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BioMusical Instrument

Total Cost €


EC-Contrib. €






Project "BioMusic" data sheet

The following table provides information about the project.


Organization address
city: LONDON
postcode: SE14 6NW

contact info
title: n.a.
name: n.a.
surname: n.a.
function: n.a.
email: n.a.
telephone: n.a.
fax: n.a.

 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


Take a look of project's partnership.

# participants  country  role  EC contrib. [€] 
1    GOLDSMITHS' COLLEGE UK (LONDON) coordinator 149˙901.00


 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.


year authors and title journal last update
List of publications.
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:
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.

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