Intelligent control of anaesthesia

Describes the structure of a real-time measuring system based on fuzzy logic. The system uses neuro-fuzzy and multi-resolution wavelet analysis for monitoring the depth of anaesthesia (DOA) based on the auditory evoked response (AER) signals, heart rate (HR) and blood pressure (BP). The AER measuring system is based on recording the brain signals using a DSP chip hosted in a PC, providing averaging and analysis using multi-resolution wavelet analysis. The analysed signal is fed to a neuro-fuzzy system (the Adaptive Network-based Fuzzy Inference System, ANFIS) where the inference takes place to obtain a measure for the DOA. Another measure for DOA is based on the cardiovascular system (HR, BP) status using a rule-based fuzzy logic classifier. The two measures are combined together using another rule-based fuzzy logic classifier to decide the final DOA. Based on the classified DOA, a target concentration is decided by a rule-based fuzzy logic controller which feeds the target to a target controller infusion (TCI) algorithm. The system forms a closed-loop controller for monitoring the DOA for patients undergoing surgical operation. (4 pages)