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Brain-Machine Interface: Closed-loop Bidirectional System Design [Hardcover]

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  • Category: Books (Technology &Amp; Engineering)
  • Author:  Liu, Xilin, Van der Spiegel, Jan
  • Author:  Liu, Xilin, Van der Spiegel, Jan
  • ISBN-10:  3319679392
  • ISBN-10:  3319679392
  • ISBN-13:  9783319679396
  • ISBN-13:  9783319679396
  • Publisher:  Springer
  • Publisher:  Springer
  • Binding:  Hardcover
  • Binding:  Hardcover
  • Pub Date:  01-Apr-2017
  • Pub Date:  01-Apr-2017
  • SKU:  3319679392-11-SPRI
  • SKU:  3319679392-11-SPRI
  • Item ID: 100730289
  • List Price: $179.99
  • Seller: ShopSpell
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This book provides an introduction to the emerging area of Brain-Machine Interfaces, with emphasis on the operation and practical design aspects. The book will help both electrical & bioengineers as well as neuroscience investigators to learn about the next generation brain-machine interfaces. The comprehensive review and design analysis will be very helpful for researchers who are new to this area or interested in the study of the brain. The in-depth discussion of practical design issues especially in animal experiments will also be valuable for experienced researchers.

1. Introduction
2. Neural Recording Front-end Design
3. Neural Feature Extraction
4. Neural Stimulator Design
5. Bidirectional Neural Interface and Closed-loop Control
6. System Integration and Experiments
7. Conclusion and Future Direction
Appendix
Bibliography
Index

Xilin Liu received the B.S. degree in Electrical Engineering from the Harbin Institute of Technology, China, in 2011. He received the M.S. and the Ph.D. degrees in Electrical Engineering from the University of Pennsylvania in 2013 and 2017, respectively. He joined Qualcomm Inc. in 2017. His research interests include analog and mixed-signal integrated circuits and system design for medical applications, brain-machine interface, data converters, and CMOS sensors.

Dr. Liu received the IEEE Solid-State Circuits Society (SSCS) 2015-16 Predoctoral Achievement Award, the Best Student Paper Award of the 2017 International Symposium on Circuits and Systems (ISCAS), the Best Paper Award (1st place) of the 2015 Biomedical Circuits and Systems Conference (BioCAS), and the Best Paper Award of the BioCAS Track of the 2014 International Symposium on Circuits and SystlC3

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