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In this study the effect of transcutaneous (tSCS) and epidural electrical spinal cord stimulation (EES) to facilitate volitional movements, balance, and non-motor functions was consecutively tested in two subjects with motor complete spinal cord injury (SCI). We hypothesized that tSCS and EES have different but complimentary effects on restoration after SCI. In both subjects tSCS demonstrated minimal improvement in volitional movements critical to initiate tSCS-enabled rehabilitation. Compared to tSCS, following EES demonstrated immediate restoration of volitional movements, while tSCS was more effective in improving balance. Continuous improvement in non-motor functions was found during tSCS-enabled and then EES-enabled rehabilitation. These results show significant difference in effect of tSCS and EES on recovery of neurologic functions and demonstrate advantages of consecutive tSCS and EES therapy of SCI. Proposed approach will help to select responsive to neuromodulation subjects and early initiate therapy, particularly for motor complete SCI with minimal effect from conventional rehabilitation.

Prosthetic reconstructions provide anatomical reconstruction to replace bones and joints. However, these operations have a high number of short- and long-term complications. One of the main problems in surgery is that the implant remains in the body after the operation. The solution to this problem is to use biomaterial for the implant, but biomaterial does not have the required strength characteristics. The implant must also have a mesh-like structure so that the bone can grow into the implant. The additive manufacturing process is ideal for the production of such a structure. The study deals with the correlation between different prosthetic structures, namely, the relationship between geometry, mechanical properties and biological additivity. The main challenge is to design an endoprosthesis that will mimic the geometric structure of bone and also meet the conditions of strength, hardness and stiffness. In order to match the above factors, it is necessary to develop appropriate algorithms. The main objective of this study is to augment the algorithm to ensure minimum structural weight without changing the strength characteristics of the lattice endoprosthesis of long bones. The iterative augmentation process of the algorithm was implemented by removing low-loaded ribs. A low-loaded rib is a rib with a maximum stress that is less than the threshold stress. Values within the range (10, 13, 15, 16, 17, 18, 19 and 20 MPa) were taken as the threshold stress. The supplement to the algorithm was applied to the initial structure and the designed structure at threshold stresses σf = 10, 13, 15, 16, 17, 18, 19 and 20 MPa. A Pareto diagram for maximum stress and the number of ribs is plotted for all cases of the design: original, engineered and lightened structures. The most optimal was the designed “lightweight” structure under the condition σf = 17 MPa. The maximum stress was 147.48 MPa, and the number of ribs was 741. Specimens were manufactured using additive manufacturing and then tested for four-point bending.

The development of additive manufacturing technology leads to new concepts for design implants and prostheses. The necessity of such approaches is fueled by patient-oriented medicine. Such a concept involves a new way of understanding material and includes complex structural geometry, lattice constructions, and metamaterials. This leads to new design concepts. In the article, the structural design method is presented. The general approach is based on the separation of the micro- and macro-mechanical parameters. For this purpose, the investigated region as a complex of the basic cells was considered. Each basic cell can be described by a parameters vector. An initializing vector was introduced to control the changes in the parameters vector. Changing the parameters vector according to the stress-strain state and the initializing vector leads to changes in the basic cells and consequently to changes in the microarchitecture. A medium with a spheroidal pore was considered as a basic cell. Porosity and ellipticity were used for the parameters vector. The initializing vector was initialized and depended on maximum von Mises stress. A sample was designed according to the proposed method. Then, solid and structurally designed samples were produced by additive manufacturing technology. The samples were scanned by computer tomography and then tested by structural loads. The results and analyses were presented.

Nowadays, the use of a digital prototype in numerical modeling is one of the main approaches to calculating the elements of an inhomogeneous structure under the influence of external forces. The article considers a finite element analysis method based on computed tomography data. The calculations used a three-dimensional isoparametric finite element of a continuous medium developed by the authors with a linear approximation, based on weighted integration of the local stiffness matrix. The purpose of this study is to describe a general algorithm for constructing a numerical model that allows static calculation of objects with a porous structure according to its computed tomography data. Numerical modeling was carried out using kinematic boundary conditions. To evaluate the results obtained, computational and postprocessor grids were introduced. The qualitative assessment of the modeling data was based on the normalized error. Three-point bending of bone specimens of the pig forelimbs was considered as a model problem. The numerical simulation results were compared with the data obtained from a physical experiment. The relative error ranged from 3 to 15%, and the crack location, determined by the physical experiment, corresponded to the area where the ultimate strength values were exceeded, determined by numerical modeling. The results obtained reflect not only the effectiveness of the proposed approach, but also the agreement with experimental data. This method turned out to be relatively non-resource-intensive and time-efficient.

The article describes the solution to the problem of stabilizing a nonlinear system using machine learning methods. Neural networks are one of the promising directions in this area. The article describes a model of spiking neural network, which differs from previous generations of networks by its similarity to biological neurons. A pendulum on an elastic foundation was chosen as a dynamic system for the study. The input layer of the neural network is the so-called sensory neuron, and information about the deviation of the pendulum from the equilibrium position was received on it. The Leaky Integrate-and-Fire model of the spiking neural network was used. The article shows the process of stabilization of a pendulum on an elastic foundation. The closed system was built and a method for a numerical solution was implemented. Two configurations of control functions have been considered. It is shown that the time required to bring the system into a steady equilibrium state depends on the choice of the control function.

The volumetric distribution of bone tissue can be analysed in terms of orthotropic medium. In this case, it is important to define the orthotropic directions. Nowadays, computed tomography methods allow getting such information. The method for automation such analysis is presented. Firstly, the threshold of binarization should be calculated. Then the sample should be meshed and each element should be binarized. After that fabric tensor, eigenvalues, eigenvectors and fractional anisotropy can be calculated for each element. Statistical methods were used to analyse the field of the obtained data. Described methods were used on a bone sample. It was shown that for a sample the fabric tensor is constant and the fractional anisotropy is close to zero. That’s means that the medium in the sample was isotropic.

In the paper, a method for the direct image-based creation of the finite element model from images is presented. Image information is taken into account during the calculation of the element stiffness matrix. In this case, material heterogeneity can be included directly in the finite element model. For this purpose, the hypothesis about the correlation between pixel values and elastic properties was used. Four nodes plane element was built. The element can be used with the quantitative phase or scanning electron images and computed tomography data. Simulation for bone data performed. The influence of pixel on the error estimate was studied. The method to parallelize the calculation of the stiffness matrix is presented. As an example, a slice of bone was used in the calculation. Results for average stress distribution for the origin and improved mesh are presented.