Automated Cognitive Health Assessment Using Smart Home Monitoring of Complex Tasks
One of the many services that intelligent systems can provide is the automated assessment of resident well-being. We hypothesize that the functional health of individuals, or ability of individuals to perform activities independently without assistance, can be estimated by tracking their activities...
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| Veröffentlicht in: | IEEE transactions on systems, man, and cybernetics. Systems man, and cybernetics. Systems, 2013-11, Vol.43 (6), p.1302-1313 |
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| container_title | IEEE transactions on systems, man, and cybernetics. Systems |
| container_volume | 43 |
| creator | Dawadi, Prafulla N. Cook, Diane J. Schmitter-Edgecombe, Maureen |
| description | One of the many services that intelligent systems can provide is the automated assessment of resident well-being. We hypothesize that the functional health of individuals, or ability of individuals to perform activities independently without assistance, can be estimated by tracking their activities using smart home technologies. In this paper, we introduce a machine-learning-based method to assess activity quality in smart homes. To validate our approach, we quantify activity quality for 179 volunteer participants who performed a complex, interweaved set of activities in our smart home apartment. We compare our automated assessment of task quality with direct observation scores. We also assess the ability of machine-learning techniques to predict the cognitive health of the participants based on these automated scores. We believe that this capability is an important step in understanding everyday functional health of individuals in their home environments. |
| doi_str_mv | 10.1109/TSMC.2013.2252338 |
| format | Article |
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User interface ; Computerized, statistical medical data processing and models in biomedicine ; Cybernetics ; Dementia ; Exact sciences and technology ; Gerontology ; Health ; Machine learning ; Medical computing and teaching ; Medical sciences ; Monitoring ; Patient monitoring ; Quality assessment ; Sequential analysis ; Smart environments ; Smart homes ; Software ; Tasks ; Tracking ; Ubiquitous computing</subject><ispartof>IEEE transactions on systems, man, and cybernetics. Systems, 2013-11, Vol.43 (6), p.1302-1313</ispartof><rights>2015 INIST-CNRS</rights><rights>Copyright The Institute of Electrical and Electronics Engineers, Inc. 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Systems</title><addtitle>TSMC</addtitle><addtitle>IEEE Trans Syst Man Cybern Syst</addtitle><description>One of the many services that intelligent systems can provide is the automated assessment of resident well-being. We hypothesize that the functional health of individuals, or ability of individuals to perform activities independently without assistance, can be estimated by tracking their activities using smart home technologies. In this paper, we introduce a machine-learning-based method to assess activity quality in smart homes. To validate our approach, we quantify activity quality for 179 volunteer participants who performed a complex, interweaved set of activities in our smart home apartment. We compare our automated assessment of task quality with direct observation scores. We also assess the ability of machine-learning techniques to predict the cognitive health of the participants based on these automated scores. 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| source | IEEE Electronic Library (IEL) |
| subjects | Applied sciences Artificial intelligence Assessments Automated Biological and medical sciences Computer science control theory systems Computer systems and distributed systems. User interface Computerized, statistical medical data processing and models in biomedicine Cybernetics Dementia Exact sciences and technology Gerontology Health Machine learning Medical computing and teaching Medical sciences Monitoring Patient monitoring Quality assessment Sequential analysis Smart environments Smart homes Software Tasks Tracking Ubiquitous computing |
| title | Automated Cognitive Health Assessment Using Smart Home Monitoring of Complex Tasks |
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