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SAPHE: Advanced Pervasive Healthcare Solutions for Aging Populations

SAPHE (Smart and Aware Pervasive Healthcare Environment) is a pioneering project aimed at enhancing health monitoring through unobtrusive sensing technologies. Funded by the DTI Technology Programme with £3.36M, the initiative is led by Professor Guang-Zhong Yang of Imperial College London, in partnership with industry leaders like BT and Philips, as well as academic institutions. The project focuses on developing miniaturized sensors for real-time monitoring of physiological and lifestyle parameters, fostering improved well-being and early disease detection for the aging population.

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SAPHE: Advanced Pervasive Healthcare Solutions for Aging Populations

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  1. SAPHE - Smart and Aware Pervasive Healthcare Environment • Funded by DTI Technology Programme (£3.36M with £1.68M from DTI, from 1st March, 2006) • Project Director: Professor Guang-Zhong Yang, Imperial College London with BT and Philips as the industry leaders • Project Partners: Imperial College London, BT, Philips, Cardionetics, University of Dundee, Docobo, and in collaboration with University of Liverpool and Liverpool Social Services and Primary Care Trust

  2. Intelligent Wearable Ambient

  3. By sensing under normal physiological conditions combined with intelligent trend analysis, SAPHE opens up new opportunities for the UK ICT and healthcare sectors in meeting the challenges of demographic changes associated with the aging population DTI Technology Programme Project Overview • To develop a novel architecture for unobtrusive pervasive sensing to link physiological/metabolic parameters and lifestyle patterns for improved well-being monitoring and early detection of changes in disease.

  4. Technical Objectives • Miniaturised sensing with self-management and configuration • Local data abstraction and sensor fusion/inferencing with low power sensor and wireless data path • Processing-on-node technology for context aware sensing • Automated trust-based decision support and "affective computing" for improved human-computer interfacing • Intelligent trend analysis and large scale data mining

  5. Central Server

  6. Intelligent Wearable Ambient

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