Ph.D. Defense of Dissertation Announcement
Title: The ClockMe System: Computer-Assisted Screening Tool for Dementia
 
 
Hyungsin Kim
Human Centered Computing Program
School of Interactive Computing
College of Computing
Georgia Institute of Technology
hyungsin@gatech.edu

Date: Thursday, December 6, 2012
Time: 5:00pm - 7:00pm EST
Location: Technology Square Research Building (TSRB), 222
 
 
Committee:

• Dr. Ellen Yi-Luen Do (Advisor, School of Interactive Computing & School of Industrial Design)

• Dr. Jim Foley (School of Interactive Computing)

• Dr. Mark Guzdial (School of Interactive Computing)

• Dr. Janet Cellar (Emory Alzheimer’s Disease Research Center)

• Dr. Michael J. Jacobson (The University of Sydney)

 
 Abstract:
Due to the fastest growing senior population, age-related cognitive impairments, including Alzheimer’s disease, are becoming among the most common diseases in the United States. Currently, prevention through delay is considered the best way to tackle Alzheimer’s disease and related dementia because there is no known cure for those diseases. Early detection is crucial, as screening individuals with Mild Cognitive Impairment may delay its progression and prevent it from developing. For my dissertation work, I investigate how computing technologies can help medical practitioners detect and monitor cognitive impairment due to dementia, and I develop a computerized sketch-based screening tool.
 
In this dissertation, I present the design, implementation, and evaluation of the ClockMe System, a computerized Clock Drawing Test. The traditional Clock Drawing Test (CDT) is a rapid and reliable instrument for the early detection of cognitive dysfunction. Neurologists often notice missing or extra numbers in drawings from people with cognitive impairments and use scoring criteria to make a diagnosis and treatment plan. The ClockMe System includes two different applications - (1) the ClockReader for the patients who take the Clock Drawing Test and (2) the ClockAnalyzer for clinicians who use the CDT results to make a diagnosis or to monitor patients.
 
The contributions of this research are (1) the creation of a computerized screening tool that can help clinicians identify cognitive impairment through a more accessible and quick-and-easy screening process; (2) the delivery of computer-collected novel behavioral data, which may be able to offer new insights and understanding of a patient’s cognition; (3) an in-depth understanding of different stakeholders and the identification of their common use needs and desires within a complicated healthcare workflow system; and (4) the triangulation of multiple data collection methods such as ethnographical observations, interviews, focus group meetings, and quantitative data from a user survey in a real-world deployment study.