A Systems Approach for Real-Time Data Compression in Advanced Brain-Machine Interfaces

Abstract

Advanced array processing techniques are becoming an indispensable requirement for integrating the rapid developments in wireless high-density electronic interfaces to the central nervous system (CNS) with computational neuroscience. This work aims at describing a systems approach for data compression to enable real-time transmission of high volumes of neural data acquired by implantable microelectrode arrays to extra-cutaneous devices. We show that the tradeoff between transmission bit rate and processing complexity requires a smart coding mechanism to yield a fast and efficient neural interface capable of transmitting the information from the CNS in real-time without compromising issues of communication bandwidth and signal fidelity. The results presented demonstrate that on-chip coding offers tremendous savings in communication costs compared to raw data transmission for off-chip analysis. Performance illustrations and experimental neural data examples are described in details