Jakub Krzysztof Grabski

The Recognition of Human by the Dynamic Determinants of the Gait with Use of ANN

In this paper human recognition method is based on dynamic parameters of the human gait. In the method the artificial neural network algorithm is employed. Some parameters of the gait are defined in order to describe and recognize characteristics of gait for each considered individual. In classical approach to human recognition, description of the gait pattern is based on sequence of images analysis and biometric parameters. In this paper we present method based on determining some dynamic characteristics of the gait, which together with other kinematic determinants should allow to describe the unique gait pattern for each individual. Necessary data were obtained from system of motion analysis BTS and force plates, commonly used in biomechanics. All considered gait parameters were calculated from data which were obtained for 15 persons with different characteristic of the gait. To implement the recognition process the back-propagation neural network algorithm was used. In the paper three configurations of the input data (only kinematic parameters from the BTS system, only dynamic parameters from the force plates and both types of parameters together) are investigated and compared.

Discussion about different cut-off values of conventional hamstring-to-quadriceps ratio used in hamstring injury prediction among professional male football players

Objective To measure the sensitivity and specificity of differences cut-off values for isokinetic Hcon/Qcon ratio in order to improve the capacity to evaluate (retrospectively) the injury of hamstring muscles in professional soccer screened with knee isokinetic tests. Design Retrospective study. Methods Medical and biomechanical data of professional football players playing for the same team for at least one season between 2010 and 2016 were analysed. Hamstring strain injury cases and the reports generated via isokinetic testing were investigated. Isokinetic concentric(con) hamstring(H) and quadriceps(Q) absolute strength in addition with Hcon/Qcon ratio were examined for the injured versus uninjured limbs among injured players, and for the injured and non-injured players. 2 x 2 contingency table was used for comparing variables: predicted injured or predicted uninjured with actual injured or actual uninjured. Sensitivity, specificity, accuracy, positive and negative predictive values, and positive and negative likelihood ratio were calculated for three different cut-off values (0.47 vs. 0.6 vs. 0.658) to compare the discriminative power of an isokinetic test, whilst examining the key value of Hcon/Qcon ratio which may indicate the highest level of ability to predispose a player to injury. McNemar’s chi2 test with Yates’s correction was used to determine agreement between the tests. PQStat software was used for all statistical analysis, and an alpha level of p <0.05 was used for all statistical comparisons. Results 340 isokinetic test reports on both limbs of 66 professional soccer players were analysed. Eleven players suffered hamstring injuries during the analysed period. None of these players sustained recurrence of hamstring injury. One player sustained hamstring strain injury on both legs, thus the total number of injuries was 12. Application of different cut-off values for Hcon/Qcon significantly affected the sensitivity and specificity of isokinetic test used as a tool for muscle injury detection. The use of 0.47 of Hcon/Qcon as a discriminate value resulted in significantly lower sensitivity when compared to 0.658 threshold (sensitivity of 16.7% vs. 91.7%, respectively; t = 6.125,p = 0.0133). Calculated values of specificity (when three different cut-off were applied) were also significantly different. Threshold of 0.6 of Hcon/Qcon resulted with significantly lower specificity compared to 0.47 value (specificity of 46.9% vs. 94.5%, respectively; t = 153.0,p<0.0001), and significantly higher specificity when compared to 0.658 (specificity of 46.9% vs. 24.1%, respectively; t = 229.0, p<0.0001). Conclusion The use of different cut-off values for Hcon/Qcon significantly affected the sensitivity and specificity of isokinetic testing. The interpretation of usefulness of isokinetic test as a screening tool in a group of male professional football players to predict hamstring injury occurrence within the next 12 months might be therefore significantly biased due to the different threshold values of Hcon/Qcon. Using one “normative” value as a cut-off (e.g. 0.47 or 0.60, or 0.658) to quantify soccer players (or not) to the group with a higher risk of knee injury might result in biased outcomes due to the natural strength asymmetry that is observed within the group of soccer players.

Analysis of Carreau fluid flow between corrugated plates

The paper deals with a problem of Carreau fluid flow between corrugated plates. A meshless numerical procedure for solving nonlinear governing equation is constructed using the Picard iteration method in combination with the method of fundamental solutions and the radial basis functions. The dimensionless average velocity and the product of friction factor and Reynolds number are calculated for different values of the fluid model and parameters of the considered region.

Gender recognition using artificial neural networks and data coming from force plates

The paper deals with a problem of automatic gender recognition based on parameters obtained from the force plates. The ground reaction force is recorded and some selected parameters of the curve are calculated. These parameters are used in this study as inputs to artificial neural network which should recognize if the individual is male or famale. The results of recognition are satisfactory and presented in the paper.

Laminar fluid flow and heat transfer in an internally corrugated tube by means of the method of fundamental solutions and radial basis functions

Abstract The paper shows application of the method of fundamental solutions in combination with the radial basis functions for analysis of fluid flow and heat transfer in an internally corrugated tube. Cross-section of such a tube is mathematically described by a cosine function and it can potentially represent a natural duct with internal corrugations, e.g. inside arteries. The boundary value problem is described by two partial differential equations (one for fluid flow problem and one for heat transfer problem) and appropriate boundary conditions. During solving this boundary value problem the average fluid velocity and average fluid temperature are calculated numerically. In the paper the Nusselt number and the product of friction factor and Reynolds number are presented for some selected geometrical parameters (the number and amplitude of corrugations). It is shown that for a given number of corrugations a minimal value of the product of friction factor and Reynolds number can be found. As it was expected the Nusselt number increases with increasing amplitude and number of corrugations.

