神经网络在人工心脏输出流量和压力检测中的应用

人工心脏的输出流量和压力是血泵设计及运行的重要特性参数,其测量精度和方法直接关系到人工心脏在动物实验及临床中的实际应用效果本文提出了一种新的测量方法,即用神经网络将叶轮式人工心脏电机驱动参数换算成血泵的流量和压力与传统的测量方法相比,采用本文方法可做到无创性,不会对血液造成破坏,同时减少了感染机会;结构简单,省去了流量计和压力计,便于人工心脏完全植入体内

The Neural Networks' Application in the Detection of Output Flow Rate and Pressure in Artificial Hearts

The output flow rate and pressure of artificial hearts are very important characteristic parameters,so the precision and means of measuring them have direct effect on animal and clinic tests.On the basis of the performance experiment with blood pump, the authors put forward a new measuring method in which neural networks are applied to convert motor drive parameters to flow rate and pressure of the blood pump.Compared with the traditional measuring method,the advantages of this method lie in two aspects: first,it is non aggressive and does not destroy blood corpuscles,Meanwhile it decreases the chances of infection;second,the structure is simplified by leaving out flowmeters and manometers,and the new method has also smoothed the way for the total implantation of impeller artificial heart.