Activity Monitoring and UI Plasticity for supporting Ageing with Mild Dementia at Home

A/Prof. Mounir Mokhtari (IPAL), Dr. Jit Biswas (I2R), A/Prof. Dong Jin Song (NUS) & MD. Philip Yap (Alexandra Hospital)

Members & funding

AMUPADH is a two years project (2010-2012) between IPAL Laboratory, the Institute for Infocomm Research (I2R), the School of Computing of the National University of Singapore (NUS), and in close collaboration with Alexandra Hospital and Peacehaven Nursing Home in Singapore. It is one of the eleven A*STAR SERC Home2015 (Singapore national research program) projects, promoting cross-disciplinary research enabling technologies, foundations or frameworks for the future home systems and technologies.

Research focus

The project addresses the improvement of QoL (Quality of Life) for the elderly, especially those with dementia, by enabling their home with ambient assistive living technologies. The research scope is described in the figure below:


The general research axis in this project are:

  • Mechanisms of plasticity and adaptation of user interfaces in ambient intelligent space based on service provision architecture.
  • Fine grained activity recognition and plan recognition for activities of daily living using micro-context and grammar based techniques.
  • Scenario verification for sequences of activities at the level of multiple sensors, objects and people. Using Process Analysis Toolkit [PAT] from NUS SoC.

Within AMUPADH, IPAL project members are focused on the development of a context-aware service platform dedicated to ambient assisted living. This platform deals with context uncertainty, service selection and provision including service discontinuity aspects and user interface plasticity at the service delivery step. It is based on a service oriented approach using OSGi framework and integrated in a pervasive computing environment. Ontological models are designed to represent the environment (users, devices, services, activities...) and shared between context, service or interface reasoning engines. Reasoning is using description logic rules written using Notation3 (N3, N3Logic) and Euler inference engine for ontological inference of models.

A video demonstrating the current capabilities of our system is available in the demo page.

Research Team