Development of musculoskeletal models for the design and the pre-clinical validation of hip resurfacing prosthesis

Background. The surgical treatment of dysfunctional hips is a severe condition for the patient and a costly therapy for the public health. Hip resurfacing techniques seem to hold the promise of various advantages over traditional THR, with particular attention to young and active patients. Although the lesson provided in the past by many branches of engineering is that success in designing competitive products can be achieved only by predicting the possible scenario of failure, to date the understanding of the implant quality is poorly pre-clinically addressed. Thus revision is the only delayed and reliable end point for assessment. The aim of the present work was to model the musculoskeletal system so as to develop a protocol for predicting failure of hip resurfacing prosthesis. Methods. Preliminary studies validated the technique for the generation of subject specific finite element (FE) models of long bones from Computed Thomography data. The proposed protocol consisted in the numerical analysis of the prosthesis biomechanics by deterministic and statistic studies so as to assess the risk of biomechanical failure on the different operative conditions the implant might face in a population of interest during various activities of daily living. Physiological conditions were defined including the variability of the anatomy, bone densitometry, surgery uncertainties and published boundary conditions at the hip. The protocol was tested by analysing a successful design on the market and a new prototype of a resurfacing prosthesis. Results. The intrinsic accuracy of models on bone stress predictions (RMSE < 10%) was aligned to the current state of the art in this field. The accuracy of prediction on the bone-prosthesis contact mechanics was also excellent (< 0.001 mm). The sensitivity of models prediction to uncertainties on modelling parameter was found below 8.4%. The analysis of the successful design resulted in a very good agreement with published retrospective studies. The geometry optimisation of the new prototype lead to a final design with a low risk of failure. The statistical analysis confirmed the minimal risk of the optimised design over the entire population of interest. The performances of the optimised design showed a significant improvement with respect to the first prototype (+35%). Limitations. On the authors opinion the major limitation of this study is on boundary conditions. The muscular forces and the hip joint reaction were derived from the few data available in the literature, which can be considered significant but hardly representative of the entire variability of boundary conditions the implant might face over the patients population. This moved the focus of the research on modelling the musculoskeletal system; the ongoing activity is to develop subject-specific musculoskeletal models of the lower limb from medical images. Conclusions. The developed protocol was able to accurately predict known clinical outcomes when applied to a well-established device and, to support the design optimisation phase providing important information on critical characteristics of the patients when applied to a new prosthesis. The presented approach does have a relevant generality that would allow the extension of the protocol to a large set of orthopaedic scenarios with minor changes. Hence, a failure mode analysis criterion can be considered a suitable tool in developing new orthopaedic devices.

Biomechanical modelling of human knee during living activities

The knee joint is a key structure of the human locomotor system. The knowledge of how each single anatomical structure of the knee contributes to determine the physiological function of the knee, is of fundamental importance for the development of new prostheses and novel clinical, surgical, and rehabilitative procedures. In this context, a modelling approach is necessary to estimate the biomechanic function of each anatomical structure during daily living activities. The main aim of this study was to obtain a subject-specific model of the knee joint of a selected healthy subject. In particular, 3D models of the cruciate ligaments and of the tibio-femoral articular contact were proposed and developed using accurate bony geometries and kinematics reliably recorded by means of nuclear magnetic resonance and 3D video-fluoroscopy from the selected subject. Regarding the model of the cruciate ligaments, each ligament was modelled with 25 linear-elastic elements paying particular attention to the anatomical twisting of the fibres. The devised model was as subject-specific as possible. The geometrical parameters were directly estimated from the experimental measurements, whereas the only mechanical parameter of the model, the elastic modulus, had to be considered from the literature because of the invasiveness of the needed measurements. Thus, the developed model was employed for simulations of stability tests and during living activities. Physiologically meaningful results were always obtained. Nevertheless, the lack of subject-specific mechanical characterization induced to design and partially develop a novel experimental method to characterize the mechanics of the human cruciate ligaments in living healthy subjects. Moreover, using the same subject-specific data, the tibio-femoral articular interaction was modelled investigating the location of the contact point during the execution of daily motor tasks and the contact area at the full extension with and without the whole body weight of the subject. Two different approaches were implemented and their efficiency was evaluated. Thus, pros and cons of each approach were discussed in order to suggest future improvements of this methodologies. The final results of this study will contribute to produce useful methodologies for the investigation of the in-vivo function and pathology of the knee joint during the execution of daily living activities. Thus, the developed methodologies will be useful tools for the development of new prostheses, tools and procedures both in research field and in diagnostic, surgical and rehabilitative fields.

Assessment of Daily Life Mobility Levels using Wearable Inertial Sensors and Minimun Measured Input Models

Tracking activities during daily life and assessing movement parameters is essential for complementing the information gathered in confined environments such as clinical and physical activity laboratories for the assessment of mobility. Inertial measurement units (IMUs) are used as to monitor the motion of human movement for prolonged periods of time and without space limitations. The focus in this study was to provide a robust, low-cost and an unobtrusive solution for evaluating human motion using a single IMU. First part of the study focused on monitoring and classification of the daily life activities. A simple method that analyses the variations in signal was developed to distinguish two types of activity intervals: active and inactive. Neural classifier was used to classify active intervals; the angle with respect to gravity was used to classify inactive intervals. Second part of the study focused on extraction of gait parameters using a single inertial measurement unit (IMU) attached to the pelvis. Two complementary methods were proposed for gait parameters estimation. First method was a wavelet based method developed for the estimation of gait events. Second method was developed for estimating step and stride length during level walking using the estimations of the previous method. A special integration algorithm was extended to operate on each gait cycle using a specially designed Kalman filter. The developed methods were also applied on various scenarios. Activity monitoring method was used in a PRIN’07 project to assess the mobility levels of individuals living in a urban area. The same method was applied on volleyball players to analyze the fitness levels of them by monitoring their daily life activities. The methods proposed in these studies provided a simple, unobtrusive and low-cost solution for monitoring and assessing activities outside of controlled environments.