Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/76516
Title: Development of an intelligent e-healthcare system for the domestic care industry
Authors: Wong, BN 
Ho, GTS 
Tsui, E 
Keywords: Internet of Things
E-Healthcare system
Elderly care service Fuzzy Association Rule Mining
Issue Date: 2017
Publisher: Emerald Group Publishing Limited
Source: Industrial management and data systems, 2017, v. 117, no. 7, p. 1426-1445 How to cite?
Journal: Industrial management and data systems 
Abstract: Purpose - In view of the elderly caregiving service being in high demand nowadays, the purpose of this paper is to develop an intelligent e-healthcare system for the domestic care industry by using the Internet of Things (IoTs) and Fuzzy Association Rule Mining (FARM) approach. Design/methodology/approach - The IoTs connected with the e-healthcare system collect real-time vital sign monitoring data for the e-healthcare system. The FARM approach helps to identify the hidden relationships between the data records in the e-healthcare systemto support the elderly care management tasks. Findings -To evaluate the proposed system and approach, a case study was carried out to identify the association between the specific collected demographic data, behavior data and the health measurements data in the e-healthcare system. It is found that the discovered rules are useful for the care management tasks in the elderly healthcare service. Originality/value - Knowledge discovery in databases uses various data mining techniques and rule-based artificial intelligence algorithms. This paper demonstrates complete processes on how an e-healthcare system connected with IoTs can support the elderly care services via a data collection phase, data analysis phase and data reporting phase by using the FARM to evaluate the fuzzy sets of the data attributes. The caregivers can use the discovered rules for proactive decision support of healthcare services and to improve the overall service quality by enhancing the elderly healthcare service responsiveness.
URI: http://hdl.handle.net/10397/76516
ISSN: 0263-5577
EISSN: 1758-5783
DOI: 10.1108/IMDS-08-2016-0342
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