High-Density Integrated Electrocortical Neural Interfaces

High-Density Integrated Electrocortical Neural Interfaces

Low-Noise Low-Power System-on-Chip Design Methodology

1st Edition - August 3, 2019

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  • Authors: Sohmyung Ha, Chul Kim, Patrick Mercier, Gert Cauwenberghs
  • Paperback ISBN: 9780128151150
  • eBook ISBN: 9780128151167

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High-Density Integrated Electrocortical Neural Interfaces provides a basic understanding, design strategies and implementation applications for electrocortical neural interfaces with a focus on integrated circuit design technologies. A wide variety of topics associated with the design and application of electrocortical neural implants are covered in this book. Written by leading experts in the field— Dr. Sohmyung Ha, Dr. Chul Kim, Dr. Patrick P. Mercier and Dr. Gert Cauwenberghs —the book discusses basic principles and practical design strategies of electrocorticography, electrode interfaces, signal acquisition, power delivery, data communication, and stimulation. In addition, an overview and critical review of the state-of-the-art research is included. These methodologies present a path towards the development of minimally invasive brain-computer interfaces capable of resolving microscale neural activity with wide-ranging coverage across the cortical surface.

Key Features

  • Written by leading researchers in electrocorticography in brain-computer interfaces
  • Offers a unique focus on neural interface circuit design, from electrode to interface, circuit, powering, communication and encapsulation
  • Covers the newest ECoG interface systems and electrode interfaces for ECoG and biopotential sensing


Biomedical engineers, students and researchers in electrical/electronic engineering and circuit design

Table of Contents

  • 1. Introduction to ECoG and ECoG Interfaces
    2. Electrode-to-Brain Interfaces
    3. Integrated Circuit Interfaces for Data Acquisition
    4. Integrated Circuit Interfaces for Stimulation
    5. Power Management for mm-sized ECoG Implants
    6. RF Power Transfer and its Considerations
    7. Wireless Data Communication
    8. Fully Integrated Modular ECoG Recording and Stimulation

Product details

  • No. of pages: 210
  • Language: English
  • Copyright: © Academic Press 2019
  • Published: August 3, 2019
  • Imprint: Academic Press
  • Paperback ISBN: 9780128151150
  • eBook ISBN: 9780128151167

About the Authors

Sohmyung Ha

Dr. Sohmyung Ha is an Assistant Professor of Electrical and Computer Engineering at the New York University Abu Dhabi, and as well as a Research Assistant Professor in the Department of Electrical and Computer Engineering at the Tandon School of Engineering, New York University, Brooklyn. Dr. Ha also serves as Principal Investigator at the Integrated BioElectronics Lab at NYU Abu Dhabi. He received both his M.S. and Ph.D. in Bioengineering from the University of California San Diego. Dr. Ha has contributed to numerous conference and journal publications, and currently serves as Associate Editor for Smart Health, an Elsevier journal for healthcare technologies.

Affiliations and Expertise

Assistant Professor, Electrical and Computer Engineering, Division of Engineering, New York University Abu Dhabi

Chul Kim

Chul Kim is an assistant professor at the department of bio and brain engineering and the program of brain and cognitive engineering in KAIST, South Korea. He received the Ph.D. degree in 2017 from bioengineering, UC San Diego, La Jolla, CA, USA. From 2009 to 2012, he was with SK HYNIX, Icheon, South Korea, where he designed power management circuitry for dynamic random-access memory. Dr. Kim received Gold Prize in the 16th Human-Tech Thesis Prize Contest from Samsung Electronics, Suwon, South Korea, in 2010, and the 2017–2018 Shunichi Usami Ph.D. Thesis Design Award from the Bioengineering Department, UC San Diego. He was the recipient of the 2017–2018 IEEE Solid-State Circuits Society Predoctoral Achievement Award.

Affiliations and Expertise

KAIST, South Korea.

Patrick Mercier

Patrick Mercier is an Associate Professor of Electrical and Computer Engineering and co-founder/co-director of the Center for Wearable Sensors at UC San Diego. He received his B.Sc. degree from the University of Alberta, Canada, in 2006, and the S.M. and Ph.D. degrees from MIT in 2008 and 2012, respectively. Prof. Mercier has received numerous awards, including the NSF CAREER Award in 2018, the Biocom Catalyst Award in 2017, the UCSD Academic Senate Distinguished Teaching Award in 2016, the DARPA Young Faculty Award in 2015, the Beckman Young Investigator Award in 2015, The Hellman Fellowship Award in 2014, the International Solid-State Circuits Conference (ISSCC) Jack Kilby Award in 2010, amongst others. He has published over 110 peer-reviewed papers in venues such as Nature Biotechnology, Nature Communications, ISSCC (13 papers in the last six years), Advanced Science, and others. He is an Associate Editor of the IEEE Transactions on Biomedical Circuits and Systems and the IEEE Solid-State Circuits Letters, is a member of the ISSCC, CICC, and VLSI Technical Program Committees, and has co-edited two books: Power Management Integrated Circuits (CRC Press, 2016), and Ultra-Low-Power Short-Range Radios (Springer, 2015). His research interests include the design of energy-efficient mixed-signal systems, RF circuits, power converters, and sensor interfaces for wearable, medical, and mobile applications.

Affiliations and Expertise

Electrical and Computer Engineering, UC San Diego.

Gert Cauwenberghs

Dr. Gert Cauwenberghs is currently a professor in the Department of Bioengineering at the Jacobs School of Engineering, part of the University of California San Diego. Dr. Cauwenberghs received both his M.S. and his PH.D. in Electrical Engineering from the California Institute of Technology. He is the recipient of numerous awards and research grants, and contributed to hundreds of publications. His research interests include biomedical integrated circuits and systems, micropower analog VLSI, neuromorphic engineering, computational and systems neuroscience, neuron-silicon and brain-machine interfaces, and learning and intelligent systems.

Affiliations and Expertise

Professor, Department of Bioengineering, Jacobs School of Engineering, University of California San Diego

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