An adaptive multiple-input multiple-output analog-to-digital converter for high density neuroprosthetic electrode arrays.
On chip signal compression is one of the key technologies driving development of energy efficient biotelemetry devices. In this paper, we describe a novel architecture for analog-to-digital (A/D) conversion that combines sigma delta conversion with the spatial data compression in a single module. The architecture called multiple-input multiple-output (MIMO) sigma-delta is based on a min-max gradient descent optimization of a regularized cost function that naturally leads to an A/D formulation. Experimental results with simulated and recorded multichannel data demonstrate the effectiveness of the proposed architecture to eliminate cross-channel redundancy in high density microelectrode data, thus superceding the performance of parallel independent data converters in terms of its energy efficiency.
Chakrabartty
Shantanu
S
ECE Dept. Michigan State University, East Lansing, MI 48824, USA. shantanu@msu.edu
Gore
Amit
A
Oweiss
Karim G
KG
D000200:Action Potentials / Q000502:physiology*; D000703:Analog-Digital Conversion; D017076:Computer-Aided Design; D044962:Data Compression / Q000379:methods; D004599:Electric Stimulation Therapy / Q000295:instrumentation*; D004867:Equipment Design; D019544:Equipment Failure Analysis; D008839:Microelectrodes; D009474:Neurons / Q000502:physiology*; D019736:Prostheses and Implants; D013686:Telemetry / Q000295:instrumentation*