Activities of daily life recognition using process representation modelling to support intention analysis

Article


Naeem, U., Bashroush, R., Anthony, Richard, Azam, Muhammad Awais, Tawil, Abdel Rahman, Lee, S. and Mou-Ling, Dennis 2015. Activities of daily life recognition using process representation modelling to support intention analysis. International Journal of Pervasive Computing and Communications. 11 (3), pp. 347-371.
AuthorsNaeem, U., Bashroush, R., Anthony, Richard, Azam, Muhammad Awais, Tawil, Abdel Rahman, Lee, S. and Mou-Ling, Dennis
Abstract

Purpose
– 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.

Design/methodology/approach
– 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.

Findings
– 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.

Originality/value
– 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.

JournalInternational Journal of Pervasive Computing and Communications
Journal citation11 (3), pp. 347-371
ISSN1742-7371
Year2015
PublisherEmerald
Accepted author manuscript
Digital Object Identifier (DOI)doi:10.1108/IJPCC-01-2015-0002
Publication dates
Print07 Sep 2015
Publication process dates
Deposited27 Oct 2015
Copyright information© 2015 Emerald
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