PRINCIPLES OF ADEQUACY CRITERIA FORMULATION IN HUMAN MOTION ANALYSIS

Introduction. Number of parameters of an anthropomorphic model (AM), which simulates real human motion, can achieve the value of one hundred and even more than that. This makes obvious the necessity of adequacy criteria formulation. Optimal value of such criteria should indicate structural and parametric adjustment of AM to certain real human motion. Modelling of human motion with employment of mechanical-mathematical apparatus of system of body motion equations implies a significant number of problem parameters [1] required for description of the structure, and components and kinematics of motion as well. Choice of these parameters values seriously depends on what experimental data is available. METHODS AND RESULTS: The base of computer model consists in a system of differential-algebraic equations of motion of a ramified kinematics chain with nonstationary constraints. In particular, as constraint equations there can serve generalized coordinates behaviour functions, obtained through video-registration data processing. Such approach allows to determine main dynamic values, including generalized forces. However, measurement errors lead to significant errors in assessed values of inter-element forces and moments and especially values of external with respect to AM ground reaction and total moment of external forces in support phase of motion. Variation of AM elements parameters, positions of joints, parameters of trajectories smoothing allows to obtain an averaged assessment of external forces values. In the report there is suggested a new approach to structural an parametrical adjustment of AM. Presence of non-stationary constraint equations allows to use some of experimental data for such constraints. For example, ground reaction force and/or external moment can be available or equal to zero during the flight phase. One of investigation result is that there have been analyzed grand circles on the horizontal bar with a following jump off the bar and four backward somersaults performed in a grouped position. The number of AM elements is widely varied. There has been investigated influence of possible errors in determination of visco-elastic properties of the bar on the analysis results for different processing procedures. CONCLUSION: The suggested approach to iterational parametric adjustment of AM on the basis of employing of constraint equations allows for complete matching of model motion characteristics with most important experimental data. Less important data are estimated in average, which corresponds to traditional structural- parametric adjustment of AM. REFERENCES: 1. Zinkovsky A.V., Sholuha V.A., Ivanov A.A. Mathematical Modelling and Computer Simulation of Biomechanical Systems, WSP, Singapore, 1997. 216p

COMPUTER SYNTHESIS AND OPTIMIZATION OF JUMPING MOTIONS VIA NONSTATIONARY CONSTRAINTS

Introduction: This report considers the results of the authors’ research on the goal-oriented computer synthesis of human motions in support and non-support phases. The main attention is paid to the synthesis of the pushing phases. In particular, an analysis is made of the results of a sequential optimization of running long jumps and acrobatic jumps. The computer modeling of complex coordination motions is based on the development of an adequate anthropomorphic model. Methods and Results: Most effective in the developed modeling system proved to be the employment of differentiated non-stationary holonomic and nonholonomic constraints equations in order to model goal-oriented motions [1]. For descriptions of additional non-stationary items in constraints equations we used parametrically controlled smooth approximation functions which allowed us to synthesize the desired motion trajectories, ground reaction force and kinetic moment increment. Due to the non-stationary nature of constraints equations, any experimental data on kinematics and/or the dynamics of real motion can fulfill their function. For the analysis of modeling results we consider estimates of interelement control motions distribution in the support phase of jumping motion. A number of anthropomorphic model (AM) elements can change with respect to the level of AM adequacy to real human motion. For example, we used a 15-element AM for modeling the support and flying phases of the running long jump. Analysis of synthesized inter-element control moments values showed that the most significant influence on the value of the ground reaction and, therefore, on the pushingoff velocity was the motion of the swinging nonsupport leg. Variation of the parameters values of ground reaction and the resulting value of the kinetic moment allowed us to synthesize the AM motion in the support phase so that it would ensure the desired trajectory of the AM motion in the flying phase of acrobatic motions. Conclusions: Research showed the necessity of employment of non-stationary constraint equations in the synthesis of complex coordination human motions. Such an approach to motion control synthesis minimizes the number of parameters to be varied and gives a relatively stable solution with respect to small variations of AM structure. REFERENCES: 1. Zinkovsky, A.V., Sholuha, V.A., Ivanov, A.A. (1997). Mathematical Modeling and Computer Simulation of Biomechanical Systems, WSP, Singapore, 216

