Abstract
Current medical data derived from gait analysis and diagnosis of various musculoskeletal pathologies offer a plethora of text based and imaging data. The large volume and complexity of the particular data present a number of issues during the collection, storage, searching and visualisation process for gait analysis management and diagnosis. Adhering to above it is evident that a simplified, holistic and user-friendly system is required in order to improve the acquisition and comparison of medical data in a timely manner. Further consultation with health professionals suggested that the proposed prototype should entail an automated system that can extract, save and visualise the data from different sources, in order to enhance medical data visualisation, increase efficiency and thus improve quality of service and management. This work presents the development stages of a new prototype system for managing medical data for gait analysis, which additionally offer simulation capacity in a Virtual Reality environment in order to assist the medical practitioners towards a faster an better informed evaluation of each condition. In particular this paper investigates various methods of displaying medical data in a single application with a view to managing and sharing multimedia data and to employing a VR to enhance user interaction with medical data. Findings of a promising preliminary evaluation through user trials are also presented. Concluding, the paper presents future plans to incorporate a bespoke 3D human- computer interface with a view to provide the health professionals with customisable information and enhancing the interface functionalities. Finally, as the system is web-based there is scope for expansion of the application to other areas of medical assessments involving complicated datasets.
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Alfalah, S.F.M., Harrison, D.K., Charissis, V. (2013). Gait Analysis Management and Diagnosis in a Prototype Virtual Reality Environment. In: Shumaker, R. (eds) Virtual, Augmented and Mixed Reality. Systems and Applications. VAMR 2013. Lecture Notes in Computer Science, vol 8022. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-39420-1_1
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