Activities of daily life recognition using process representation modelling to support intention analysis. Issue 3 (7th September 2015)

• Record Type: Journal Article
• Authors: Naeem, Usman; Bashroush, Rabih; Anthony, Richard; Azam, Muhammad Awais; Tawil, Abdel Rahman; Lee, Sin Wee; Mou-Ling, Dennis
• Is Part Of: International journal of pervasive computing and communications. Volume 11:Issue 3(2015)
• Page Start: 347
• Page End: 371
• Publication Date: 2015-09-07
• Subjects: Ubiquitous computing -- Periodicals; Mobile computing -- Periodicals; Computer network protocols -- Periodicals; Computer network architectures -- Periodicals; Application software -- Development -- Periodicals; 004.6
• DOI: 10.1108/IJPCC-01-2015-0002
• Languages: English
• ISSNs: 1742-7371

Abstract

<abstract> <title> <x content-type="archive" xml:space="preserve">Abstract</x> </title> <sec> <title content-type="abstract-heading">Purpose</title> <p> – This paper aims to focus on applying a range of traditional classification- and semantic reasoning-based techniques to recognise activities of daily life (ADLs). ADL recognition plays an important role in tracking functional decline among elderly people who suffer from Alzheimer's disease. Accurate recognition enables smart environments to support and assist the elderly to lead an independent life for as long as possible. However, the ability to represent the complex structure of an ADL in a flexible manner remains a challenge. </p> </sec> <sec> <title content-type="abstract-heading">Design/methodology/approach</title> <p> – This paper presents an ADL recognition approach, which uses a hierarchical structure for the representation and modelling of the activities, its associated tasks and their relationships. This study describes an approach in constructing ADLs based on a task-specific and intention-oriented plan representation language called Asbru. The proposed method is particularly flexible and adaptable for caregivers to be able to model daily schedules for Alzheimer's patients. </p> </sec> <sec> <title content-type="abstract-heading">Findings</title> <p> – A proof of concept prototype evaluation has been conducted for the validation of the proposed ADL recognition engine, which has comparable recognition results with existing ADL recognition approaches. </p> </sec> <sec> <title content-type="abstract-heading">Originality/value</title> <p> – The work presented in this paper is novel, as the developed ADL recognition approach takes into account all relationships and dependencies within the modelled ADLs. This is very useful when conducting activity recognition with very limited features.</p> </sec> </abstract>