Design Techniques of Energy-Efficient Electrical Neural Recording System

  • Tae Ju Lee Korea Advanced Institute of Science and Technology
  • Min Kyu Je Korea Advanced Institute of Science and Technology
DOI: https://doi.org/10.23075/jicas.2022.8.3.008
Keywords: Energy-efficient neural recording system, low-power design technique, neuronal activity-dependent system operation, spike-dependent operation

Abstract

This paper reviews design techniques of the electrical neural recording system for energy-efficient operation. In order to operate neuroprosthetics by decoding action potentials and local field potentials in vivo, the electrical neural recording system is used. The recording system needs to be energy-efficiently driven by consuming low power and achieving low noise to extend battery lifetime in vivo and avoid tissue damage due to the heat. In this paper, three energy-efficient design techniques are reviewed with basic properties of the electrical neural recording system: 1) energy-efficient input structure of the amplifier, 2) front-end driven by the low supply voltage, and 3) neuronal activity-dependent recording system.

Author Biographies

Tae Ju Lee, Korea Advanced Institute of Science and Technology

Tae Ju Lee received the B.S. degree in electrical, electronics, and communication engineering from the Korea University of Technology and Education (KOREATECH), Cheonan, South Korea, in 2014, the M.S. degree in information and communication engineering from the Daegu Gyeongbuk Institute of Science and Technology (DGIST), Daegu, South Korea, in 2016, and the Ph.D. degree in electrical engineering from the Korea Advanced Institute of Science and Technology (KAIST), Daejeon, South Korea, in 2021.

From 2014 to 2016, he was with the DGIST, where he was involved in developing neural recording ICs and brain rehabilitation systems. From 2017 to 2020, he was with the KAIST, where he developed multichannel electrical neural recording ICs and led the development of multimodal neural recording ICs monitoring APs/LFPs/Calcium ions for conducting the cell-type-specific study in complex neural networks. He also developed the implantable electrical neural recording module for use in peripheral nerves and was involved in various in vivo experiments using the customized neural probe and neural activity readout IC. He is currently a Postdoctoral Researcher at the IMPACT Lab, KAIST.  His current research interests include neural interfaces focusing on the monitoring of multiple neural signals.

Min Kyu Je, Korea Advanced Institute of Science and Technology

Min Kyu Je received the M.S. and Ph.D. degrees in electrical engineering and computer science from the Korea Advanced Institute of Science and Technology (KAIST), Daejeon, South Korea, in 1998 and 2003, respectively.

He joined Samsung Electronics, Giheung, South Korea, as a Senior Engineer, in 2003, where he worked on multi-mode multi-band RF transceiver SoCs for GSM/GPRS/EDGE/WCDMA standards. From 2006 to 2013, he was with the Institute of Microelectronics (IME), Agency for Science, Technology and Research (A∗STAR), Singapore. He worked as a Senior Research Engineer, from 2006 to 2007, a Member of Technical Staff, from 2008 to 2011, a Senior Scientist, in 2012, and a Deputy Director, in 2013. From 2011 to 2013, he led the Integrated Circuits and Systems Laboratory, IME, as a Department Head. In IME, he led various projects developing low-power 3D accelerometer ASICs for high-end medical motion sensing applications, readout ASICs for nanowire biosensor arrays detecting DNA/RNA and protein biomarkers for point-of-care diagnostics, ultra-low-power sensor node SoCs for continuous real-time wireless health monitoring, and wireless implantable sensor ASICs for medical devices, as well as low-power radio SoCs and MEMS interface/control SoCs for consumer electronics and industrial applications. He was also a Program Director of NeuroDevices Program under A∗STAR Science and Engineering Research Council (SERC), from 2011 to 2013, and an Adjunct Assistant Professor with the Department of Electrical and Computer Engineering, National University of Singapore (NUS), from 2010 to 2013. From 2014 to 2015, he was an Associate Professor with the Department of Information and Communication Engineering, Daegu Gyeongbuk Institute of Science and Technology (DGIST), South Korea. Since 2016, he has been an Associate Professor with the School of Electrical Engineering, KAIST. He is the author of five book chapters and has more than 290 peer-reviewed international conference and journal publications in the areas of sensor interface IC, wireless IC, biomedical microsystem, 3D IC, device modeling and nanoelectronics. He also has more than 50 patents issued or filed. His main research interests include advanced IC platform development, including smart sensor interface ICs and ultra-low-power wireless communication ICs, as well as microsystem integration leveraging the advanced IC platform for emerging applications, such as intelligent miniature biomedical devices, ubiquitous wireless sensor nodes, and future mobile devices. He has served on the Technical Program Committee and Organizing Committee for various international conferences, symposiums, and workshops, including the IEEE International Solid-State Circuits Conference (ISSCC), the IEEE Asian Solid-State Circuits Conference (A-SSCC), and the IEEE Symposium on VLSI Circuits (SOVC). He is currently working as a Distinguished Lecturer of the IEEE Circuits and Systems Society.

Homepage : https://impact.kaist.ac.kr/

Published
2022-06-30
How to Cite
Lee, T. J., & Je, M. K. (2022). Design Techniques of Energy-Efficient Electrical Neural Recording System. Journal of Integrated Circuits and Systems, 8(3). https://doi.org/10.23075/jicas.2022.8.3.008
Issue
Vol 8 No 3 (2022)
Section
Articles