A 75µW, 16-channel neural spike-sorting processor with unsupervised clustering

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-V_T 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.