EMBEDDED ELECTRONIC PLATFORMS FOR BIO-INSPIRED COMPUTING

生物信号处理是神经医学中一个至关重要的领域。在过去的十年里，用于从神经元中收集原位数据的探针技术取得了长足的进步，但处理大量数据所需的技术却落后了。神经元产生的信号非常小，很难与噪声区分开来。除此之外，探针将检测来自多个神经元的脉冲，这些神经元必须按形状分组，以确定哪个神经元负责哪个尖峰。为了解决这个问题，我们打算设计一种新型的模拟电路，在预处理阶段进行大部分的排序。本研究的目的是使用忆阻器件来制造这样的系统。忆阻器是一种无源电路元件，其根据流过它们的电荷量来改变其电阻状态。从神经探针施加放大的电压尖峰导致忆阻器的电阻的变化，可以测量忆阻器的电阻的变化以检测尖峰并确定尖峰所属的组。除了这种方法，本项目还将研究其他两种方法，以改善现有的检测方法使用忆阻器作为调谐设备。

Biosignal processing is an area of critical importance in neurological medicine. The probe technology used to gather in situ data from neurons has advanced leaps and bounds in the past decade, but the technology required to process this vast amount of data lags behind. The signals produced by the neurons are extremely small and are difficult to distinguish from noise. In addition to this, a probe will detect pulses from multiple neurons, which must be grouped by shape to determine which neuron is responsible for which spike. To remedy this issue, we intend to design a new type of analogue circuit that conducts most of the sorting in the pre-processing stage. The purpose of this research is to produce such a system using memristive devices. Memristors are a type of passive electrical circuit element that change their resistive state dependent on the amount of charge that has flowed through them. Applying an amplified voltage spike from a neural probe results in a change in resistance of the memristor that can be measured to both detect the spike and determine the group to which that spike belongs. In addition to this method, this project will also investigate two other methods for improving upon existing detection methods using memristors as tuning devices.