Self-learning fuzzy logic control of neuromuscular block

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.