Combining Automated and Interactive Visual Analysis of Biomechanical Motion Data

Spurlock, Scott; Chang, Remco; Wang, Xiaoyu; Arceneaux, G.; Keefe, Daniel F.; Souvenir, Richard

doi:10.1007/978-3-642-17274-8_55

Cited by 2 publications

(2 citation statements)

References 18 publications

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“…Some approaches use (interactive) data aggregation, followed by an additional projection step. 27,28 We neglect this variant since the generalizability may be compromised when other data sets with unknown intrinsic numbers of clusters are to be analyzed. Alternative approaches firstly project data objects into the display space and then aggregate the low-dimensional data representations.…”

Section: Data Aggregation and Projection Of Multivariate Time Series mentioning

confidence: 99%

FuryExplorer: visual-interactive exploration of horse motion capture data

et al. 2015

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The analysis of equine motion has a long tradition in the past of mankind. Equine biomechanics aims at detecting characteristics of horses indicative of good performance. Especially, veterinary medicine gait analysis plays an important role in diagnostics and in the emerging research of long-term effects of athletic exercises. More recently, the incorporation of motion capture technology contributed to an easier and faster analysis, with a trend from mere observation of horses towards the analysis of multivariate time-oriented data. However, due to the novelty of this topic being raised within an interdisciplinary context, there is yet a lack of visual-interactive interfaces to facilitate time series data analysis and information discourse for the veterinary and biomechanics communities. In this design study, we bring visual analytics technology into the respective domains, which, to our best knowledge, was never approached before. Based on requirements developed in the domain characterization phase, we present a visual-interactive system for the exploration of horse motion data. The system provides multiple views which enable domain experts to explore frequent poses and motions, but also to drill down to interesting subsets, possibly containing unexpected patterns. We show the applicability of the system in two exploratory use cases, one on the comparison of different gait motions, and one on the analysis of lameness recovery. Finally, we present the results of a summative user study conducted in the environment of the domain experts. The overall outcome was a significant improvement in effectiveness and efficiency in the analytical workflow of the domain experts.

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Section: Data Aggregation and Projection Of Multivariate Time Series mentioning

confidence: 99%

FuryExplorer: visual-interactive exploration of horse motion capture data

et al. 2015

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“…Visual Analytics have been assembled successfully in the domains of brain activity simulation, as well as in the biomechanical motion analysis [6]. Spurlock et al [7] presented a framework for combining automated and interactive visual analysis techniques for use in high-resolution biomechanical data, analysing the complex motion of animals. Additionally, the study of human factors and ergonomics have benefited from advanced visualisation techniques in order to extract high level rules from the complex data space [8].…”

Section: Introductionmentioning

confidence: 99%

Simulation and Visual Analysis of Neuromusculoskeletal Models and Data

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et al. 2015

IFIP Advances in Information and Communication Technology

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Part 7: New Methods and Tools for Big DataInternational audienceThis work presents a novel medical decision support system for diseases related to the upper body neuromusculature. The backbone of the system is a simulation engine able to perform both forward and inverse simulation of upper limb motions. In forward mode neural signals are fed to the muscles that perform the corresponding motion. In the inverse mode, a specified motion trajectory is used as input and the neural signals that are the root cause of this particular motion are estimated and investigated. Due to the vast amount of information that results from even simple simulations, the results are presented to the expert using visual analytics metaphors and in particular both embodied and symbolic visualizations. Several use cases are presented so as to demonstrate the analytics potential of the proposed system

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Combining Automated and Interactive Visual Analysis of Biomechanical Motion Data

Cited by 2 publications

References 18 publications

FuryExplorer: visual-interactive exploration of horse motion capture data

FuryExplorer: visual-interactive exploration of horse motion capture data

Simulation and Visual Analysis of Neuromusculoskeletal Models and Data

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