Inertial based hand position tracking for future applications in rehabilitation environments

This work is about the application of a wireless and miniaturized MEMS based Attitude and Heading Reference System for the estimation of hands position during standard rehabilitation exercises. The 3D orientation of the platform, computed on-board, along with the acceleration data, are collected by a computer. A specific algorithm has been developed in order to provide a reliable 3D position tracking of the hand without suffering from common error sources of MEMS sensors data processing, such as integration drift, inaccurate calibration procedures and finite integration times. This paper presents the setup, the developed algorithm and the preliminary results achieved with both a mechanical arm and a set of standard physical exercises performed by a human.