Automatic 'Timed-Up and Go' (TUG) test segmentation
Name
1078148969-MIT.pdf
Description
Full printable version
Size
1.46 MB
Format
Adobe PDF
Checksum (MD5)
3a8297be16cdee182626bc0887d38715
Author(s)
Green, Ari M
Advisor(s)
Randall Davis.
Alternative Title
Automatic TUG test segmentation
Date Issued
2018
Publisher
Massachusetts Institute of Technology
Abstract
The Timed-Up and Go test (TUG) is a well-known medical test that is used as an indicator of mental and physical health. I developed the TUG-Segmenter, an automatic segmentation tool that can divide recorded TUG test data into the six main phases of the test: Sitting, Standing-Up, Walking-Forward, Turning, Walking-Back, and Sitting-Down. I created an annotation tool as well that greatly speeds up the creation of ground truth from TUG test data. Using both these tools I was able to evaluate the accuracy of the TUG-Segmenter in terms of the duration of the segmented phases ( 83.4 % accurate ) and the start times of the segmented phases ( 83.6 % accurate). Lastly, I found a 0.3 cm difference for jitteriness and an 8.5 mm/s difference for speed between healthy elderly subjects and healthy young subjects when comparing the features extracted from the individual TUG test phases.
Description
Thesis: M. Eng., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2018.
This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.
Cataloged from student-submitted PDF version of thesis.
Includes bibliographical references (pages 44-45).
Subjects
Electrical Engineering and Computer Science.
MIT Department
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
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