  This paper presents a novel online capable method for simultaneous estimation
of human motion in terms of segment orientations and positions along with
sensor-to-segment calibration parameters from inertial sensors attached to the
body. In order to solve this ill-posed estimation problem, state-of-the-art
motion, measurement and biomechanical models are combined with new stochastic
equations and priors. These are based on the kinematics of multi-body systems,
anatomical and body shape information, as well as, parameter properties for
regularisation. This leads to a constrained weighted least squares problem that
is solved in a sliding window fashion. Magnetometer information is currently
only used for initialisation, while the estimation itself works without
magnetometers. The method was tested on simulated, as well as, on real data,
captured from a lower body configuration.
