An In-Silico Corrosion Model for Biomedical Applications for Coupling With In-Vitro Biocompatibility Tests for Estimation of Long-Term Effects.

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.

Smart platform for the analysis of cupula deformation caused by otoconia presence within SCCs.

In this paper, we first briefly describe the mechanical model of cupula deformation with the appropriate analytical solution. Then, we present the numerical solution of the same problem and compare it with the analytical one. Besides, we provide another numerical solution based on the Finite Element Method procedure, in an effort to encompass a more realistic approach to the problem such as considering the real geometry of the SCCs and the obstruction of the fluid flow during head movement due to the presence of otoconia. As a result, we obtain fifty solutions for a head rotation angle in a range from 0° to 120°, taking into account that such a manoeuvre lasts exactly 3 seconds. In the end, we present a mobile client-server application for visualising the finite element solutions in a way that is convenient for the clinical practice.

Leg stiffness adjustment during hopping at different intensities and frequencies.

Understanding leg and joint stiffness adjustment during maximum hopping may provide important information for developing more effective training methods. It has been reported that ankle stiffness has major influence on stable spring-mass dynamics during submaximal hopping, and that knee stiffness is a major determinant for hopping performance during maximal hopping task. Furthermore, there are no reports on how the height of the previous hop could affect overall stiffness modulation of the subsequent maximum one. The purpose of the present study was to determine whether and how the jump height of the previous hop affects leg and joint stiffness for subsequent maximum hop. Ten participants completed trials in which they repeatedly hopped as high as possible (MX task) and trials in which they were instructed to perform several maximum hops with 3 preferred (optimal) height hops between each of them (P3MX task). Both hopping tasks were performed at 2.2 Hz hopping frequency and at the participant's preferred (freely chosen) frequency as well. By comparing results of those hopping tasks, we found that ankle stiffness at 2.2 Hz ( p = 0.041) and knee stiffness at preferred frequency ( p = 0.045) was significantly greater for MX versus P3MX tasks. Leg stiffness for 2.2 Hz hopping is greater than for the preferred frequency. Ankle stiffness is greater for 2.2 Hz than for preferred frequencies; opposite stands for knee stiffness. The results of this study suggest that preparatory hop height can be considered as an important factor for modulation of maximum hop.

Noninvasive determination of knee cartilage deformation during jumping.

The purpose of this investigation was to use a combination of image processing, force measurements and finite element modeling to calculate deformation of the knee cartilage during jumping. Professional athletes performed jumps analyzed using a force plate and high-speed video camera system. Image processing was performed on each frame of video using a color recognition algorithm. A simplified mass-spring-damper model was utilized for determination of global force and moment on the knee. Custom software for fitting the coupling characteristics was created. Simulated results were used as input data for the finite element calculation of cartilage deformation in the athlete's knee. Computer simulation data was compared with the average experimental ground reaction forces. The results show the three-dimensional mechanical deformation distribution inside the cartilage volume. A combination of the image recognition technology, force plate measurements and the finite element cartilage deformation in the knee may be used in the future as an effective noninvasive tool for prediction of injury during jumping. Key pointsEven there are many existing mathematical models of force distribution during running or jumping (Liu et al, 1998), to our knowledge there is no interdisciplinary approach where imaging processing, finite element modeling and experimental force plate system are employed.The aim is to explore noninvasive deformation in the knee cartilage during athlete's jumping on the force plate.An original image algorithms and software were developed as well as complex mathematical models using high-performance computational power of finite element modeling together with one-dimensional dynamics model.The initial results showed cartilage deformation in the knee and future research will be focused on the methodology and more precisely determination of the stress and strain distribution in the knee cartilage during training phase of sportsman.