Integrating digitizing pen technology and machine learning with the Clock Drawing Test

The Clock Drawing Test (CDT) is a medical test for neurodegenerative diseases that has been proven to have high diagnostic value due to its ease of administration and accurate results. In order to standardize the administration process and utilize the most current machine learning tools for analysis of CDT results, the digitizing pen has been used to computerize this diagnostic test. In order to successfully integrate digitizing pen technology with the CDT, a digit recognition algorithm was developed to reduce the need for manual classification of the data collected and maintain the ease of administration of the test. In addition, the Multitool Data Analysis Package was developed to aid in the exploratory data analysis stage of the CDT. This package combines several existing machine learning tools with two new algorithm implementations to provide an easy-to-use platform for discovering trends it CDT data.

Department dc:contributor.department

Massachusetts Institute of Technology. Dept. of Electrical Engineering and Computer Science.

Grantor dc:publisher

Massachusetts Institute of Technology

Year dc:date.issued

2010

Author dc:creator

• Felch, Kristen (Kristen M.)

Advisor dc:contributor.advisor

• Randall Davis.

• Electrical Engineering and Computer Science.

Statement dc:rights

• M.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission.

Licence dc:rights.uri

• http://dspace.mit.edu/handle/1721.1/7582

Language dc:language.iso

eng

Handle dc:identifier.uri

http://hdl.handle.net/1721.1/61285

OAI identifier oai:identifier

oai:dspace.mit.edu:1721.1/61285