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Dynamic online computerized neuropsychological testing system

Dynamic online computerized neuropsychological testing system As the average overall life expectancy for individuals in the U.S. continues to increase along with the aging baby boomers, so too does the need for accessible healthcare solutions. It is reported that aging is one of the greatest known risk factors for the onset of cognitive impairment (CI), such as Alzheimer's disease. For individuals with more severe forms of CI, the inability to effectively perform mental tasks required for independent daily living can severely limit one's functionality. Traditional solutions for early detection of cognitive decline and impairment can be inaccessible, expensive, and time consuming. The overarching goal of this dissertation is to develop a dynamic online computerized neuropsychological testing system capable of rapidly tracking an individual's cognitive performance throughout the user's daily or weekly schedule in a way that is the least intrusive. By utilizing embedded microsensors within tablet devices, the proposed system will capture ambient and behavioral data pertinent to the real-world contexts and times of testing. Such sensor data has the potential to compliment psychometric results by providing insight into the contextual factors relevant to the user's testing efficacy and performance. In addition, the investigation into the accessibility issues faced by older adults will lead to improved neuropsychological testing interfaces. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png ACM SIGACCESS Accessibility and Computing Association for Computing Machinery

Dynamic online computerized neuropsychological testing system

ACM SIGACCESS Accessibility and Computing , Volume (114): 6 – Mar 16, 2016

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Publisher
Association for Computing Machinery
Copyright
Copyright © 2016 Copyright is held by the owner/author(s)
ISSN
1558-2337
eISSN
1558-1187
DOI
10.1145/2904092.2904103
Publisher site
See Article on Publisher Site

Abstract

As the average overall life expectancy for individuals in the U.S. continues to increase along with the aging baby boomers, so too does the need for accessible healthcare solutions. It is reported that aging is one of the greatest known risk factors for the onset of cognitive impairment (CI), such as Alzheimer's disease. For individuals with more severe forms of CI, the inability to effectively perform mental tasks required for independent daily living can severely limit one's functionality. Traditional solutions for early detection of cognitive decline and impairment can be inaccessible, expensive, and time consuming. The overarching goal of this dissertation is to develop a dynamic online computerized neuropsychological testing system capable of rapidly tracking an individual's cognitive performance throughout the user's daily or weekly schedule in a way that is the least intrusive. By utilizing embedded microsensors within tablet devices, the proposed system will capture ambient and behavioral data pertinent to the real-world contexts and times of testing. Such sensor data has the potential to compliment psychometric results by providing insight into the contextual factors relevant to the user's testing efficacy and performance. In addition, the investigation into the accessibility issues faced by older adults will lead to improved neuropsychological testing interfaces.

Journal

ACM SIGACCESS Accessibility and ComputingAssociation for Computing Machinery

Published: Mar 16, 2016

References