Software Training

Sensors, Interfaces, and Interactive Machine Learning for Music

Master Sensors to Program Interactive Sound and Music Systems
May 4 through Fri 7 May 2021,
10 a.m.- 5:30 p.m.
salle Nono





1050 €

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 using various types of sensors (infrared, light, movement, physiological), 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 programming in Max or have successfully completed the course Max Initiation.

Educational Resources and Techniques

Classroom equipped with computers with all the necessary software installed, headphones, and MIDI keyboards

Participants will be provided kits made up of a R-IoT card and two physiological sensors (breathing, heartbeat). The R-IoT module is included in the cost of the training (a 99€ value).
Class Format: training alternates between presentations, explanations on theory, studying examples to analyze, and hands-on exercises

Didactic Materials: video-projected presentations and PDF documents

Supervision and Assessment

Welcome the first day of training beginning at 9:45am

Attendance controlled: signature of an attendance sheet required every morning and afternoon
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

Training Period and Organization

24 hours of training. Tuesday-Friday, May 4-7, 2021. 10am-1pm/2:30pm-5:30pm

11 students maximum



MorningOverview 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


MorningRecuperation and processing of sensor data in Max (Arduino and R-Iots)
Filtering (average, median filter, low pass filter) and normalization
AfternoonImplementation of a mapping system
Direct use of sensor data with simples sound processes. Synthesis control, playback of sound files


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
AfternoonIntroduction to the MuBu library and Gesture follower.


MorningTheory: introduction to interactive "machine learning" with the Mubu for Max library allowing advanced applications for gesture and motion recognition. Presentation of examples of use in sonic and artistic projects (performance art)
AfternoonHands-on exercises: produce an example of a system with sensors connected to the R-OoT interface, learning, and recognition in Max with MuBu