A Method for Compression of Intra-Cortically-Recorded Neural Signals Dedicated to Implantable Brain–Machine Interfaces

This paper proposes an efficient data compression technique dedicated to implantable intra-cortical neural recording devices. The proposed technique benefits from processing neural signals in the Discrete Haar Wavelet Transform space, a new spike extraction approach, and a novel data framing scheme to telemeter the recorded neural information to the outside world. Based on the proposed technique, a 64-channel neural signal processor was designed and prototyped as a part of a wireless implantable extra-cellular neural recording microsystem. Designed in a 0.13- μm standard CMOS process, the 64-channel neural signal processor reported in this paper occupies ~ 0.206 mm
²
of silicon area, and consumes 94.18 μW when operating under a 1.2-V supply voltage at a master clock frequency of 1.28 MHz.