The article deals with the problem of forming a digital shadow of the process of moving a person. An analysis of the subject area was carried out, which showed the need to formalize the process of creating digital shadows to simulate human movements in virtual space, testing software and hardware systems that operate on the basis of human actions, as well as in various systems of musculoskeletal rehabilitation. It was revealed that among the existing approaches to the capture of human movements, it is impossible to single out a universal and stable method under various environmental conditions. A method for forming a digital shadow has been developed based on combining and synchronizing data from three motion capture systems (virtual reality trackers, a motion capture suit, and cameras using computer vision technologies). Combining the above systems makes it possible to obtain a comprehensive assessment of the position and condition of a person regardless of environmental conditions (electromagnetic interference, illumination). To implement the proposed method, a formalization of the digital shadow of the human movement process was carried out, including a description of the mechanisms for collecting and processing data from various motion capture systems, as well as the stages of combining, filtering, and synchronizing data. The scientific novelty of the method lies in the formalization of the process of collecting data on the movement of a person, combining and synchronizing the hardware of the motion capture systems to create digital shadows of the process of moving a person. The obtained theoretical results will be used as a basis for software abstraction of a digital shadow in information systems to solve the problems of testing, simulating a person, and modeling his reaction to external stimuli by generalizing the collected data arrays about his movement.
The process of forming a digital shadow of the human movement process is considered, which can be used in virtual reality systems, musculoskeletal rehabilitation, and other human-machine systems based on the analysis of the user’s movement. The most important step in creating the digital shadow is its formalization in the form of a mathematical model. At present, the issue of the formalization of digital shadows of various objects and processes has not been fully developed. The article discusses the development of the mathematical model of the digital shadow of the movement process, the novelty of which lies in combining information from four sources (three different motion capture systems and a complex of medical sensors to assess the physical condition of a person), as well as their synchronization and filtering. The obtained theoretical results will be used as a basis for software abstraction of the digital shadow in information systems to solve the problems of testing, simulating a person and modeling his reaction by summarizing the collected data arrays about his movement.
The improvement of virtual reality systems declares new requirements for the user immersion quality. To improve the immersiveness of the interaction process with virtual space, it is necessary to provide a realistic representation of a person in it, as well as the processes of his movement and interaction with virtual objects. In this work, the issue of using motion capture technologies to create a realistic avatar (digital shadow) and visualization of the movement process is considered. An algorithm for capturing human movements based on synchronization of various hardware solutions has been developed to create a digital shadow of the human movement process. The algorithm can be used to match the user with his virtual copy in virtual reality systems. The scientific novelty of the method lies in taking into account the position, direction and speed of a person’s movement, synchronization of the motion capture hardware tools used to create digital shadows of the person’s movement process.
Analysis and assessment of the state of information objects is an urgent task in adaptive systems. Information about the current state of the system, its constituent components, the object of observation can be used in the decision-making process or in the implementation of control algorithms. However, an information object can have a complex structure or be characterized by many features, among which it is difficult to distinguish the main components. Therefore, an algorithm for analyzing and assessing the state of information objects is proposed, based on obtaining the compressed state of objects using neural networks. The resulting compressed state sufficiently characterizes the original object, but has a lower dimension. This can be used to speed up the analysis and assessment process and improve its accuracy in adaptive systems.
In virtual reality (VR) systems, a problem is the accurate reproduction of the user’s body in a virtual environment using inverse kinematics because existing motion capture systems have a number of drawbacks, and minimizing the number of key tracking points (KTPs) leads to a large error. To solve this problem, it is proposed to use the concept of a digital shadow and machine learning technologies to optimize the number of KTPs. A technique for movement process data collecting from a virtual avatar is implemented, modeling of nonlinear dynamic processes of human movement based on a digital shadow is carried out, the problem of optimizing the number of KTP is formulated, and an overview of the applied machine learning algorithms and metrics for their evaluation is given. An experiment on a dataset formed from virtual avatar movements shows the following results: three KTPs do not provide sufficient reconstruction accuracy, the choice of five or seven KTPs is optimal; among the algorithms, the most efficient in descending order are AdaBoostRegressor, LinearRegression, and SGDRegressor. During the reconstruction using AdaBoostRegressor, the maximum deviation is not more than 0.25 m, and the average is not more than 0.10 m.
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