Journal Article

Anaesthesia monitoring using fuzzy logic

Kouzani, Abbas, GholamHosseini, Hamid, Harrison, Michael J., Baig, Mirza Mansoor

2011

Overview

Objective Humans have a limited ability to accurately and continuously analyse large amount of data. In recent times, there has been a rapid growth in patient monitoring and medical data analysis using smart monitoring systems. Fuzzy logic-based expert systems, which can mimic human thought processes in complex circumstances, have indicated potential to improve clinicians’ performance and accurately execute repetitive tasks to which humans are ill-suited. The main goal of this study is to develop a clinically useful diagnostic alarm system based on fuzzy logic for detecting critical events during anaesthesia administration. Method The proposed diagnostic alarm system called fuzzy logic monitoring system (FLMS) is presented. New diagnostic rules and membership functions (MFs) are developed. In addition, fuzzy inference system (FIS), adaptive neuro fuzzy inference system (ANFIS), and clustering techniques are explored for developing the FLMS’ diagnostic modules. The performance of FLMS which is based on fuzzy logic expert diagnostic systems is validated through a series of off-line tests. The training and testing data set are selected randomly from 30 sets of patients’ data. Results The accuracy of diagnoses generated by the FLMS was validated by comparing the diagnostic information with the one provided by an anaesthetist for each patient. Kappa-analysis was used for measuring the level of agreement between the anaesthetist’s and FLMS’s diagnoses. When detecting hypovolaemia, a substantial level of agreement was observed between FLMS and the human expert (the anaesthetist) during surgical procedures. Conclusion The diagnostic alarm system FLMS demonstrated that evidence-based expert diagnostic systems can diagnose hypovolaemia, with a substantial degree of accuracy, in anaesthetized patients and could be useful in delivering decision support to anaesthetists.

• Publisher: Springer Netherlands,Springer,Springer Nature B.V
• Subject: Adaptive systems / Alarm systems / Anesthesia / Anesthesia - methods / Anesthesia. Intensive care medicine. Transfusions. Cell therapy and gene therapy / Anesthesiology / Anesthesiology - trends / Artificial neural networks / Biological and medical sciences / Cluster Analysis / Clustering / Computerized, statistical medical data processing and models in biomedicine / Critical Care Medicine / Data analysis / Decision Support Techniques / Diagnostic systems / Evidence-Based Medicine / Expert Systems / Fuzzy / Fuzzy Logic / Fuzzy set theory / Health Sciences / Human / Humans / Hypovolemia / Hypovolemia - diagnosis / Inference / Intensive / Intensive care medicine / Medical computing and teaching / Medical sciences / Medicine / Medicine & Public Health / Monitoring / Monitoring, Physiologic - methods / Patients / Statistics for Life Sciences / Telemedicine