Software Training

Sensors, Interfaces, and Interactive Machine Learning for Music

Master motion and physiological sensors to program interactive sound and music systems
May 15 through Fri 17 May 2019,
10 a.m.- 5:30 p.m.
salle Nono





750 €

          Practical Information          


Upon completion of this training program, participants will have acquired the theoretical and practical notions for the conception and realization of interactive sound and music systems in Max, using a range of motion and physiological sensors as well as pattern-recognition systems.

Programming interfaces such as the  Arduino  or  R-IoT  will also be addressed.


Composers, musicians, performers, teachers, designers


Good understanding of digital signal processing;
Good understanding of programming in Max.


Assessment: Hands-on exercises throughout the course.
A certificate at the end of the program is given to each participant with the results of the exam.



MorningTheoretical background: Overview of different types of sensors, interfaces, and suppliers. The particular case of wireless sensors;
Hands-on exercises: use the programming environments Arduino and Energia.
AfternoonHands-on exercises : master the basics of programming in Arduino and Energia, first simple examples of coding, uploading code towards the Arduino and R-IoT interfaces.


MorningTheoretical background: introduction to Max, in particular to objects and libraries that can interface with Arduino and R-IoT and to automatic learning/recognition of patterns based on acquired data;
Hands-on exercises: make Max communicate with the Arduino and R-IoT interfaces.
AfternoonHands-on exercises: recuperate, process, route, and map the data acquired in a sonification system made in Max.


MorningHands-on exercises: create a sonification system: physiological capture (heart beats, breathing) via sensors connected to the R-IoT interface, recuperation of data and sonification in Max.
AfternoonTheoretical background: Technical description of examples of advanced use of motion capture and gesture recognition in a sonification project and performance art.