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With advances in data acquisition devices, current rehabilitation research involves extensive experimental trials 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. For research focused on movement analysis, high volume of multimedia data such as high-speed video is acquired with other data types such as surveys, spreadsheets, force data recordings from instrumented surfaces etc. These datasets are recorded from various standalone sources however multimedia data in rehabilitation research is often requires analysis in context with subject’s medical history, treatment plan or progress. But in current research workflow, no pathways and data handling protocols are defined to successfully achieve comprehensive integration of multimedia data, for various data types collected at various stages in a clinical trial, different data handling protocols needs to be defined and designed. In this presentation, we will be focusing on multimedia data only such as high-speed video files collected during a clinical trial. Multimedia data collected during a rehabilitation research often end up residing in an isolated space. Our aim for this presentation is to design and evaluate data handling steps for successful integration, storage and retrieval of multimedia data. This presentation focuses on establishing tools that can be used between data acquisition step to data storage for media files. We will present method for metadata creation for multimedia data based on the electronic patient data (ePR) model design as well as two common standards of medical imaging, DICOM and PACS to form an effective data handling protocol. For evaluation, data set collected for wheelchair movement analysis study at Rancho Los Amigos National Rehabilitation Center in Downey, California will be used. The broader aim of this paper is to present development of standards and protocols for multimedia data handling in a clinical workflow based on medical imaging informatics.
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