Fluid flow and heat transfer of a power-law fluid in an internally finned tube with different fin lengths

In the paper an analysis of fluid flow and heat transfer of a power-law fluid in an internally finned tube with different fin length is conducted. Nonlinear momentum equation of a power-law fluid flow and nonlinear energy equation are solved using the Picard iteration method. Then on each iteration step the solution of inhomogeneous equation consists of two parts: the general solution and the particular solution. Firstly the particular solution is obtained by interpolation of the inhomogeneous term by means of the radial basis functions and monomials. Then the general solution is obtained using the method of fundamental solutions and by fulfilling boundary conditions.

On Different Methods for Calculating the Flight Height in the Vertical Countermovement Jump Analysis

Vertical countermovement jump is a very simple and common method for assessing the jumping ability of athletes. There are different techniques for measurements of the flight height, e.g. using motion capture systems or accelerometers. In this paper for estimating the flight height the measurements coming from the force plates are used. Furthermore different methods can be applied for calculating the flight height based on these measurements. In these paper four methods of calculating the flight height during the vertical countermovement jump based on the measurements from the force plates are compared (the flight time method, the take-off velocity method, the work-energy method and the center of jumper’s body vertical position method). In addition for two of these methods (the take-off velocity method and the center of jumper’s body vertical position method) the authors applied two different methods of numerical integration (the trapezoidal rule and based on the cubic spline interpolation).

Application of Artificial Neural Networks in the Human Identification Based on Thermal Image of Hands

The aim of this study was to check the possibility of identifying the persons based on the properties of thermal maps and a temperature distribution of a hand, obtained from a thermal image, with use of artificial neural networks. For this purpose, a series of thermographs of the right hand of eight people was taken, with a thermal imaging camera. The photos were taken under the same thermal conditions, but with different state of warming of hands. After processing the photos (determining the edges, characteristic hand points and areas of interest), the parameters characterizing the metacarpal temperature distribution were determined. Eight parameters were chosen, which were average temperatures of the areas of interest. These parameters were input data of neural networks in the learning and identification process. As it was shown in this study, these parameters were sufficient to clearly identify the persons. Neural networks, designed as multi-layered perceptron, after proper learning showed very high values of identification parameters, including high values of sensitivity and specificity, what proves the high quality of classification. Such identification is possible with the natural thermal state of the hand and if thermal images are not strongly disturbed, the artificial neural networks are very good tool to implement in persons identification process.

Comparison of Some Evolutionary Algorithms For Optimization of the Path Synthesis Problem

The paper presents comparison of the results obtained in a mechanism synthesis by means of some selected evolutionary algorithms. The optimization problem considered in the paper as an example is the dimensional synthesis of the path generating four-bar mechanism. In order to solve this problem, three different artificial intelligence algorithms are employed in this study.The paper presents comparison of the results obtained in a mechanism synthesis by means of some selected evolutionary algorithms. The optimization problem considered in the paper as an example is the dimensional synthesis of the path generating four-bar mechanism. In order to solve this problem, three different artificial intelligence algorithms are employed in this study.

Artificial neural networks in knee injury risk evaluation among professional football players

Lower limb injury risk assessment was proposed, based on isokinetic examination that is a part of standard athlete’s biomechanical evaluation performed mainly twice a year. Information about non-contact knee injury (or lack of the injury) sustained within twelve months after isokinetic test, confirmed in USG were verified. Three the most common types of football injuries were taken into consideration: anterior cruciate ligament (ACL) rupture, hamstring and quadriceps muscles injuries. 22 parameters, obtained from isokinetic tests were divided into 4 groups and used as input parameters of five feedforward artificial neural networks (ANNs). The 5th group consisted of all considered parameters. The networks were trained with the use of Levenberg-Marquardt backpropagation algorithm to return value close to 1 for the sets of parameters corresponding injury event and close to 0 for parameters with no injury recorded within 6 - 12 months after isokinetic test. Results of this study shows that ANN might be useful tools, which simplify process of simultaneous interpretation of many numerical parameters, but the most important factor that significantly influence the results is database used for ANN training.Lower limb injury risk assessment was proposed, based on isokinetic examination that is a part of standard athlete’s biomechanical evaluation performed mainly twice a year. Information about non-contact knee injury (or lack of the injury) sustained within twelve months after isokinetic test, confirmed in USG were verified. Three the most common types of football injuries were taken into consideration: anterior cruciate ligament (ACL) rupture, hamstring and quadriceps muscles injuries. 22 parameters, obtained from isokinetic tests were divided into 4 groups and used as input parameters of five feedforward artificial neural networks (ANNs). The 5th group consisted of all considered parameters. The networks were trained with the use of Levenberg-Marquardt backpropagation algorithm to return value close to 1 for the sets of parameters corresponding injury event and close to 0 for parameters with no injury recorded within 6 - 12 months after isokinetic test. Results of this study shows that ANN might be useful...