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Interactive Coordinated Multiple-View Visualization of Biomechanical Motion Data

机译:生物力学运动数据的交互式协调多视图可视化

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We present an interactive framework for exploring space-time and form-function relationships in experimentally collected high-resolution biomechanical data sets. These data describe complex 3D motions (e.g. chewing, walking, flying) performed by animals and humans and captured via high-speed imaging technologies, such as biplane fluoroscopy. In analyzing these 3D biomechanical motions, interactive 3D visualizations are important, in particular, for supporting spatial analysis. However, as researchers in information visualization have pointed out, 2D visualizations can also be effective tools for multi-dimensional data analysis, especially for identifying trends over time. Our approach, therefore, combines techniques from both 3D and 2D visualizations. Specifically, it utilizes a multi-view visualization strategy including a small multiples view of motion sequences, a parallel coordinates view, and detailed 3D inspection views. The resulting framework follows an overview first, zoom and filter, then details-on-demand style of analysis, and it explicitly targets a limitation of current tools, namely, supporting analysis and comparison at the level of a collection of motions rather than sequential analysis of a single or small number of motions. Scientific motion collections appropriate for this style of analysis exist in clinical work in orthopedics and physical rehabilitation, in the study of functional morphology within evolutionary biology, and in other contexts. An application is described based on a collaboration with evolutionary biologists studying the mechanics of chewing motions in pigs. Interactive exploration of data describing a collection of more than one hundred experimentally captured pig chewing cycles is described.
机译:我们提出了一个互动的框架,以探索实验收集的高分辨率生物力学数据集中的时空与形式-功能之间的关系。这些数据描述了动物和人类执行的复杂3D运动(例如咀嚼,行走,飞行),并通过高速成像技术(例如双平面荧光检查)捕获了这些3D运动。在分析这些3D生物力学运动时,交互式3D可视化尤为重要,特别是对于支持空间分析。但是,正如信息可视化研究人员所指出的那样,二维可视化也可以是多维数据分析的有效工具,尤其是随着时间推移确定趋势的工具。因此,我们的方法结合了3D和2D可视化技术。具体来说,它利用了多视图可视化策略,包括运动序列的较小倍数视图,平行坐标视图和详细的3D检查视图。生成的框架首先遵循概述,然后进行缩放和过滤,然后按需提供详细的分析样式,并且明确地针对当前工具的局限性,即在运动集合的层次上支持分析和比较,而不是顺序分析。单个或少量动作。骨科和物理康复的临床工作,进化生物学内的功能形态研究以及其他情况下,都存在适合这种分析方式的科学运动集合。基于与进化生物学家合作研究一种应用的描述,该生物学家研究了猪的咀嚼运动的机理。描述了描述一百多个实验捕获的猪咀嚼周期集合的数据的交互式探索。

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