RESUMO
Osseointegrated transfemoral prostheses experience aseptic complications with an incidence between 3% and 30%. The main aseptic risks are implant loosening, adverse bone remodeling, and post-operative periprosthetic fractures. Implant loosening can either be due to a lack of initial (primary) stability of the implant, which hinders bone ingrowth and therefore prevents secondary stability, or, in the long-term, to the progressive resorption of the periprosthetic bone. Post-operative periprosthetic fractures are most often caused by stress concentrations. A method to simultaneously evaluate the primary stability and the load transfer is currently missing. Furthermore, the measurement errors are seldom reported in the literature. In this study a method to reliably quantify the bone implant interaction of osseointegrated transfemoral prostheses in terms of primary stability and load transfer was developed, and its precision was quantified. Micromotions between the prosthesis and the host bone and the strains on the cortical bone were measured on five human cadaveric femurs with a typical commercial osseointegrated implant. To detect the primary stability of the implant and the load transfer, cyclic loads were applied, simulating the peak load during gait. Digital Image Correlation was used to measure displacements and bone strains simultaneously throughout the test. Permanent migrations and inducible micromotions were measured (three translations and three rotations), while, on the same specimen, the full-field strain distribution on the bone surface was measured. The repeatability tests showed that the devised method had an intra-specimen variability smaller than 6 µm for the translation, 0.02 degrees for the rotations, and smaller than 60 microstrain for the strain distribution. The inter-specimen variability was larger than the intra-specimen variability due to the natural differences between femurs. Altogether, the measurement uncertainties (intrinsic measurement errors, intra-specimen repeatability and inter-specimen variability) were smaller than critical levels of biomarkers for adverse remodelling and aseptic loosening, thus allowing to discriminate between stable and unstable implants, and to detect critical strain magnitudes in the host bone. In conclusion, this work showed that it is possible to measure the primary stability and the load transfer of an osseointegrated transfemoral prosthesis in a reliable way using a combination of mechanical testing and DIC.
RESUMO
The amputee population according to the World-Health-Organization is about 40 million. However, there is a high abandon rate of socket prostheses for the lower limb (25%-57%). The direct connection between the external prosthesis and the patient's bone makes osseointegrated prostheses for transfemoral amputees advantageous (e.g., improvement of the motor control) compared to socket prostheses, which are currently the gold standard. However, similarly to other uncemented prostheses, the osseointegrated ones are at risk of aseptic loosening and adverse bone remodelling caused by stress-shielding. The preclinical assessment of these prostheses has already been evaluated using different methods which did not provide unanimous and comparable evidence. To compare data from different investigations, a clear and detailed overview of the methods used to assess the performance is necessary. In this review 17 studies investigating the primary stability, stress shielding and stress concentration of osseointegrated transfemoral prostheses are examined. Primary stability consists in the biomechanical stability upon implant insertion. Primary stability is assessed measuring extraction force (either with a pull-out or a push-out test) and micromotion at the interface between the implant and the host bone with LVDT (in vitro test) or numerical models. Stress-shielding causes adaptive changes in the bone density around metal implants, and thus in the bone strength and stiffness. Stress-shielding is assessed with strain gauges or numerical models measuring the load transfer and the strain distribution on the surface of the femur, and between the implant and the bone respectively. Stress concentration can lead to the formation of cracks inside the bone, resulting in fractures. The stress concentration is assessed measuring the load transfer and the strain energy density at the interface between the implant and the bone, using numerical models. As a result, a global view and consensus about the methods are missing from all these tests. Indeed, different setup and loading scenario were used in the in vitro test, while different model parameters (e.g., bone properties) were used in the numerical models. Once the preclinical assessment method is established, it would be important to define thresholds and acceptance criteria for each of the possible failure scenarios investigated.
RESUMO
This paper reports the architecture of a low-cost smart crutches system for mobile health applications. The prototype is based on a set of sensorized crutches connected to a custom Android application. Crutches were instrumented with a 6-axis inertial measurement unit, a uniaxial load cell, WiFi connectivity, and a microcontroller for data collection and processing. Crutch orientation and applied force were calibrated with a motion capture system and a force platform. Data are processed and visualized in real-time on the Android smartphone and are stored on the local memory for further offline analysis. The prototype's architecture is reported along with the post-calibration accuracy for estimating crutch orientation (5° RMSE in dynamic conditions) and applied force (10 N RMSE). The system is a mobile-health platform enabling the design and development of real-time biofeedback applications and continuity of care scenarios, such as telemonitoring and telerehabilitation.
