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methods. Finally, the enormous number of decision variables (unknowns) with the proposed framework would lead to the computational complexity; and consequently, the derivation of exact optimal solution
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, to equip individuals with knowledge, increase motivation and help them make informed choices to proactively address seven key modifiable risk factors for dementia including low education, physical inactivity
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vibration characteristic identification. This project will investigate digital twins techniques aided by computer vision based measurement. Aims This project develops computer vision-assisted digital twin
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fall detection would be from video as it does not require wearing a device and remembering to charge it and so on. But computer vision-based falls detection in the elderly can be problematic due
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the Digital Systems and Intelligent Sensors group (DSIS). within the School of Electrical Engineering, Computing and Mathematical Sciences. DSIS endeavours to utilise technology to assist people with
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assist in solving a real-world problem that is limiting the optimisation of their player preparation practices. This research will also address a significant gap in the current understanding of how