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Title: Enhancement of asynchronous musculoskeletal diagnostic methods with the use of real-time virtual reality and motion capture systems for telemedicine
Author: Khan, Mohammed Soheeb
ISNI:       0000 0004 5354 9099
Awarding Body: Glasgow Caledonian University
Current Institution: Glasgow Caledonian University
Date of Award: 2014
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The demand and utilisation of telemedicine-based care is increasingly in demand due to the highly amplified number of populations striving towards a country life and remote location living style. Additionally, the financial climate, limited resources and the constantly growing population around the globe have prompted an interest from various governing bodies to reform and seek alternative methods for delivering high quality health care. The technological advancements and the increase of communication innovations have made telemedicine a promising solution for many issues faced by the current health care systems. Musculoskeletal (MSK) issues and injuries often present the largest number of cases amongst General Practitioners COPs) which tend to need monitoring after any surgical intervention or rehabilitation process. Yet the gait analysis of each patient is time-consuming and costly if the patients are located away from the medical and city centres. The technological innovations in motion-capture (Mo-Cap) systems have made it possible to acquire and collect complex motion data for biomechanics of musculoskeletal (MSK) structures. Yet the requirement of specialised costly equipment, professional setup, training and allocation of a dedicated large space rendered these techniques ideal only for a laboratory environment. Such laboratories are most commonly situated at a designated facility which requires the patients to travel to and from it routinely. Due to the limitation of such facilities, patients living in isolated and rural areas have limited or no access to this triage. Contemporary technological breakthroughs, related to cameras, projectors and videogames fuelled the development of cost-efficient, consumer-based peripherals offering Markerless motion capture techniques. Off-the-shelf devices such as Microsoft "Kinect" could be utilised efficiently for a fraction of the typical Mo-Cap suites price with insignificant difference in the tracking quality for the majority of the tracking activities. Mass developments of videogames, Virtual Reality (VR) and 3D programs have made it possible for 3D engines to be utilised across various industries as common platforms for real-time visualisation purposes. This has prompted medical information to be presented in a much-improved manner by the use of photorealistic 3D models and user-friendly interfaces. Early attempts to utilise 3D medical data-set in real-time environments have been limited or designed for a set purpose. Several systems have been designed for educational rationale and even contain visually appealing 3D data-sets but are velY restrictive in their functionality. Although they may illustrate details of human anatomy and provide users with enriched content and information, the restrictive system design renders them unsuccessful for adaptation and cannot be employed for gait analysis, rehabilitation and diagnosis purposes. Other systems have been designed for gait analysis and rehabilitation purposes and have been employed by the industry in various disciplines. Such systems are designed to work with high-end expensive tracking hardware, only support specific file formats and lack detailed visually appealing 3D content for the user. Furthermore they do not support off-the-shelf devices such as Microsoft "Kinect" therefore cannot be used in conjunction with such devices. However there have been some initial amateur attempts to perform gait analysis using off-the-shelf devices. But they are very limited with complex customised interfaces, have very limited functionality and an inaccurate visualisation and representation of the human anatomy. Due to these limitations a telemedicine based system has not been implemented in the past.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available