The release of metal particles and ions due to wear and corrosion is one of the main underlying reasons for the long-term complications of implantable metallic implants. The rather short-term focus of the established in-vitro biocompatibility tests cannot take into account such effects. Corrosion behavior of metallic implants mostly investigated in in-vitro body-like environments for long time periods and their coupling with long-term in-vitro experiments are not practical. Mathematical modeling and modeling the corrosion mechanisms of metals and alloys is receiving a considerable attention to make predictions in particular for long term applications by decreasing the required experimental duration. By using such in-silico approaches, the corrosion conditions for later stages can be mimicked immediately in in-vitro experiments. For this end, we have developed a mathematical model for multi-pit corrosion based on Cellular Automata (CA). The model consists of two sub-models, corrosion initialization and corrosion progression, each driven by a set of rules. The model takes into account several environmental factors (pH, temperature, potential difference, etc.), as well as stochastic component, present in phenomena such as corrosion. The selection of NiTi was based on the risk of Ni release from the implant surface as it leads to immune reactions. We have also performed experiments with Nickel Titanium (NiTi) shape memory alloys. The images both from simulation and experiments can be analyzed using a set of statistical methods, also investigated in this paper (mean corrosion, standard deviation, entropy etc.). For more widespread implementation, both simulation model, as well as analysis of output images are implemented as a web tool. Described methodology could be applied to any metal provided that the parameters for the model are available. Such tool can help biomedical researchers to test their new metallic implant systems at different time points with respect to ion release and corrosion and couple the obtained information directly with in-vitro tests.
In this study we modeled a patient specific 3D knee after anterior cruicate
ligament (ACL) reconstruction. The purpose of the ACL reconstruction is to
achieve stability in the entire range of motion of the knee and the
establishment of the normal gait pattern. We present a new reconstruction
technique that generates patient-specific 3D knee models from patient?s
magnetic resonant images (MRIs). The motion of the ACL reconstruction
patients is measured by OptiTrack system with six infrared cameras. Finite
element model of bones, cartilage and meniscus is used for determination
stress and strain distribution at different body postures during gait
analysis. It was observed that the maximum effective von Mises stress
distribution up to 8 MPa occurred during 30% of the gait cycle on the
meniscus. The biomechanical model of the knee joint during gait analysis can
provide insight into the underlying mechanisms of knee function after ACL
reconstruction. [Projekat Ministarstva nauke Republike Srbije, br. III-41007,
i br. OI-174028]
In tennis, the complex serving motions produce high mechanical stresses on player's musculoskeletal, tendon and ligament joints. In this paper, different cognitive methods have been integrated in order to non-invasively assess the knee's bone and cartilage resistance at the maximum power tennis serve. The proposed methodology is based on the creation of patientspecific biomechanical model, as well as on the tracking the knee's kinematics, ground force measurement, inverse dynamics modelling and analysis of the knee using the Finite Element Method with aim to assess the knee resistance of a tennis player, considering acute deformations and potential injuries. The main objective of this paper is development of the optimised computational technology and creation of practical diagnostic tool for non-invasive assessment of the knee function during specific moves and motions in tennis. It is expected that this approach can provide prediction and injury prevention in training and competitive tennis to a significant extent.
The speed-accuracy trade-off of fast movements acts inversely and as such is known as the Fitts's law. The aim of this study is to determine how instep kick (IK) speed grading instructions affect the instep kick speed and accuracy. The primary hypothesis assumes that a complex motor task such as IK has an inverse relation between speed and accuracy, and the secondary hypothesis assumes that the applied speed grading instructions are sensitive. The research involved 13 male players, the average age of 15 years (±1.6). The experimental protocol included the execution of IK at five different speeds, determined by verbal instructions to respondents. For assessment of kicking accuracy, we observed the following dependent variables: mean radial error (MRE), bivariate variable error (BVE), and centroid radial error (CRE). Comparative analysis has shown that higher accuracy (reduced MRE) and kicking consistency (reduced BVE) are achieved under lower kicking speeds, but these effects were not achieved in regard to CRE. Subsequent analyses have shown that MRE has a tendency towards a significant difference between the slowest and fastest kicks (p=0.068-0.075), while in the case of BVE it has been found that there are differences between the slowest and all other speed levels (p≤0.05). The main findings of this study have indicated a partial existence (two of three variables) of an inverse relationship between speed and accuracy in complex motor tasks such as IK (multi-joint and discrete motion).
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