The reconstruction of skeletal movement: the soft tissue artefact issue

In 3D human movement analysis performed using stereophotogrammetric systems and skin markers, bone pose can only be estimated in an indirect fashion. During a movement, soft tissue deformations make the markers move with respect to the underlying bone generating soft tissue artefact (STA). STA has devastating effects on bone pose estimation and its compensation remains an open question. The aim of this PhD thesis was to contribute to the solution of this crucial issue. Modelling STA using measurable trial-specific variables is a fundamental prerequisite for its removal from marker trajectories. Two STA model architectures are proposed. Initially, a thigh marker-level artefact model is presented. STA was modelled as a linear combination of joint angles involved in the movement. This model was calibrated using ex-vivo and in-vivo STA invasive measures. The considerable number of model parameters led to defining STA approximations. Three definitions were proposed to represent STA as a series of modes: individual marker displacements, marker-cluster geometrical transformations (MCGT), and skin envelope shape variations. Modes were selected using two criteria: one based on modal energy and another on the selection of modes chosen a priori. The MCGT allows to select either rigid or non-rigid STA components. It was also empirically demonstrated that only the rigid component affects joint kinematics, regardless of the non-rigid amplitude. Therefore, a model of thigh and shank STA rigid component at cluster-level was then defined. An acceptable trade-off between STA compensation effectiveness and number of parameters can be obtained, improving joint kinematics accuracy. The obtained results lead to two main potential applications: the proposed models can generate realistic STAs for simulation purposes to compare different skeletal kinematics estimators; and, more importantly, focusing only on the STA rigid component, the model attains a satisfactory STA reconstruction with less parameters, facilitating its incorporation in an pose estimator