Session 24-2

A 75μW, 16-Channel Neural Spike-Sorting Processor
with Unsupervised Clustering

 

Abstract

We describe a neural spike-sorting processor that provides unsupervised clustering simultaneously for 16 channels. The use of a two-stage clustering algorithm, noise-tolerant distance metric, and selectively clocked high-VT register arrays makes online clustering feasible for implementation. The spike-sorting processor has a power consumption of 75μW at 270mV and an area of 2.45mm2 in a 65nm CMOS.