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dc.contributor.advisorDavis, Randall
dc.contributor.advisorPenney, Dana L.
dc.contributor.authorAscanio Alino, Maria
dc.date.accessioned2023-07-31T19:39:02Z
dc.date.available2023-07-31T19:39:02Z
dc.date.issued2023-06
dc.date.submitted2023-06-06T16:35:24.711Z
dc.identifier.urihttps://hdl.handle.net/1721.1/151429
dc.description.abstractEarly detection of cognitive impairment enables more effective treatments and better outcomes. Despite advances in cognitive assessments, traditional assessment methods are often time-consuming and require extensive medical expertise, making it challenging to reach many patients and limiting data availability. This thesis explores an innovative solution - an advanced, unified iPad platform designed to administer tests in a way that embodies some of the skills of a practiced clinician. The platform provides faster and self-administered medical assessments with granular testing information, allowing for early detection of cognitive impairment. This application streamlines the assessment process and increases patient access, providing valuable data for ongoing research and treatment development. In addition, the platform’s ease of use, interactivity, and accessibility make it a valuable tool for both medical professionals and patients, as it embodies some clinical expertise enabling it to interact in ways similar to a human examiner. This thesis provides an in-depth examination of this cutting-edge platform, describing its benefits and its potential to improve the early detection of cognitive impairment.
dc.publisherMassachusetts Institute of Technology
dc.rightsIn Copyright - Educational Use Permitted
dc.rightsCopyright retained by author(s)
dc.rights.urihttps://rightsstatements.org/page/InC-EDU/1.0/
dc.titleTesting for Subtle Cognitive Impairments in aClinically Informed iPad Platform
dc.typeThesis
dc.description.degreeM.Eng.
dc.contributor.departmentMassachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
mit.thesis.degreeMaster
thesis.degree.nameMaster of Engineering in Electrical Engineering and Computer Science


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