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Guide to Brain-Computer Music Interfacing

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  • 12 uur lezen

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The emergence of affordable EEG equipment is reviving innovative methods for creating music using brain signals. This guide presents a comprehensive collection of Brain-Computer Music Interfacing (BCMI) tools for those interested in exploring music neurotechnology. It emphasizes how these tools can extract meaningful control information from brain signals and discusses designing effective generative music techniques in response to this data. Key topics include hands-free computer interaction techniques, such as event-related potentials with P300 waves, and the exploration of semiotic brain-computer interfacing (BCI) alongside machine learning's role in understanding the connections between music and emotions. The guide offers tutorials on signal extraction, brain electric fields, passive BCI, and genetic algorithms, complemented by historical surveys. It advocates for a deeper scientific understanding of the brain and its potential influence on musical creativity. Covering a broad spectrum of this interdisciplinary field, from EEG analysis to practical musical applications, this pioneering text will attract researchers, graduates, and advanced undergraduates across computer science, music technology, and biomedical engineering.

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Guide to Brain-Computer Music Interfacing, Eduardo Reck Miranda, Julien Castet

Taal
Jaar van publicatie
2014
Bindwijze
(Hardcover)
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Titel
Guide to Brain-Computer Music Interfacing
Taal
Engels
Jaar van publicatie
2014
Formaat
Hardcover
Aantal pagina's
331
ISBN10
1447165837
ISBN13
9781447165835
Reeks
Aantekening
The emergence of affordable EEG equipment is reviving innovative methods for creating music using brain signals. This guide presents a comprehensive collection of Brain-Computer Music Interfacing (BCMI) tools for those interested in exploring music neurotechnology. It emphasizes how these tools can extract meaningful control information from brain signals and discusses designing effective generative music techniques in response to this data. Key topics include hands-free computer interaction techniques, such as event-related potentials with P300 waves, and the exploration of semiotic brain-computer interfacing (BCI) alongside machine learning's role in understanding the connections between music and emotions. The guide offers tutorials on signal extraction, brain electric fields, passive BCI, and genetic algorithms, complemented by historical surveys. It advocates for a deeper scientific understanding of the brain and its potential influence on musical creativity. Covering a broad spectrum of this interdisciplinary field, from EEG analysis to practical musical applications, this pioneering text will attract researchers, graduates, and advanced undergraduates across computer science, music technology, and biomedical engineering.