A Survey on Ambient Intelligence in Health Care
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Auteurs : Giovanni Acampora ; Diane J. Cook ; Parisa Rashidi ; Athanasios V. VasilakosSource :
- Proceedings of the IEEE. Institute of Electrical and Electronics Engineers [ 0018-9219 ] ; 2013.
Abstract
Ambient Intelligence (AmI) is a new paradigm in information technology aimed at empowering people’s capabilities by the means of digital environments that are sensitive, adaptive, and responsive to human needs, habits, gestures, and emotions. This futuristic vision of daily environment will enable innovative human-machine interactions characterized by pervasive, unobtrusive and anticipatory communications. Such innovative interaction paradigms make ambient intelligence technology a suitable candidate for developing various real life solutions, including in the health care domain. This survey will discuss the emergence of ambient intelligence (AmI) techniques in the health care domain, in order to provide the research community with the necessary background. We will examine the infrastructure and technology required for achieving the vision of ambient intelligence, such as smart environments and wearable medical devices. We will summarize of the state of the art artificial intelligence methodologies used for developing AmI system in the health care domain, including various learning techniques (for learning from user interaction), reasoning techniques (for reasoning about users’ goals and intensions) and planning techniques (for planning activities and interactions). We will also discuss how AmI technology might support people affected by various physical or mental disabilities or chronic disease. Finally, we will point to some of the successful case studies in the area and we will look at the current and future challenges to draw upon the possible future research paths.
Url:
DOI: 10.1109/JPROC.2013.2262913
PubMed: 24431472
PubMed Central: 3890262
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<author><name sortKey="Cook, Diane J" sort="Cook, Diane J" uniqKey="Cook D" first="Diane J." last="Cook">Diane J. Cook</name>
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<author><name sortKey="Rashidi, Parisa" sort="Rashidi, Parisa" uniqKey="Rashidi P" first="Parisa" last="Rashidi">Parisa Rashidi</name>
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<author><name sortKey="Vasilakos, Athanasios V" sort="Vasilakos, Athanasios V" uniqKey="Vasilakos A" first="Athanasios V." last="Vasilakos">Athanasios V. Vasilakos</name>
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<author><name sortKey="Vasilakos, Athanasios V" sort="Vasilakos, Athanasios V" uniqKey="Vasilakos A" first="Athanasios V." last="Vasilakos">Athanasios V. Vasilakos</name>
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<front><div type="abstract" xml:lang="en"><p id="P1">Ambient Intelligence (AmI) is a new paradigm in information technology aimed at empowering people’s capabilities by the means of digital environments that are sensitive, adaptive, and responsive to human needs, habits, gestures, and emotions. This futuristic vision of daily environment will enable innovative human-machine interactions characterized by pervasive, unobtrusive and anticipatory communications. Such innovative interaction paradigms make ambient intelligence technology a suitable candidate for developing various real life solutions, including in the health care domain. This survey will discuss the emergence of ambient intelligence (AmI) techniques in the health care domain, in order to provide the research community with the necessary background. We will examine the infrastructure and technology required for achieving the vision of ambient intelligence, such as smart environments and wearable medical devices. We will summarize of the state of the art artificial intelligence methodologies used for developing AmI system in the health care domain, including various learning techniques (for learning from user interaction), reasoning techniques (for reasoning about users’ goals and intensions) and planning techniques (for planning activities and interactions). We will also discuss how AmI technology might support people affected by various physical or mental disabilities or chronic disease. Finally, we will point to some of the successful case studies in the area and we will look at the current and future challenges to draw upon the possible future research paths.</p>
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<journal-id journal-id-type="nlm-ta">Proc IEEE Inst Electr Electron Eng</journal-id>
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<article-categories><subj-group subj-group-type="heading"><subject>Article</subject>
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<title-group><article-title>A Survey on Ambient Intelligence in Health Care</article-title>
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<contrib-group><contrib contrib-type="author"><name><surname>Acampora</surname>
<given-names>Giovanni</given-names>
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<role>Member, IEEE</role>
<aff id="A1">School of Industrial Engineering, Information Systems, Eindhoven University of Technology, Eindhoven, 5600 MB, the Netherlands.<email>g.acampora@tue.nl</email>
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<contrib contrib-type="author"><name><surname>Cook</surname>
<given-names>Diane J.</given-names>
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<role>Fellow, IEEE</role>
<aff id="A2">Department of Electrical and Computer Engineering, Washington State University, Pullman, WA, 99164, US.<email>cook@eecs.wsu.edu</email>
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<contrib contrib-type="author"><name><surname>Rashidi</surname>
<given-names>Parisa</given-names>
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<role>Member, IEEE</role>
<aff id="A3">Biomedical Informatics at Feinberg school of Medicine at Northwestern University, Chicago, IL, 60611, US.<email>parisa.rashidi@northwestern.edu</email>
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<contrib contrib-type="author"><name><surname>Vasilakos</surname>
<given-names>Athanasios V.</given-names>
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<role>Member, IEEE</role>
<aff id="A4">Department of Computer and Telecommunications Engineering, University of Western Macedonia, Greece.<email>vasilako@ath.forthnet.gr</email>
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<pub-date pub-type="nihms-submitted"><day>16</day>
<month>7</month>
<year>2013</year>
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<pub-date pub-type="epub"><day>15</day>
<month>8</month>
<year>2013</year>
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<month>12</month>
<year>2013</year>
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<pub-date pub-type="pmc-release"><day>13</day>
<month>1</month>
<year>2014</year>
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<volume>101</volume>
<issue>12</issue>
<fpage>2470</fpage>
<lpage>2494</lpage>
<pmc-comment>elocation-id from pubmed: 10.1109/JPROC.2013.2262913</pmc-comment>
<abstract><p id="P1">Ambient Intelligence (AmI) is a new paradigm in information technology aimed at empowering people’s capabilities by the means of digital environments that are sensitive, adaptive, and responsive to human needs, habits, gestures, and emotions. This futuristic vision of daily environment will enable innovative human-machine interactions characterized by pervasive, unobtrusive and anticipatory communications. Such innovative interaction paradigms make ambient intelligence technology a suitable candidate for developing various real life solutions, including in the health care domain. This survey will discuss the emergence of ambient intelligence (AmI) techniques in the health care domain, in order to provide the research community with the necessary background. We will examine the infrastructure and technology required for achieving the vision of ambient intelligence, such as smart environments and wearable medical devices. We will summarize of the state of the art artificial intelligence methodologies used for developing AmI system in the health care domain, including various learning techniques (for learning from user interaction), reasoning techniques (for reasoning about users’ goals and intensions) and planning techniques (for planning activities and interactions). We will also discuss how AmI technology might support people affected by various physical or mental disabilities or chronic disease. Finally, we will point to some of the successful case studies in the area and we will look at the current and future challenges to draw upon the possible future research paths.</p>
</abstract>
<kwd-group><title>Index Terms</title>
<kwd>Ambient Intelligence</kwd>
<kwd>Health Care</kwd>
<kwd>Smart Environments</kwd>
<kwd>Sensor Networks</kwd>
</kwd-group>
<funding-group><award-group><funding-source country="United States">National Institute of Biomedical Imaging and Bioengineering : NIBIB</funding-source>
<award-id>R01 EB015853 || EB</award-id>
</award-group>
<award-group><funding-source country="United States">National Institute of Biomedical Imaging and Bioengineering : NIBIB</funding-source>
<award-id>R01 EB009675 || EB</award-id>
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