A screening method to analyse the sensitivity of a lower limb multibody kinematic model.

The study presents a screening method used to identify the influential parameters of a lower limb model including ligaments, at low numerical cost. Concerning multibody kinematics optimisation, the ligament parameters (isometric length) were found the most influential ones in a previous study. The screening method tested if they remain influential with minimised length variations. The most important parameters for tibiofemoral kinematics were the skin markers, segment lengths and joint parameters, including two ligaments. This was confirmed by a quantitative sensitivity analysis. The screening method has the potential to be used as a stand-alone procedure for a sensitivity analysis.

Contribution of passive actions to the lower limb joint moments and powers during gait: A comparison of models.

The lower limb passive actions representing the actions of all the passive periarticular structures have been shown to have a significant contribution to the power generation and absorption during gait. However, the respective magnitude of its different components was not established, although models of ligament moment were implemented in some musculoskeletal models. These ligament moments have shown to have an influence on the musculo-tendon forces and contact forces but the models used were never specifically evaluated, that is, compared to the passive and net joint moments. Two models of passive joint moments and three models of ligament moments were selected from the literature. Ten subjects (23-29 years old, 79.8 ± 9.5 kg, 1.85 ± 0.06 m) participated in the study. Each subject performed three gait cycles in a gait laboratory to acquire the kinematics and ground reaction forces and to compute the ligament, passive and net moments of the right lower limb joints. The contributions of the passive joint moments to the net joint moments were in accordance with the literature, although time shifts appeared for peaks in the hip and knee powers. Two of the models of ligament moments seemed, in fact, to represent the passive joint moments as their contributions were very similar while the third model of ligament moments seemed to represent only penalty-based joint limits. As a conclusion, this study showed that the models of ligament moments existing in the literature do not seem reliable. This study also demonstrated that the use of non-subject-specific models of the passive joint moments could be a valid approach for healthy subjects.

Stiffness of a wobbling mass models analysed by a smooth orthogonal decomposition of the skin movement relative to the underlying bone.

The so-called soft tissue artefacts and wobbling masses have both been widely studied in biomechanics, however most of the time separately, from either a kinematics or a dynamics point of view. As such, the estimation of the stiffness of the springs connecting the wobbling masses to the rigid-body model of the lower limb, based on the in vivo displacements of the skin relative to the underling bone, has not been performed yet. For this estimation, the displacements of the skin markers in the bone-embedded coordinate systems are viewed as a proxy for the wobbling mass movement. The present study applied a structural vibration analysis method called smooth orthogonal decomposition to estimate this stiffness from retrospective simultaneous measurements of skin and intra-cortical pin markers during running, walking, cutting and hopping. For the translations about the three axes of the bone-embedded coordinate systems, the estimated stiffness coefficients (i.e. between 2.3kN/m and 55.5kN/m) as well as the corresponding forces representing the connection between bone and skin (i.e. up to 400N) and corresponding frequencies (i.e. in the band 10-30Hz) were in agreement with the literature. Consistently with the STA descriptions, the estimated stiffness coefficients were found subject- and task-specific.

Validation of a multi-body optimization with knee kinematic models including ligament constraints.

Motion analysis aims at evaluating the joint kinematics but the relative movement between the bones and the skin markers, known as soft tissue artifact (STA), introduces large errors. Multi-body optimization (MBO) methods were proposed to compensate for the STA. However, the validation of the MBO methods using no or simple kinematic constraints (e.g., spherical joint) demonstrated inaccurate in vivo kinematics. Anatomical constraints were introduced in MBO methods and various ligament constraints were proposed in the literature. The validation of these methods has not been performed yet. The objective of this study was to validate, against in vivo knee joint kinematics measured by intra-cortical pins on three subjects, the model-based kinematics obtained by MBO methods using three different types of ligament constraints. The MBO method introducing minimized or prescribed ligament length variations showed some improvements in the estimation of knee kinematics when compared to no kinematic constraints, to degree-of-freedom (DoF) coupling curves, and to null ligament length variations. However, the improvements were marginal when compared to spherical constraints. The errors obtained by minimized and prescribed ligament length variations were below 2.5° and 4.1mm for the joint angles and displacements while the errors obtained with spherical joint constraints were below 2.2° and 3.1mm. These errors are generally lower than the errors previously reported in the literature. As a conclusion, this study presented encouraging results for the compensation of the STA by MBO and for the introduction of anatomical constraints in MBO. Personalization of the geometry should be considered for further improvements.