In this paper we present a constrained inverse kinematics algorithm for rea
l-time motion capture in virtual environments, that has its origins in the
simulation of multi-body systems. We apply this algorithm to an articulated
human skeletal model using an electromagnetic motion tracking system with
a small number of sensors to create avatar postures. The method offers effi
cient inverse kinematics computation and it is also generalised for the con
figurations of an articulated skeletal model. We investigate the possibilit
y of capturing fast gestures by analysing the convergence patterns of the a
lgorithm with the motion tracking sampling frequency for a range of actions
.