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Signal Processing and Machine Learning for Brain-Machine Interfaces, Hardback Book

Signal Processing and Machine Learning for Brain-Machine Interfaces Hardback

Edited by Toshihisa (Associate Professor, Tokyo University of Agriculture and Technology, Department o Tanaka, Mahnaz (Lecturer, University of Sheffield, UK) Arvaneh

Part of the Control, Robotics and Sensors series

Hardback

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Description

Brain-machine interfacing or brain-computer interfacing (BMI/BCI) is an emerging and challenging technology used in engineering and neuroscience.

The ultimate goal is to provide a pathway from the brain to the external world via mapping, assisting, augmenting or repairing human cognitive or sensory-motor functions. In this book an international panel of experts introduce signal processing and machine learning techniques for BMI/BCI and outline their practical and future applications in neuroscience, medicine, and rehabilitation, with a focus on EEG-based BMI/BCI methods and technologies.

Topics covered include discriminative learning of connectivity pattern of EEG; feature extraction from EEG recordings; EEG signal processing; transfer learning algorithms in BCI; convolutional neural networks for event-related potential detection; spatial filtering techniques for improving individual template-based SSVEP detection; feature extraction and classification algorithms for image RSVP based BCI; decoding music perception and imagination using deep learning techniques; neurofeedback games using EEG-based Brain-Computer Interface Technology; affective computing system and more.

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£120.00

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