Guide to Brain-Computer Music Interfacing

The emergence of more affordable EEG equipment is fostering a renaissance of approaches to making music with brain signals.

This Guide to Brain-Computer Music Interfacing (BCMI) presents a world-class collection of BCMI tools with which adventurous explorers may pursue practical and propositional models in music neurotechnology. 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.

Topics and 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.

This unique and pioneering text/reference will appeal to researchers, graduates and advanced undergraduates from a range of different domains within computer science and beyond, such as music technology and biomedical engineering.