Automated Functional and Behavioral Health Assessment of Older Adults with Dementia

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dc.contributor.authorAlam, Mohammad Arif Ul
dc.contributor.authorRoy, Nirmalya
dc.contributor.authorHolmes, Sarah
dc.contributor.authorGangopadhyay, Aryya
dc.contributor.authorGalik, Elizabeth
dc.date.accessioned2018-09-04T18:22:57Z
dc.date.available2018-09-04T18:22:57Z
dc.date.issued2016-08-18
dc.description© 2016 IEEE; 2016 IEEE First International Conference on Connected Health: Applications, Systems and Engineering Technologies (CHASE)en_US
dc.description.abstractDementia is a clinical syndrome of cognitive deficits that involves both memory and functional impairments. While disruptions in cognition is a striking feature of dementia, it is also closely coupled with changes in functional and behavioral health of older adults. In this paper, we investigate the challenges of improving the automatic assessment of dementia, by better exploiting the emerging physiological sensors in conjunction with ambient sensors in a real field environment with IRB approval. We hypothesize that the cognitive health of older individuals can be estimated by tracking their daily activities and mental arousal states. We employ signal processing on wearable sensor data streams (e.g., Electrodermal Activity (EDA), Photoplethysmogram (PPG), accelerometer (ACC)) and machine learning algorithms to assess cognitive impairments and its correlation with functional health decline. To validate our approach, we quantify the score of machine learning, survey and observation based Activities of Daily Living (ADLs) and signal processing based mental arousal state, respectively for functional and behavioral health measures among 17 older adults living in a continuing care retirement community in Baltimore. We compare clinically observed scores with technology guided automated scores using both machine learning and statistical techniques.en_US
dc.description.sponsorshipThis work is supported by UMB-UMBC Research and Innovation Partnership grant.en_US
dc.description.urihttps://ieeexplore.ieee.org/document/7545827/en_US
dc.format.extent10PAGESen_US
dc.genreconference papers and proceedings preprintsen_US
dc.identifierdoi:10.13016/M21C1TK0P
dc.identifier.citationM. A. U. Alam, N. Roy, S. Holmes, A. Gangopadhyay and E. Galik, "Automated Functional and Behavioral Health Assessment of Older Adults with Dementia," 2016 IEEE First International Conference on Connected Health: Applications, Systems and Engineering Technologies (CHASE), Washington, DC, 2016, pp. 140-149.en_US
dc.identifier.uri10.1109/CHASE.2016.16
dc.identifier.urihttp://hdl.handle.net/11603/11210
dc.language.isoen_USen_US
dc.publisherIEEEen_US
dc.relation.isAvailableAtThe University of Maryland, Baltimore County (UMBC)
dc.relation.ispartofUMBC Information Systems Department Collection
dc.relation.ispartofUMBC Faculty Collection
dc.relation.ispartofUMBC Gerontology Collection
dc.rightsThis item may be protected under Title 17 of the U.S. Copyright Law. It is made available by UMBC for non-commercial research and education. For permission to publish or reproduce, please contact the author.
dc.subjectBiomedical monitoringen_US
dc.subjectDementiaen_US
dc.subjectMonitoringen_US
dc.subjectSkinen_US
dc.subjectSensorsen_US
dc.subjectSmart homesen_US
dc.subjectHeart rateen_US
dc.subjectMobile Pervasive & Sensor Computing Laben_US
dc.titleAutomated Functional and Behavioral Health Assessment of Older Adults with Dementiaen_US
dc.typeTexten_US

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