Bootstrapping activity modeling for ambient assisted living

Authors:
Jie Wan;Michael J. O'Grady;Gregory M. P. O'Hare
Affiliations:
CLARITY Centre for Sensor Web Technologies, University College Dublin, Ireland;CLARITY Centre for Sensor Web Technologies, University College Dublin, Ireland;CLARITY Centre for Sensor Web Technologies, University College Dublin, Ireland
Venue:
ICSH'13 Proceedings of the 2013 international conference on Smart Health
Year:
2013

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Abstract

In many societies, the age profile of the population is increasing, posing many challenges for societies, health services and carers. One response to this unfolding situation has been to direct research effort towards Ambient Assisted Living (AAL), specifically, its enabling technologies. A critical impediment to the deployment of such systems remains the accurate and timely identification of the Activities of Daily Living (ADLs). This paper advocates a minimalist approach to ADL recognition; rather than capturing all possible ADLs, the reliable identification of a select subset of ADLs may prove sufficient for many categories of AAL services. A methodology is described and initial results presented.