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020 _a9781447165842
_9978-1-4471-6584-2
024 7 _a10.1007/978-1-4471-6584-2
_2doi
035 _ato000540739
040 _aSpringer
_cSpringer
_dRU-ToGU
050 4 _aQA76.9.U83
050 4 _aQA76.9.H85
072 7 _aUYZG
_2bicssc
072 7 _aCOM070000
_2bisacsh
082 0 4 _a005.437
_223
082 0 4 _a4.019
_223
245 1 0 _aGuide to Brain-Computer Music Interfacing
_helectronic resource
_cedited by Eduardo Reck Miranda, Julien Castet.
260 _aLondon :
_bSpringer London :
_bImprint: Springer,
_c2014.
300 _aXVIII, 313 p. 103 illus.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
505 0 _aBrain-Computer Music Interfacing -- Electroencephalogram-Based Brain-Computer Interface -- Contemporary Approaches to BCMI Using P300 Event Related Potentials -- Prospective View on Sound Synthesis BCI Control in Light of Two Paradigms of Cognitive Neuroscience -- Machine Learning to Identify Neural Correlates of Music and Emotions -- Emotional Responses During Music Listening -- A Tutorial on EEG Signal Processing Techniques for Mental State Recognition in Brain-Computer Interfaces -- An Introduction to EEG Source Analysis with an Illustration of a Study on Error-Related Potentials -- Feature Extraction and Classification of EEG Signals -- On Mapping EEG Information into Music -- Retroaction Between Music and Physiology -- Creative Music Neurotechnology with Symphony of Minds Listening -- Passive Brain-Computer Interfaces.
520 _aThe 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. Prof. Eduardo R. Miranda is a composer and Professor in Computer Music at Plymouth University, UK, where he is Director of the Interdisciplinary Centre for Computer Music Research (ICCMR). Dr. Julien Castet is a Research Project Manager at Immersion SAS, and a Computer and Art Freelancer based in Bordeaux, France.
650 0 _aComputer Science.
_9155490
650 0 _aNeurosciences.
_9302217
650 0 _aBiomedical engineering.
_9302214
650 0 _amusic.
_9566408
650 1 4 _aComputer Science.
_9155490
650 2 4 _aUser Interfaces and Human Computer Interaction.
_9219093
650 2 4 _aMusic.
_9566409
650 2 4 _aBiomedical Engineering.
_9302214
650 2 4 _aNeurosciences.
_9302217
700 1 _aMiranda, Eduardo Reck.
_eeditor.
_9317825
700 1 _aCastet, Julien.
_eeditor.
_9444787
710 2 _aSpringerLink (Online service)
_9143950
773 0 _tSpringer eBooks
856 4 0 _uhttp://dx.doi.org/10.1007/978-1-4471-6584-2
912 _aZDB-2-SCS
999 _c397976