Intelligent engineering in biomedicine

Complexity in living systems and the associated difficulties entailed in detailed physiologically meaningful measurements present many problems in the application of engineering principles into biomedicine. The interest in artificial intelligence (AI) spawned in recent years has provided a number of different paradigms which offer considerable advantages in this field. Thus, fuzzy logic offers the ability to perform logical inference under uncertain conditions. In contrast, neural networks can provide quantitative models without requiring detailed knowledge of internal structures and relationships. In addition, genetic algorithms (GA) are capable of nonlinear optimisation in cases of multiple optima, multi-objective fitness functions and hybrid (mixed quantitative and qualitative) representations. In this paper, the above paradigms are used synergetically in the area of controlled anaesthesia in the operating theatre