Communication channel analysis and real time compressed sensing for high density neural recording devices

Zhang, J., Duncan, K., Suo, Y., Xiong, T., Mitra, S., Tran, T. D. and Etienne-Cummings, R. (2016) Communication channel analysis and real time compressed sensing for high density neural recording devices. IEEE Transactions on Circuits and Systems I: Regular Papers, 63(5), pp. 599-608. (doi: 10.1109/TCSI.2016.2556123)

Abstract

Next generation neural recording and Brain- Machine Interface (BMI) devices call for high density or distributed systems with more than 1000 recording sites. As the recording site density grows, the device generates data on the scale of several hundred megabits per second (Mbps). Transmitting such large amounts of data induces significant power consumption and heat dissipation for the implanted electronics. Facing these constraints, efficient on-chip compression techniques become essential to the reduction of implanted systems power consumption. This paper analyzes the communication channel constraints for high density neural recording devices. This paper then quantifies the improvement on communication channel using efficient on-chip compression methods. Finally, This paper describes a Compressed Sensing (CS) based system that can reduce the data rate by > 10x times while using power on the order of a few hundred nW per recording channel.

• Item Type: Articles
• Status: Published
• Refereed: Yes
• Glasgow Author(s) Enlighten ID: Mitra, Dr Srinjoy
• Authors: Zhang, J., Duncan, K., Suo, Y., Xiong, T., Mitra, S., Tran, T. D., and Etienne-Cummings, R.
• College/School: College of Science and Engineering > School of Engineering
• Journal Name: IEEE Transactions on Circuits and Systems I: Regular Papers
• Publisher: IEEE
• ISSN: 1549-8328
• Copyright Holders: Copyright © 2016 IEEE
• First Published: First published in IEEE Transactions on Circuits and Systems I: Regular Papers 63(5): 599-608
• Publisher Policy: Reproduced in accordance with the publisher copyright policy