Analysing and measuring the performance of memristive integrating amplifiers. (12th July 2021) - Wang, Jiaqi; Serb, Alexantrou; Papavassiliou, Christos; Maheshwari, Sachin; Prodromakis, Themis
Abstract: Recording reliably extracellular neural activities is an essential prerequisite for the development of bioelectronics and neuroprosthetic applications. Recently, a fully differential, two‐stage, integrating pre‐amplifier was proposed for amplifying and then digitising neural signals. The amplifier featured a finely tuneable offset that was used as a variable threshold detector. Given that the amplifier is integrating, the DC operating point keeps changing during integration, rendering traditional analysis (AC/DC) unsuitable. In this work, we analyse the operation of this circuit and propose alternative definitions for validating the necessary key performance metrics, including gain, bandwidth, offset tuning range and offset sensitivity with respect to the memory states of the employed memristors. The amplification process is analysed largely through investigating the transient behaviour during the integration phase. This benchmarking approach is finally leveraged for providing useful insights and design trade‐offs of the memristor‐based integrating amplifier. Abstract : A fully differential, two‐stage, integrating pre‐amplifier was proposed for amplifying and then digitising neural signals. In this work, we analyse the operation of this circuit and propose alternative definitions for validating the necessary key performance metrics, including gain, bandwidth, offset tuning range and offset sensitivity with respect to the memory states of the employed memristors. This benchmarking approach is finally leveraged for providing useful insights and design trade‐offs of the memristor‐based integrating amplifier.