MotionLab Sonify: A Framework for the Sonification of Human Motion Data

Abstract

Sonification of human movement offers a wide range of new kinds of information for supporting motor learning in sports and rehabilitation. Even though motor learning is dominated visually, auditory perception offers unique subtle temporal resolution as well as enormous integrative capacity - both are important features on perception of human movement patterns. But how to address the auditory system adequately? A sonification based on kinematic movement data can mediate structural features of movement via the auditory system, like polyrhythms of movement etc. And sonification of dynamic movement data makes muscle forces audible approximately. Here, a flexible framework for the sonification of human movement data is presented, capable of processing standard kinematic motion capture data as well as derived quantities such as force data. Force data are computed by inverse dynamics algorithms and can be used as input parameters for real time sonification. Simultaneous visualization is provided using OpenGL.