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Medical Imaging Informatics based solutions for human performance analytics

机译：基于医学影像信息学的人员绩效分析解决方案

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For human performance analysis, extensive experimental trials are often conducted to identify the underlying cause or long-term consequences of certain pathologies and to improve motor functions by examining the movement patterns of affected individuals. Data collected for human performance analysis includes high-speed video, surveys, spreadsheets, force data recordings from instrumented surfaces etc. These datasets are recorded from various standalone sources and therefore captured in different folder structures as well as in varying formats depending on the hardware configurations. Therefore, data integration and synchronization present a huge challenge while handling these multimedia datasets specifically for large datasets. Another challenge faced by researchers is querying large quantity of unstructured data and to design feedbacks/reporting tools for users who need to use datasets at various levels. In the past, database server storage solutions have been introduced to securely store these datasets. However, to automate the process of uploading raw files, various file manipulation steps are required. In the current workflow, this file manipulation and structuring is done manually and is not feasible for large amounts of data. However, by attaching metadata files and data dictionaries with these raw datasets, they can provide information and structure needed for automated server upload. We introduce one such system for metadata creation for unstructured multimedia data based on the DICOM data model design. We will discuss design and implementation of this system and evaluate this system with data set collected for movement analysis study. The broader aim of this paper is to present a solutions space achievable based on medical imaging informatics design and methods for improvement in workflow for human performance analysis in a biomechanics research lab.
机译：对于人体性能分析，经常进行广泛的试验，以查明某些病理的根本原因或长期后果，并通过检查受影响个体的运动方式来改善运动功能。收集用于人类绩效分析的数据包括高速视频，调查，电子表格，来自仪器表面的力数据记录等。这些数据集是从各种独立来源记录的，因此根据硬件配置以不同的文件夹结构以及不同的格式捕获。因此，在处理这些专门针对大型数据集的多媒体数据集时，数据集成和同步提出了巨大的挑战。研究人员面临的另一个挑战是查询大量非结构化数据，并为需要使用不同级别数据集的用户设计反馈/报告工具。过去，已经引入了数据库服务器存储解决方案来安全地存储这些数据集。但是，要自动化上载原始文件的过程，需要执行各种文件操作步骤。在当前的工作流程中，此文件操作和结构化是手动完成的，不适用于大量数据。但是，通过将元数据文件和数据字典与这些原始数据集连接在一起，它们可以提供自动服务器上载所需的信息和结构。我们介绍了一种基于DICOM数据模型设计的非结构化多媒体数据元数据创建系统。我们将讨论该系统的设计和实现，并使用为运动分析研究而收集的数据集对该系统进行评估。本文的广泛目标是提出一种基于医学成像信息学设计和方法的可实现的解决方案空间，以改善生物力学研究实验室中的人类绩效分析的工作流程。

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