BioMusic SIGNED
BioMusical Instrument
Total Cost €
0EC-Contrib. €
0Partnership
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0BioMusic project word cloud
Explore the words cloud of the BioMusic project. It provides you a very rough idea of what is the project "BioMusic" about.
Project "BioMusic" data sheet
The following table provides information about the project.
| Coordinator |
GOLDSMITHS' COLLEGE
Organization address contact info |
| Coordinator Country | United Kingdom [UK] |
| Total cost | 149˙901 € |
| EC max contribution | 149˙901 € (100%) |
| Programme |
1. H2020-EU.1.1. (EXCELLENT SCIENCE - European Research Council (ERC)) |
| Code Call | ERC-2017-PoC |
| Funding Scheme | ERC-POC |
| Starting year | 2018 |
| Duration (year-month-day) | from 2018-05-01 to 2019-10-31 |
Partnership
Take a look of project's partnership.
| # | ||||
|---|---|---|---|---|
| 1 | GOLDSMITHS' COLLEGE | UK (LONDON) | coordinator | 149˙901.00 |
Map
Project objective
The BioMusical Instrument project will create a product prototype of a wearable digital musical instrument based on biosignals from the performer’s muscles. It will allow musicians to perform electronic sounds from bodily gestures. Muscle tension will be sensed by innovative new electromyogram sensing hardware packaged in an ergonomic housing and coupled to wireless communication. Sophisticated machine learning methods developed in the ERC MetaGesture Music and H2020 Rapid-Mix projects will track musician gesture and create meaningful relationships with computer-based synthesized sound. The BioMusical Instrument will be marketed to three distinct application areas: First, it will enable “hands-free” performance of electronic music. Second, the visualization of body states will make it a useful training tool in traditional musical instrument pedagogy. Finally, the sonification of physiological signals will allow the instrument to be used in the health sector in physical rehabilitation exercises. The BioMusical Instrument will be the first product to combine EMG sensing, machine learning, and advanced audio signal processing. We have identified partners in the biomedical hardware field, the music technology industry, and rehabilitation research with whom we will benchmark and evaluate the product prototype.
Publications
| year | authors and title | journal | last update |
|---|---|---|---|
| 2019 |
Zbyszynski, Michael; Di Donato, Balandino and Tanaka, Atau Gesture-Timbre Space: Multidimensional Feature Mapping Using Machine Learning & Concatenative Synthesis published pages: , ISSN: , DOI: |
14th International Symposium on Computer Music Multidisciplinary Research (CMMR) | 2020-04-16 |
| 2018 |
Di Donato, Balandino; Bullock, Jamie and Tanaka, Atau Myo Mapper: a Myo armband to OSC mapper published pages: , ISSN: , DOI: |
Proceedings of the International Conference on New Interfaces for Musical Expression | 2020-04-16 |
| 2020 |
Michael Zbyszyński, Atau Tanaka, Federico Visi Interactive Machine Learning: Strategies for live performance using Electromyography published pages: , ISSN: , DOI: |
2020-04-16 | |
| 2019 |
Tanaka, Atau; Di Donato, Balandino; Zbyszynski, Michael and Roks, Geert Designing Gestures for Continuous Sonic Interaction published pages: , ISSN: , DOI: |
The International Conference on New Interfaces for Musical Expression | 2020-04-16 |
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The information about "BIOMUSIC" are provided by the European Opendata Portal: CORDIS opendata.