The Closed-Loop Neural Interface Available Simultaneously Recording and Stimulation Using Fast Convergence Stimulation Artifact Removal

  • Geunchang Seong Korea Advanced Institute of Science and Technology
  • Jaeouk Cho Korea Advanced Institute of Science and Technology
  • Hee Young Jung Korea Advanced Institute of Science and Technology
  • Chul Kim Korea Advanced Institute of Science and Technology
Keywords: Closed-loop neural interface, Stimulation artifact removal, Fast convergence, On-chip processing

Abstract

The closed-loop neural interface is actively researched field having broad range of applications. However, it has serious issue that stimulation itself make huge artifacts (~mV) in recording system saturating amplifier, contaminating bio-signal (~ 50V) and the post-analysis during disturbed period. Several stimulation artifact removal (SAR) techniques were presented, but having trade-off between conversion time and algorithm accuracy. Here, we suggested closed-loop neural interface using fast convergence SAR algorithm while sustaining adequate removal accuracy. The amplifier-free ADC-direct 2nd-order continuous delta-sigma modulator recording stage is adopted to provide ~15Vrms input-referred integrated noise from 5Hz to 5kHz which is adequate to record bio-signal. Also, it succeeds to record ~10mV signal about the size of stimulation artifact. The fast-convergence SAR module provides stable accuracy under versatile recording environment. The chip is designed using TSMC 65-nm CMOS process. The Chip is composed of 18 input channels, 2 SAR block, 1 stimulation channel and 2 CIC Filter for down-sampling. The Entire chip area is 1mm2.

Author Biographies

Geunchang Seong, Korea Advanced Institute of Science and Technology

Geunchang Seong (Student Member, IEEE) received the B.S. and M.S. degrees in bio and brain engineering from the Korea Advanced Institute of Science and Technology (KAIST), Daejeon, Republic of Korea, in 2020 and 2022 , respectively. He is currently pursuing the Ph.D. degree in bio and brain engineering from KAIST. His research interests include bio-signal processing and integrated circuit (IC) chip design for biomedical healthcare system.

Jaeouk Cho, Korea Advanced Institute of Science and Technology

Jaeouk Cho (Student Member, IEEE) received the B.S. degree in biomedical engineering from Hanyang University, Seoul, Korea, in 2019, and the M.S degree in bio and brain engineering from Korea Advanced Institute of Science and Technology (KAIST), Daejeon, South Korea in 2021. He is currently working toward Ph.D. degree in bio and brain engineering at KAIST, Daejeon, Korea. His research interests include Neural recording IC and implantable biomedical devices.

Hee Young Jung, Korea Advanced Institute of Science and Technology

Hee Young Jung received the B.S degree in biomedical engineering and electronic engineering from Kyung Hee University, Suwon, Yongin, in 2023. She is currently working toward M.S degree in bio and brain engineering at the Korea Advanced Institute of Science and Technology     (KAIST), Daejeon, South Korea. Her research interests include signal processing.

Chul Kim, Korea Advanced Institute of Science and Technology

Chul Kim (Senior Member, IEEE) is an associate professor in the Department of Bio and Brain Engineering and the Program of Brain and Cognitive Engineering at Korea Advanced Institute of Science and Technology (KAIST), Daejeon, South Korea. He received the Ph.D. degree in  bioengineering, UC San Diego, La Jolla, CA, USA, in 2017 where he was a postdoctoral fellow from 2017 to 2019. From 2009 to 2012, he was with SK HYNIX, Icheon, South Korea, where he designed power management circuitry for dynamic random-access memory(DRAM). His current research interests include the design of energy-efficient integrated circuits and systems for fully wireless brain-machine interfaces and unobtrusive wearable sensors.

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

Published
2024-07-01
How to Cite
Seong, G., Cho, J., Jung, H. Y., & Kim, C. (2024). The Closed-Loop Neural Interface Available Simultaneously Recording and Stimulation Using Fast Convergence Stimulation Artifact Removal. Journal of Integrated Circuits and Systems, 10(3). https://doi.org/10.23075/jicas.2024.10.3.006
Section
Articles