Literature DB >> 19834212

Interactive coordinated multiple-view visualization of biomechanical motion data.

Daniel F Keefe1, Marcus Ewert, William Ribarsky, Remco Chang.   

Abstract

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.

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Year:  2009        PMID: 19834212     DOI: 10.1109/TVCG.2009.152

Source DB:  PubMed          Journal:  IEEE Trans Vis Comput Graph        ISSN: 1077-2626            Impact factor:   4.579


  3 in total

1.  Virtual mastoidectomy performance evaluation through multi-volume analysis.

Authors:  Thomas Kerwin; Don Stredney; Gregory Wiet; Han-Wei Shen
Journal:  Int J Comput Assist Radiol Surg       Date:  2012-04-12       Impact factor: 2.924

2.  Trend-Centric Motion Visualization: Designing and Applying a New Strategy for Analyzing Scientific Motion Collections.

Authors:  David Schroeder; Fedor Korsakov; Carissa Mai-Ping Knipe; Lauren Thorson; Arin M Ellingson; David Nuckley; John Carlis; Daniel F Keefe
Journal:  IEEE Trans Vis Comput Graph       Date:  2014-12       Impact factor: 4.579

3.  ENIGMA-Viewer: interactive visualization strategies for conveying effect sizes in meta-analysis.

Authors:  Guohao Zhang; Peter Kochunov; Elliot Hong; Sinead Kelly; Christopher Whelan; Neda Jahanshad; Paul Thompson; Jian Chen
Journal:  BMC Bioinformatics       Date:  2017-06-06       Impact factor: 3.169

  3 in total

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