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dc.contributor.authorLuperto, M
dc.contributor.authorRomeo, M
dc.contributor.authorLunardini, F
dc.contributor.authorBasilico, N
dc.contributor.authorAbbate, C
dc.contributor.authorJones, Ray
dc.contributor.authorCangelosi, Angelo
dc.contributor.authorFerrante, S
dc.contributor.authorBorghese, NA
dc.date.accessioned2022-02-08T17:11:25Z
dc.date.available2022-02-08T17:11:25Z
dc.date.issued2019-11
dc.identifier.isbn9781728140049
dc.identifier.issn2153-0858
dc.identifier.issn2153-0866
dc.identifier.urihttp://hdl.handle.net/10026.1/18724
dc.description.abstract

The employment of Social Assistive Robots (SARs) for monitoring elderly users represents a valuable gateway for at-home assistance. Their deployment in the house of the users can provide effective opportunities for early detection of Mild Cognitive Impairment (MCI), a condition of increasing impact in our aging society, by means of digitalized cognitive tests. In this work, we present a system where a specific set of cognitive tests is selected, digitalized, and integrated with a robotic assistant, whose task is the guidance and supervision of the users during the completion of such tests. The system is then evaluated by means of an experimental study involving potential future users, in order to assess its acceptability and identify key directions for technical improvements.

dc.format.extent1257-1264
dc.language.isoen
dc.publisherIEEE
dc.subjectBrain Disorders
dc.subjectAlzheimer's Disease including Alzheimer's Disease Related Dementias (AD/ADRD)
dc.subjectDementia
dc.subjectNeurodegenerative
dc.subjectAcquired Cognitive Impairment
dc.subjectAging
dc.subjectClinical Research
dc.subjectBehavioral and Social Science
dc.subjectAlzheimer's Disease
dc.titleEvaluating the Acceptability of Assistive Robots for Early Detection of Mild Cognitive Impairment
dc.typeconference
dc.typeConference Proceeding
plymouth.author-urlhttps://www.webofscience.com/api/gateway?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:000544658401009&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=11bb513d99f797142bcfeffcc58ea008
plymouth.date-start2019-11-03
plymouth.date-finish2019-11-08
plymouth.conference-name2019 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)
plymouth.publication-statusPublished
plymouth.journal2019 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)
dc.identifier.doi10.1109/iros40897.2019.8968234
plymouth.organisational-group/Plymouth
plymouth.organisational-group/Plymouth/Faculty of Health
plymouth.organisational-group/Plymouth/Faculty of Health/School of Nursing and Midwifery
plymouth.organisational-group/Plymouth/Faculty of Science and Engineering
plymouth.organisational-group/Plymouth/REF 2021 Researchers by UoA
plymouth.organisational-group/Plymouth/REF 2021 Researchers by UoA/UoA03 Allied Health Professions, Dentistry, Nursing and Pharmacy
plymouth.organisational-group/Plymouth/Research Groups
plymouth.organisational-group/Plymouth/Research Groups/Institute of Health and Community
plymouth.organisational-group/Plymouth/Research Groups/Marine Institute
plymouth.organisational-group/Plymouth/Users by role
plymouth.organisational-group/Plymouth/Users by role/Academics
dc.identifier.eissn2153-0866
dc.rights.embargoperiodNot known
rioxxterms.versionofrecord10.1109/iros40897.2019.8968234
rioxxterms.licenseref.urihttp://www.rioxx.net/licenses/all-rights-reserved
rioxxterms.typeConference Paper/Proceeding/Abstract


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