Guide to Brain-Computer Music Interfacing

Nonfiction, Computers, Advanced Computing, Programming, User Interfaces, General Computing, Entertainment, Music
Cover of the book Guide to Brain-Computer Music Interfacing by , Springer London
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Author: ISBN: 9781447165842
Publisher: Springer London Publication: October 3, 2014
Imprint: Springer Language: English
Author:
ISBN: 9781447165842
Publisher: Springer London
Publication: October 3, 2014
Imprint: Springer
Language: English

This book presents a world-class collection of Brain-Computer Music Interfacing (BCMI) tools. The text focuses on how these tools enable the extraction of meaningful control information from brain signals, and discusses how to design effective generative music techniques that respond to this information. Features: reviews important techniques for hands-free interaction with computers, including event-related potentials with P300 waves; explores questions of semiotic brain-computer interfacing (BCI), and the use of machine learning to dig into relationships among music and emotions; offers tutorials on signal extraction, brain electric fields, passive BCI, and applications for genetic algorithms, along with historical surveys; describes how BCMI research advocates the importance of better scientific understanding of the brain for its potential impact on musical creativity; presents broad coverage of this emerging, interdisciplinary area, from hard-core EEG analysis to practical musical applications.

View on Amazon View on AbeBooks View on Kobo View on B.Depository View on eBay View on Walmart

This book presents a world-class collection of Brain-Computer Music Interfacing (BCMI) tools. The text focuses on how these tools enable the extraction of meaningful control information from brain signals, and discusses how to design effective generative music techniques that respond to this information. Features: reviews important techniques for hands-free interaction with computers, including event-related potentials with P300 waves; explores questions of semiotic brain-computer interfacing (BCI), and the use of machine learning to dig into relationships among music and emotions; offers tutorials on signal extraction, brain electric fields, passive BCI, and applications for genetic algorithms, along with historical surveys; describes how BCMI research advocates the importance of better scientific understanding of the brain for its potential impact on musical creativity; presents broad coverage of this emerging, interdisciplinary area, from hard-core EEG analysis to practical musical applications.

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