A Datex Relaxograph was used to measure the
degree of neuromuscular block, and control to a T1 twitch height set point
of 10% of baseline neuromuscular function was selected. The controller
commenced with a blank rule-base and instructed a Graseby 3400 infusion
pump to administer an atracurium infusion to maintain this level of block.
The system achieved stable control of neuromuscular block with a mean T1
error of -0.52% (SD 0.55%) accommodating a range in mean atracurium
infusion rate of 0.25- 0.44 mg kg-1 h-1. These results compare favourably
with the more computationally intensive and unwieldy adaptive control
strategies for atracurium infusion used previously. There was less
variation in infusion rates than in our previously studied fixed rules
fuzzy controller.
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