Upper limb movement simulation and biomechanical characteristics during human movement
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Hao Wang
Abstract
The movement process of the human body is not the movement process of a single limb, but the movement process of skeletal muscles that coordinate multiple adjacent limbs with joints as the hub. Human body movement has different actions and links. When observing the human body movement mechanism, introducing the body movement chain can maintain the integrity and independence of the movement system. The upper limb of the human body is a kinematic chain with multiple limbs and multiple degrees of freedom, which can perform various complex movements. This article mainly introduces the upper limb movement simulation and biomechanical characteristics analysis during human movement, and intends to provide some ideas and directions for the upper limb movement simulation and biomechanical characteristics research during human movement. This paper proposes the research methods of upper limb motion simulation and biomechanical characteristics analysis during human movement, summarizes the human upper limb physiological structure and the relevant theoretical knowledge of human body biomechanics, and proposes the human upper limb motion capture and the human upper limb posture description algorithm for the human body Simulation experiment of upper limb movement during exercise. The experimental results of this paper show that the overall prediction time of simulation using MSCNN is only 0.0065 s, which ensures the real-time prediction.
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Author contributions: The author has accepted responsibility for the entire content of this submitted manuscript and approved submission.
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Research funding: None declared.
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Conflict of interest statement: The author declares no conflicts of interest regarding this article.
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© 2022 Walter de Gruyter GmbH, Berlin/Boston
Artikel in diesem Heft
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- Automatic monitoring system of power equipment based on Internet of Things technology
- Intelligent algorithm of electrical fire monitoring system based on data mining technology
- Vector correlation learning and pairwise optimization feature selection for false data injection attack detection in smart grid
- ZIP load modeling for single and aggregate loads and CVR factor estimation
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Artikel in diesem Heft
- Frontmatter
- Research Articles
- Fault diagnosis of ship power equipment based on adaptive neural network
- Application of sustainable power and laser washing device in garment design
- Automatic monitoring system of power equipment based on Internet of Things technology
- Intelligent algorithm of electrical fire monitoring system based on data mining technology
- Vector correlation learning and pairwise optimization feature selection for false data injection attack detection in smart grid
- ZIP load modeling for single and aggregate loads and CVR factor estimation
- Upper limb movement simulation and biomechanical characteristics during human movement
- Intelligent home control system based on BP neural network speech recognition
- User-side precision marketing model of integrated energy service system
- Building carbon neutrality goals break down strategies for sustainable energy development
- Energy-saving intelligent manufacturing optimization scheme for new energy vehicles
