Signal Processing and Machine Learning for Brain-Machine Interfaces (Hardcover)

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.

General

Imprint:	Institution Of Engineering And Technology
Country of origin:	United Kingdom
Series:	Control, Robotics and Sensors
Release date:	November 2018
First published:	2018
Editors:	Toshihisa Tanaka (Associate Professor) • Mahnaz Arvaneh (Lecturer)
Dimensions:	234 x 156mm (L x W)
Format:	Hardcover
Pages:	360
ISBN-13:	978-1-78561-398-2
Categories:	Books > Computing & IT > Applications of computing > Signal processing Books > Science & Mathematics > Biology, life sciences > Life sciences: general issues > Neurosciences Books > Computing & IT > Applications of computing > Artificial intelligence > Machine learning Promotions
LSN:	1-78561-398-7
Barcode:	9781785613982

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