Guide to Brain-Computer Music Interfacing

ISBN-13: 9781447172109 / Angielski / Miękka / 2016 / 313 str.

Eduardo Reck Miranda; Julien Castet

Opis

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.

Spis treści

Brain-Computer Music Interfacing: Interdisciplinary Research at the Crossroads of Music, Science and Biomedical Engineering
Eduardo Reck Miranda

Electroencephalogram-Based Brain-Computer Interface: An Introduction
Ramaswamy Palaniappan

Contemporary Approaches to BCMI Using P300 Event Related Potentials
Mick Grierson, and Chris Kiefer

Prospective View on Sound Synthesis BCI Control in Light of Two Paradigms of Cognitive Neuroscience
Mitsuko Aramaki, Jean-Arthur Micoulaud-Franchi, Richard Kronland-Martinet, Jean Vion-Dury, and Sølvi Ystad

Machine Learning to Identify Neural Correlates of Music and Emotions
Ian Daly, Etienne B. Roesch, James Weaver, and Slawomir J. Nasuto

Emotional Responses During Music Listening
Konstantinos Trochidis and Emmanuel Bigan

A Tutorial on EEG Signal Processing Techniques for Mental State Recognition in Brain-Computer Interfaces
Fabien Lotte

An Introduction to EEG Source Analysis with an Illustration of a Study on Error-Related Potentials
Marco Congedo, Sandra Rousseau, and Christian Jutten

Feature Extraction and Classification of EEG Signals: The Use of a Genetic Algorithm for an Application on Alertness Prediction
Pierrick Legrand, Laurent Vézard, Marie Chavent, Freédérique Faïta-Aïnseba, and Leonardo Trujillo

On Mapping EEG Information into Music
Joel Eaton and Eduardo Reck Miranda

Retroaction Between Music and Physiology: An Approach from the Point of View of Emotions
Pierre-Henri Vulliard, Joseph Larralde, and Myriam Desainte-Catherine

Creative Music Neurotechnology with Symphony of Minds Listening
Eduardo Reck Miranda, Dan Lloyd, Zoran Josipovic, and Duncan Williams

Passive Brain-Computer Interfaces
Laurent George and Anatole Lécuyer

Blurb

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.

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.