Brain-machine interface engineering
By: Sanchez, Justin Cort.
Contributor(s): Príncipe, J. C.
Material type:
BookSeries: Synthesis lectures on biomedical engineering: #17.Publisher: San Rafael, Calif. (1537 Fourth St, San Rafael, CA 94901 USA) : Morgan & Claypool Publishers, c2007Description: 1 electronic text (ix, 234 p. : col. ill.) : digital file.ISBN: 1598290355 (electronic bk.); 9781598290356 (electronic bk.); 1598290347 (pbk.); 9781598290349 (pbk.).Uniform titles: Synthesis digital library of engineering and computer science. Subject(s): Brain-computer interfaces | Computational neuroscience | Neural networks (Computer science) | Bioengineering | Neural interfaces | Brain | Neural engineering | Neuroscience | Neural representation | Motor systemsDDC classification: 620.8/2 Online resources: Abstract with links to resource | Abstract with links to resource Also available in print.| Item type | Current location | Call number | Status | Date due | Barcode | Item holds |
|---|---|---|---|---|---|---|
E books
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PK Kelkar Library, IIT Kanpur | Available | EBKE001 |
Mode of access: World Wide Web.
System requirements: Adobe Acrobat Reader.
Part of: Synthesis digital library of engineering and computer science.
Series from website.
Includes bibliographical references.
Introduction to neural interfaces -- Types of brain-machine interfaces -- Beyond state-of-the-art technology -- Computational modeling -- Generation of communication and control signals in the brain -- Motor BMIs -- Foundations of neuronal representations -- Cytoarchitecture -- Connectionism -- Neural signaling and electric fields of the brain -- Spiking models for the neuron -- Stochastic modeling -- Neural coding and decoding -- Methods of kinematic and dynamic representation -- Modeling and assumptions -- Implications for BMI signal processing -- Input-output BMI models -- Multivariate linear models -- Nonlinear models -- Regularization techniques for BMI models -- Least squares and regularization theory -- Channel selection experimental results -- Neural decoding using generative BMI models -- Population vector coding -- Sequential estimation -- Kalman filter -- Particle filters -- Hidden markov models -- Adaptive algorithms for point processes -- Adaptive filtering for point processes with a Gaussian assumption -- Monte Carlo sequential estimation for point processes -- Simulation of Monte Carlo sequential estimation using spike trains -- Encoding/decoding in motor control -- BMI systems -- Sensing neuronal activity : the electrodes -- Amplification -- The PICO system -- Portable DSP designs : the neural signal processor -- Florida wireless implantable recording electrodes.
Abstract freely available; full-text restricted to subscribers or individual document purchasers.
Neural interfaces are one of the most exciting emerging technologies to impact bioengineering and neuroscience because they enable an alternate communication channel linking directly the nervous system with man-made devices. This book reveals the essential engineering principles and signal processing tools for deriving control commands from bioelectric signals in large ensembles of neurons. The topics featured include analysis techniques for determining neural representation, modeling in motor systems, computing with neural spikes, and hardware implementation of neural interfaces. Beginning with an exploration of the historical developments that have led to the decoding of information from neural interfaces, this book compares the theory and performance of new neural engineering approaches for BMIs.
Also available in print.
Title from PDF t.p. (viewed on Nov. 4, 2008).
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