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A hybrid approach to 3D arm motion tracking

Department of Computing and Electronic Systems, University of Essex, Wivenhoe Park, Colchester CO4 3SQ, UK

Huosheng Hu

Department of Computing and Electronic Systems, University of Essex, Wivenhoe Park, Colchester CO4 3SQ, UK, hhu{at}essex.ac.uk

This paper presents a hybrid approach to 3D arm motion tracking for tele-rehabilitation applications. A particle filter (PF) algorithm is adopted in the proposed system to fuse data from inertial and visual sensors in a probabilistic manner. Multi-modal distributions of system states are propagated based on a 'factor sampling' technique. To avoid the problem of particle degeneracy in conventional PF algorithms, two strategies are adopted in our system, namely state-space pruning and an arm physical geometry constraint. Experimental results show that the proposed PF framework outperforms other fusion methods and tracking results are accurate in comparison to the ground truth provided by a commercial mark-based motion tracking system.

Key Words: human motion tracking • inertial sensor • particle filters • tele-rehabilitation • visual tracking.

Transactions of the Institute of Measurement and Control, Vol. 30, No. 3-4, 259-273 (2008)
DOI: 10.1177/0142331208090965


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