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Titlebook: Brain-Machine Interface; Closed-loop Bidirect Xilin Liu,Jan Van der Spiegel Book 2018 Springer International Publishing AG 2018 Brain-Machi

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發(fā)表于 2025-3-21 19:35:23 | 只看該作者 |倒序瀏覽 |閱讀模式
期刊全稱Brain-Machine Interface
期刊簡稱Closed-loop Bidirect
影響因子2023Xilin Liu,Jan Van der Spiegel
視頻videohttp://file.papertrans.cn/191/190310/190310.mp4
發(fā)行地址Provides readers with background on brain-machine interfaces, a summary of design requirements, and circuit and system design examples.Presents the first comprehensive study of closed-loop bidirection
圖書封面Titlebook: Brain-Machine Interface; Closed-loop Bidirect Xilin Liu,Jan Van der Spiegel Book 2018 Springer International Publishing AG 2018 Brain-Machi
影響因子.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..
Pindex Book 2018
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書目名稱Brain-Machine Interface影響因子(影響力)




書目名稱Brain-Machine Interface影響因子(影響力)學(xué)科排名




書目名稱Brain-Machine Interface網(wǎng)絡(luò)公開度




書目名稱Brain-Machine Interface網(wǎng)絡(luò)公開度學(xué)科排名




書目名稱Brain-Machine Interface被引頻次




書目名稱Brain-Machine Interface被引頻次學(xué)科排名




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Neural Recording Front-End Design,g front-end design. However, there are two challenges remaining: the increasing bandwidth requirement for modern high-density microelectrode arrays, and the high dynamic range requirement in advanced low voltage and low power systems. This work investigates novel circuit and system designs to addres
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Neural Feature Extraction,decision support systems, including closed-loop brain–machine interface systems. The implementation of on-chip energy efficient neural feature extraction significantly reduces the wireless bandwidth required for streaming the raw data, and also minimizes the processing delay. In this chapter, neural
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Neural Stimulator Design,rements for safety, reliability, programmability, with a minimum heat dissipation. This work first gives an overview of neural stimulator design, including the physicochemical background, design requirements, system topologies, and circuit techniques. Methods for stimulus generation, stimulation wav
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System Integration and Experiments,imals, which are not feasible using conventional medical instrumentation. A successful BMI system is much more than a simple collection of individual circuit blocks. There are many practical issues and challenges that need to be carefully addressed. This chapter presents the design of a general–purp
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https://doi.org/10.1007/978-3-030-71457-4opment of BMIs have achieved significant progress in the past decade. However, several bottlenecks from the electrical engineering perspective still need to be overcome before this technique can be extensively used in experimentation and clinical treatment. The next-generation BMIs should include se
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