{"id":{"repo_id":"mit","oai_identifier":"oai:dspace.mit.edu:1721.1/150199"},"canonical_url":"https://search.dev.ndltd.org/etd/mit/oai:dspace.mit.edu:1721.1/150199","repository":{"repo_id":"mit","name":"MIT","base_url":"https://dspace.mit.edu/oai/request"},"display":{"title":"An Effective Platform for Assessing Cognitive Health","abstract":"Over 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.","abstract_html":"Over 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.","abstract_has_math":false,"creators":["Cook, Jack"],"institution":"Massachusetts Institute of Technology","degree_name":"Master","degree_level":null,"degree_discipline":null,"degree_department":"Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science","school":null,"contributors":[],"advisors":["Davis, Randall","Penney, Dana"],"committee_chairs":[],"committee_members":[],"year":2023,"date_issued":"2023-02","date_published":"2023-02","updated_at":"2026-07-22T22:21:03Z","subjects":[],"languages":[],"rights":["In Copyright - Educational Use Permitted","Copyright MIT"],"rights_urls":["http://rightsstatements.org/page/InC-EDU/1.0/"],"identifier_entries":[]},"links":{"outbound_url":"https://hdl.handle.net/1721.1/150199","outbound_label":"Handle","outbound_source":"dc:identifier.uri"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor.advisor","label":"Advisor","values":["Davis, Randall","Penney, Dana"]},{"key":"dc:contributor.department","label":"Department","values":["Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science"]},{"key":"dc:creator","label":"Author","values":["Cook, Jack"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date.accessioned","label":"Dc Date Accessioned","values":["2023-03-31T14:39:08Z"]},{"key":"dc:date.available","label":"Dc Date Available","values":["2023-03-31T14:39:08Z"]},{"key":"dc:date.issued","label":"Date","values":["2023-02"]},{"key":"dc:publisher","label":"Institution","values":["Massachusetts Institute of Technology"]},{"key":"dc:type","label":"Dc Type","values":["Thesis"]},{"key":"thesis:degree_name","label":"Degree Name","values":["Master","Master of Engineering in Electrical Engineering and Computer Science"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:rights","label":"Dc Rights","values":["In Copyright - Educational Use Permitted","Copyright MIT"]},{"key":"dc:rights.uri","label":"Rights URI","values":["http://rightsstatements.org/page/InC-EDU/1.0/"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier.uri","label":"Identifier URI","values":["https://hdl.handle.net/1721.1/150199"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description.abstract","label":"Abstract","values":["Over 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."]},{"key":"dc:description.degree","label":"Dc Description Degree","values":["M.Eng."]},{"key":"dc:title","label":"Title","values":["An Effective Platform for Assessing Cognitive Health"]}]}],"canonical_facts":{"dc:contributor.advisor":["Davis, Randall","Penney, Dana"],"dc:contributor.department":["Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science"],"dc:creator":["Cook, Jack"],"dc:date.accessioned":["2023-03-31T14:39:08Z"],"dc:date.available":["2023-03-31T14:39:08Z"],"dc:date.issued":["2023-02"],"dc:description.abstract":["Over 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."],"dc:description.degree":["M.Eng."],"dc:identifier.uri":["https://hdl.handle.net/1721.1/150199"],"dc:publisher":["Massachusetts Institute of Technology"],"dc:rights":["In Copyright - Educational Use Permitted","Copyright MIT"],"dc:rights.uri":["http://rightsstatements.org/page/InC-EDU/1.0/"],"dc:title":["An Effective Platform for Assessing Cognitive Health"],"dc:type":["Thesis"],"thesis:degree_name":["Master","Master of Engineering in Electrical Engineering and Computer Science"]},"updated_at":"2026-07-22T22:21:03Z"}