Massachusetts Institute of Technology
An Effective Platform for Assessing Cognitive Health
Abstract
dc:description.abstractOver the last two decades, mortality rates due to Alzheimer’s disease and related dementias (ADRD) have more than doubled in the United States. Currently available treatments for Alzheimer’s disease are more effective in the disease’s earlier stages, but making early diagnoses remains difficult. The most common method for diagnosing early-stage ADRD involves routine cognitive assessments under the supervision of a medical professional, a costly and time-consuming process. Furthermore, these assessments are often administered with pen and paper, making it difficult to measure many behaviors expressed by the patient. In this work, we develop an app for a tablet computer and stylus that administers novel variations of three established cognitive assessments: the Clock Drawing Test, the Maze Test, and the Symbol Digit Test. The app aims to replicate the role of a human administrator by providing instructions and correcting mistakes as patients complete each assessment. It also collects a wealth of data, such as pen strokes and patient movements, that can be used to aid medical professionals in making an accurate diagnosis. Combined, these innovations make it easy for patients to routinely complete assessments at home, on their own devices. We hope this reduces barriers toward diagnosing early-stage ADRD.
Degree
thesis:*- Name thesis:degree_name
- Master
- Department dc:contributor.department
- Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
- Grantor dc:publisher
- Massachusetts Institute of Technology
- Year dc:date.issued
- 2023
Author and committee
dc:creator, dc:contributor.*- Author dc:creator
-
- Cook, Jack
- Advisors dc:contributor.advisor
-
- Davis, Randall
- Penney, Dana
Rights
dc:rights- Statement dc:rights
-
- In Copyright - Educational Use Permitted
- Copyright MIT
- Licence dc:rights.uri
Identifiers
dc:identifier.*- Handle dc:identifier.uri
- https://hdl.handle.net/1721.1/150199
- OAI identifier oai:identifier
- oai:dspace.mit.edu:1721.1/150199