Abstract
Introduction
Dislocation of total hip replacements (THRs) remains a severe complication after total hip arthroplasty. However, the contribution of influencing factors, such as implant positioning and soft tissue tension, is still not well understood due to the multi-factorial nature of the dislocation process. In order to systematically evaluate influencing factors on THR stability, our novel approach is to extract the anatomical environment of the implant into a musculoskeletal model. Within a hardware-in-the-loop (HiL) simulation the model provides hip joint angles and forces for a physical setup consisting of a compliant support and a robot which accordingly moves and loads the real implant components [2]. The purpose of this work was to validate the HiL test system against experimental data derived from one patient.
Methods
The musculoskeletal model includes all segments of the right leg with a simplified trunk. Bone segments were reconstructed from a human computed tomography dataset. The segments were mutually linked in the multibody software SIMPACK (v8.9, Simpack AG, Gilching, Germany) by ideal joints starting from the ground-fixed foot. Furthermore, inertia properties were incorporated based on anthropometric data. Inverse dynamics was used to obtain muscle forces. Thus, optimization techniques were implemented to resolve the distribution problem of muscle forces whereas muscles were assumed to act along straight lines. For validation purposes the model was scaled to one patient with an instrumented THR [1]. Averaged kinematic measurements were used to obtain joint angles for a knee-bending motion. Then, the model was exported into real-time capable machine code and embedded into the HiL environment. Real implant components of a standard THR were attached to the endeffector of the robot and the compliant support. Finally, the HiL simulation was carried out simulating knee-bending. Experimentally measured hip joint forces from the patient [1] were used to validate the HiL simulation.
Results
According to the joint angles obtained a knee-bending motion was carried out during the HiL simulation (Fig. 1). Predicted components of the hip joint force were in-between the envelopes of measured in-vivo data with partial deviation of the y-component (Fig. 2). The force application by the robot agreed well with the force values provided by the model.
Discussion
Previous quasi-static mechanical setups for testing subluxation and dislocation of THRs neglected the impact of soft tissue structures on actual joint loading. Therefore, we combine the advantages of robot-based testing and numerical simulations within a HiL approach for dynamic analyses of THRs [2]. Thereby, validation is required to enhance the credibility of test results. The data presented demonstrate that the HiL test system with the embedded musculoskeletal model is capable of providing comparable THR loading as derived from in-vivo data. Certain deviations of the joint force's y-component will be the focus of up-coming model improvements. By considering dislocation-associated movements such as deep knee-bending, the influence of implant design and positioning on THR stability can be evaluated under reproducible, physiological-like conditions in subsequent studies.
