Rau G, Becker K, Kaufmann R, Zimmermann H J
Helmholtz-Institute for Biomedical Engineering at the RWTH, Aachen, Germany.
Artif Organs. 1995 Jan;19(1):105-12. doi: 10.1111/j.1525-1594.1995.tb02255.x.
During the last few years intelligent machines appeared in nearly all technical areas, such as consumer electronics, robotics, and industrial control systems. There are for example washing machines that work very effectively, need comparably less power than in the past, and have short execution times because they adjust their washing cycles to each set of clothes and change their washing strategies as the clothes become clean. These intelligent systems are based on fuzzy control strategies, i.e., common sense rules are used to describe a system's behavior instead of complex mathematical models. We have applied this new technology to control problems as well as to reasoning problems in biomedical engineering where appropriate mathematical models could not be built due to the complexity of the problem. After a short introduction to the concepts of fuzzy logic two approaches in the field are described: a fuzzy control strategy for the pump rate adjustment of a novel total artificial heart and an intelligent alarm system based on fuzzy inference which supports the anesthetist in monitoring and evaluating the hemodynamic state of a patient undergoing cardiac surgery. These examples indicate the inherent reliability and stability of this technique in the field of complex dynamic systems. Such properties are highly significant especially in medical applications.
在过去几年中，智能机器几乎出现在所有技术领域，如消费电子、机器人技术和工业控制系统。例如，现在的洗衣机工作效率很高，比过去消耗的电力相对更少，而且执行时间短，因为它们能根据每批衣物调整洗涤周期，并随着衣物变干净而改变洗涤策略。这些智能系统基于模糊控制策略，也就是说，用常识规则来描述系统行为，而非复杂的数学模型。我们已将这项新技术应用于控制问题以及生物医学工程中的推理问题，在这些领域，由于问题的复杂性，无法建立合适的数学模型。在对模糊逻辑概念作简短介绍后，描述了该领域的两种方法：一种用于新型全人工心脏泵速调节的模糊控制策略，以及一种基于模糊推理的智能报警系统，该系统可辅助麻醉师监测和评估心脏手术患者的血流动力学状态。这些例子表明了该技术在复杂动态系统领域所固有的可靠性和稳定性。这些特性在医疗应用中尤为重要。
