Fuzzy logic based smart Anaesthesia monitoring system in the operation theatre

Abstract

Man has a limited ability to accurately and continuously analyse large amounts of data. In recent years, there has been a rapid growth in patient monitoring and medical data analysis using decision support systems, smart alarm monitoring, expert systems and many other computer aided protocols. The main goals of this study are to enhance the developed diagnostic alarm system for detecting critical events during anaesthesia and to accurately diagnose a hypovolaemia event in anaesthetized patients. The performance of the proposed diagnostic system, fuzzy logic monitoring system-2 (FLMS-2), was validated through a series of off-line tests. When detecting hypovolaemia a substantial level of agreement was observed between FLMS-2 and the human expert and it is shown that system has a better performance with sensitivity of 94%, specificity of 90% and predictability of 72%.