Use this URL to cite or link to this record in EThOS: http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.558785
Title: The use of computer vision techniques to augment home based sensorised environments
Author: Šturcová, Zdenka
Awarding Body: University of Ulster
Current Institution: Ulster University
Date of Award: 2012
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Abstract:
Sensorised environments offer opportunities in the support of our everyday lives, in particular, towards realising the concepts of 'Ageing in place'. Such environments are capable of allowing occupants to live independently by providing remote monitoring services and by supporting the completion of activities of daily living. This research focuses on augmenting sensorised environments and promoting improved health- care services with video based solutions. The aim was to demonstrate that video based solutions are feasible and have wide usability and potential in health care, elderly care and generally within sensorised environments. This aim was addressed by considering a number of research objectives, which have been investigated and presented as a series of studies within this thesis. Specifically, the first study targeted multiple occupancy within sensorised environments where a solution based on tracking persons through the use of video was proposed. The results show that multiple occupancy can be handled using video and that users can be successfully tracked within an environment. The second study used video to investigate repetitive behaviour patterns in persons with dementia. The experiment showed that the repetitive behaviour can be extracted and successfully analysed using a single camera. Thirdly, a target group of Parkinson's disease patients are considered with whom video analysis is used to build an automated diary describing their changing status over the day. Results showed that the changes in the patient's movement abilities can be revealed from a video. The final study investigated a specific type of movement disorder known as a tremor. A method involving frequency analysis of tremor from video data was validated in a clinical study involving 31 participants. Furthermore, this study resulted in the development of an open-source software application for routine tremor assessment. This thesis offers a contribution to knowledge by demonstrating that video can be used to further augment sensorised environments to support non-invasive remote monitoring and assessment.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID: uk.bl.ethos.558785  DOI: Not available
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