THE PRINCIPLES OF CONSTRUCTION OF THE ADEQUATE MATHEMATICAL MODELS FOR THE INVESTIGATION OF THE ANTHROPOMORPH MECHANISMS DYNAMICS

On the base of the mathematical modeling of the problems of the dynamics of the branching kinematic circuits with the connections, the computer model has been developed for the analysis, synthesis and optimization of the motion of the anthropomorph mechanisms has been developed, the model allowed to model the locomotor apparatus of the man and its parts for a wide class of the purpose-directed and complex-coordinated motions. The results of the work allow to build the adequate model of the locomotor apparatus for the concrete motions, allowing to design the structure of control and necessary energo-power expenditures for the motion completion. The models for the design of forces of the muscle contraction have been offered. The results of the work have been introduced in the scientific investigations.Available from VNTIC / VNTIC - Scientific & Technical Information Centre of RussiaSIGLERURussian Federatio

Kinematics Reconstruction by Scalable Double Step Registration (SDSR)

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Challenges in the system modeling of the musculoskeletal apparatus

The musculoskeletal system (or MSS) is essential for the performance of day-to-day functional tasks and thus leading a quality life. MSS pathologies can therefore have a significant impact on our daily life. The MSS is also involved in central nervous conditions (e.g. brain stroke, cerebral palsy, spinal cord damages, etc.) and is sensitive to cardiovascular disorders. Such conditions can lead to severe impairments of the MSS normal physiology, leading to severe disabilities. It is therefore not surprising to find MSS-related health problems at the top of global statistics on professional absenteeism or societal health costs (see The Burden of Musculoskeletal Diseases in the United States, AAOS). Recently, a couple of papers by Lozano et al. and Murray et al. published in The Lancet reported results from a large comprehensive study about the worldwide impact of all major diseases and risk factors on disability and mortality; this study found “that musculoskeletal conditions affect more than 1.7 billion people worldwide and have the fourth greatest impact on the overall health of the world population, considering both death and disability (DALYs).” The same study also stated that musculoskeletal-related disorders have increased by 45% over the past 20 years and will continue to increase unless appropriate preventive action is taken. Despite the widely recognized important role of MSS in our daily functions and in maintaining quality of life, the current fundamental knowledge related to the individual components of the MSS architecture remains relatively limited. This limited knowledge with a lack of standardized data representation often proves insufficient in systems engineering and modeling applications. This limitation is a major obstacle in the progress of fundamental and applied research today. Efforts in bioengineering and biomechanics are needed to improve current simulation methods through a better integration of functional anatomy knowledge with improved and well-described system modeling. In fundamental research on MSS architecture, more effort should be devoted to gathering reliable statistical data on the architecture of each single muscle and quantify anatomical variations in the human species. This chapter focuses on compiling all the knowledge available on MSS architecture and presents the details with the aim of facilitating further research and bridging the gap between literature and current knowledge. It also presents a wider picture of several challenges lying ahead and tasks to be performed to achieve the goals of gaining objective fundamental knowledge on all MSS components in order to develop clinically useful MSS models.SCOPUS: ch.binfo:eu-repo/semantics/publishe

Real time modeling of human body dynamics

Abstract—3D real time human body dynamics modeling allows fast and correct assessment of internal forces distribution, providing measured by motion analysis kinematics. In this paper we touch upon a subject of unsupported human body motion modeling with real-time or interactive rate. Speed is very important when someone examines the reaction of human body on some external influence or change of configuration of system containing human body. This paper discusses two approaches for real-time modeling of body dynamics and presents their programming realization. Keywords-human body; dynamics; real-time I

Bone and joint shape prediction by customizable multiple regressions

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Combined motions of the shoulder joint complex for model-based simulation: modeling of the shoulder rythm (ShRm)

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Muscle and ligament surface reconstruction by digital stereophotogrammetry

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Multidimensional regression for joint position prediction

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