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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
- Langue
- Année de publication
- 2014
- Reliure
- (rigide)
Modes de paiement
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- Titre
- Guide to Brain-Computer Music Interfacing
- Langue
- Anglais
- Auteurs
- Eduardo Reck Miranda, Julien Castet
- Éditeur
- Springer London
- Publié
- 2014
- Format
- rigide
- Pages
- 331
- ISBN10
- 1447165837
- ISBN13
- 9781447165835
- Séries
- Mots clés
- Nonfiction, Technologie & Ingénierie, Thématique musicale, Informatique & Internet, Science, Médecine, Technologie, Théories scientifiques, Neurosciences
- Description
- 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.