Multibody kinematics optimization (MKO) aims to reduce soft tissue artefact (STA) and is a key step in musculoskeletal modeling. The objective of this review was to identify the numerical methods, their validation and performance for the estimation of the human joint kinematics using MKO. Seventy-four papers were extracted from a systematized search in five databases and cross-referencing. Model-derived kinematics were obtained using either constrained optimization or Kalman filtering to minimize the difference between measured (i.e., by skin markers, electromagnetic or inertial sensors) and model-derived positions and/or orientations. While hinge, universal, and spherical joints prevail, advanced models (e.g., parallel and four-bar mechanisms, elastic joint) have been introduced, mainly for the knee and shoulder joints. Models and methods were evaluated using: (i) simulated data based, however, on oversimplified STA and joint models; (ii) reconstruction residual errors, ranging from 4 mm to 40 mm; (iii) sensitivity analyses which highlighted the effect (up to 36 deg and 12 mm) of model geometrical parameters, joint models, and computational methods; (iv) comparison with other approaches (i.e., single body kinematics optimization and nonoptimized kinematics); (v) repeatability studies that showed low intra- and inter-observer variability; and (vi) validation against ground-truth bone kinematics (with errors between 1 deg and 22 deg for tibiofemoral rotations and between 3 deg and 10 deg for glenohumeral rotations). Moreover, MKO was applied to various movements (e.g., walking, running, arm elevation). Additional validations, especially for the upper limb, should be undertaken and we recommend a more systematic approach for the evaluation of MKO. In addition, further model development, scaling, and personalization methods are required to better estimate the secondary degrees-of-freedom (DoF).

To reduce the effects of skin movement artefacts and apparent joint dislocations in the kinematics of whole body movement derived from marker locations, global optimisation procedures with a chain model have been developed. These procedures can also be used to reduce the number of markers when self-occlusions are hard to avoid. This paper assesses the kinematics precision of three marker sets: 16, 11 and 7 markers, for movements on high bar with straddled piked posture. A three-dimensional person-specific chain model was defined with 9 parameters and 12 degrees of freedom and an iterative procedure optimised the gymnast posture for each frame of the three marker sets. The time histories of joint angles obtained from the reduced marker sets were compared with those from the 16 marker set by means of a root mean square difference measure. Occlusions of medial markers fixed on the lower limb occurred when the legs were together and the pelvis markers disappeared primarily during the piked posture. Despite these occlusions, reconstruction was possible with 16, 11 and 7 markers. The time histories of joint angles were similar; the main differences were for the thigh mediolateral rotation and the knee flexion because the knee was close to full extension. When five markers were removed, the average angles difference was about 3 degrees . This difference increased to 9 degrees for the seven marker set. It is concluded that kinematics of sports movement can be reconstructed using a chain model and a global optimisation procedure for a reduced number of markers.