Literature DB >> 35892035

High-density neural recording system design.

Han-Sol Lee1, Kyeongho Eom1, Minju Park1, Seung-Beom Ku1, Kwonhong Lee1, Hyung-Min Lee1.   

Abstract

Implantable medical devices capable of monitoring hundreds to thousands of electrodes have received great attention in biomedical applications for understanding of the brain function and to treat brain diseases such as epilepsy, dystonia, and Parkinson's disease. Non-invasive neural recording modalities such as fMRI and EEGs were widely used since the 1960s, but to acquire better information, invasive modalities gained popularity. Since such invasive neural recording system requires high efficiency and low power operation, they have been implemented as integrated circuits. Many techniques have been developed and applied when designing integrated high-density neural recording architecture for better performance, higher efficiency, and lower power consumption. This paper covers general knowledge of neural signals and frequently used neural recording architectures for monitoring neural activity. For neural recording architecture, various neural recording amplifier structures are covered. In addition, several neural processing techniques, which can optimize the neural recording system, are also discussed. © Korean Society of Medical and Biological Engineering 2022.

Entities:  

Keywords:  High-density; Neural processing ; Neural recording ; Neural signal

Year:  2022        PMID: 35892035      PMCID: PMC9308855          DOI: 10.1007/s13534-022-00233-z

Source DB:  PubMed          Journal:  Biomed Eng Lett        ISSN: 2093-9868


  60 in total

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Journal:  Network       Date:  1998-11       Impact factor: 1.273

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3.  A Low-Voltage Chopper-Stabilized Amplifier for Fetal ECG Monitoring With a 1.41 Power Efficiency Factor.

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4.  Design of a Closed-Loop, Bidirectional Brain Machine Interface System With Energy Efficient Neural Feature Extraction and PID Control.

Authors:  Xilin Liu; Milin Zhang; Andrew G Richardson; Timothy H Lucas; Jan Van der Spiegel
Journal:  IEEE Trans Biomed Circuits Syst       Date:  2016-12-16       Impact factor: 3.833

5.  A 3 mm × 3 mm Fully Integrated Wireless Power Receiver and Neural Interface System-on-Chip.

Authors:  Chul Kim; Jiwoong Park; Sohmyung Ha; Abraham Akinin; Rajkumar Kubendran; Patrick P Mercier; Gert Cauwenberghs
Journal:  IEEE Trans Biomed Circuits Syst       Date:  2019-10-02       Impact factor: 3.833

6.  SiNAPS: An implantable active pixel sensor CMOS-probe for simultaneous large-scale neural recordings.

Authors:  Gian Nicola Angotzi; Fabio Boi; Aziliz Lecomte; Ermanno Miele; Mario Malerba; Stefano Zucca; Antonino Casile; Luca Berdondini
Journal:  Biosens Bioelectron       Date:  2018-10-19       Impact factor: 10.618

7.  A 0.19×0.17mm2 Wireless Neural Recording IC for Motor Prediction with Near-Infrared-Based Power and Data Telemetry.

Authors:  Jongyup Lim; Eunseong Moon; Michael Barrow; Samuel R Nason; Paras R Patel; Parag G Patil; Sechang Oh; Inhee Lee; Hun-Seok Kim; Dennis Sylvester; David Blaauw; Cynthia A Chestek; Jamie Phillips; Taekwang Jang
Journal:  Dig Tech Pap IEEE Int Solid State Circuits Conf       Date:  2020-04-13

8.  Relationship between intracortical electrode design and chronic recording function.

Authors:  Lohitash Karumbaiah; Tarun Saxena; David Carlson; Ketki Patil; Radhika Patkar; Eric A Gaupp; Martha Betancur; Garrett B Stanley; Lawrence Carin; Ravi V Bellamkonda
Journal:  Biomaterials       Date:  2013-07-26       Impact factor: 12.479

9.  Extracellular Recording of Entire Neural Networks Using a Dual-Mode Microelectrode Array With 19584 Electrodes and High SNR.

Authors:  Xinyue Yuan; Andreas Hierlemann; Urs Frey
Journal:  IEEE J Solid-State Circuits       Date:  2021-03-24       Impact factor: 5.013

10.  A Multi-Functional Microelectrode Array Featuring 59760 Electrodes, 2048 Electrophysiology Channels, Stimulation, Impedance Measurement and Neurotransmitter Detection Channels.

Authors:  Jelena Dragas; Vijay Viswam; Amir Shadmani; Yihui Chen; Raziyeh Bounik; Alexander Stettler; Milos Radivojevic; Sydney Geissler; Marie Obien; Jan Müller; Andreas Hierlemann
Journal:  IEEE J Solid-State Circuits       Date:  2017-04-27       Impact factor: 5.013

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