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Model-based approach for human kinematics reconstruction from markerless and marker-based motion analysis systems

机译:无标记和基于标记的运动分析系统中基于模型的人体运动学重建方法

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Modeling tools related to the musculoskeletal system have been previously developed. However, the integration of the real underlying functional joint behavior is lacking and therefore available kinematic models do not reasonably replicate individual human motion. In order to improve our understanding of the relationships between muscle behavior, i.e. excursion and motion data, modeling tools must guarantee that the model of joint kinematics is correctly validated to ensure meaningful muscle behavior interpretation. This paper presents a model-based method that allows fusing accurate joint kinematic information with motion analysis data collected using either marker-based stereophotogrammetry (MBS) (i.e. bone displacement collected from reflective markers fixed on the subject's skin) or markerless single-camera (MLS) hardware. This paper describes a model-based approach (MBA) for human motion data reconstruction by a scalable registration method for combining joint physiological kinematics with limb segment poses. The presented results and kinematics analysis show that model-based MBS and MLS methods lead to physiologically-acceptable human kinematics. The proposed method is therefore available for further exploitation of the underlying model that can then be used for further modeling, the quality of which will depend on the underlying kinematic model.
机译:先前已经开发了与肌肉骨骼系统有关的建模工具。但是,缺乏真正的基础功能关节行为的整合,因此可用的运动学模型不能合理地复制单个人的动作。为了增进我们对肌肉行为之间关系(即偏移和运动数据)的理解,建模工具必须保证关节运动学模型得到正确验证,以确保有意义的肌肉行为解释。本文提出了一种基于模型的方法,该方法允许将准确的关节运动学信息与使用基于标记的立体摄影测量(MBS)(即从固定在受试者皮肤上的反射性标记收集的骨骼位移)或无标记的单相机(MLS)收集的运动分析数据融合) 硬件。本文介绍了一种基于模型的方法(MBA),该方法通过可伸缩的注册方法将关节生理运动学与肢体节段姿势相结合来重建人体运动数据。提出的结果和运动学分析表明,基于模型的MBS和MLS方法导致了生理学上可接受的人类运动学。因此,所提出的方法可用于基础模型的进一步开发,然后可将其用于进一步的建模,其质量将取决于基础的运动学模型。

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