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A decision-support framework for promoting independent living and ageing well.

Abstract：

:Artificial intelligence and decision support systems offer a plethora of health monitoring capabilities in ambient assisted living environment. Continuous assessment of health indicators for elderly people living on their own is of utmost importance, so as to prolong their independence and quality of life. Slow varying, long-term deteriorating health trends are not easily identifiable in seniors. Thus, early sign detection of a specific condition, as well as, any likely transition from a healthy state to a pathological one are key problems that the herein proposed framework aims at resolving. Statistical process control concepts offer a personalized approach toward identification of trends that are away from the atypical behavior or state of the seniors, while fuzzy cognitive maps knowledge representation and inference schema have proved to be efficient in terms of disease classification. Geriatric depression is used as a case study throughout the paper, so to prove the validity of the framework, which is planned to be pilot tested with a series of lone-living seniors in their own homes.

journal_name

IEEE J Biomed Health Inform

journal_title

IEEE journal of biomedical and health informatics

authors

Billis AS,Papageorgiou EI,Frantzidis CA,Tsatali MS,Tsolaki AC,Bamidis PD

doi

10.1109/JBHI.2014.2336757

subject

Has Abstract

pub_date

2015-01-01 00:00:00

pages

199-209

issue

1

eissn

2168-2194

issn

2168-2208

pii

6866107

journal_volume

19

pub_type

杂志文章

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