Implantation study of an analog spiking neural network in an auto-adaptive pacemaker

The goals of this research are to develop an analog spiking neural network so as to improve the performance of biventricular pacemaker (CRT devices). Implantation in silicon uses the analogical neural network approach that requires the development of a technical solution satisfying the requirement of very low energy consumption. Targeting an alternative analog solution in 0.18 mum CMOS technology, this paper presents a new approach in analog spiking neural network for the delay prediction by using a Hebbian learning algorithm.