Brain-machine Interface Engineering

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Morgan & Claypool Publishers, 2007 - Medical - 234 pages
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Brain-Machine Interaction provides a unique framework for understanding the motivation and techniques of applying signal processing methodologies to brain-machine interaction (BMI) design and experimentation. Each chapter begins with a historical perspective and motivating example illustrating the need for this approach in BMI design. Included in each chapter is a list of assumptions associated with each methodological choice and the impact on BMI performance. To validate and advance the state-of-the-art of BMI modeling design, model performance is discussed and how the proposed model represents the neural-to-motor mappings. Finally, the feasibility of building BMIs (technical and practical aspects) is developed in the context of digital computational hardware.

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Introduction to Neural Interfaces
Foundations of Neuronal Representations
InputOutput BMI Models
Regularization Techniques for BMI Models
Neural Decoding Using Generative BMI Models
Adaptive Algorithms for Point Processes
BMI Systems
Author Biography

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