DocumentCode :
621846
Title :
Mapping Kinect-based in-home gait speed to TUG time: A methodology to facilitate clinical interpretation
Author :
Stone, Erik E. ; Skubic, Marjorie
Author_Institution :
Dept. of Electr. & Comput. Eng., Univ. of Missouri, Columbia, MO, USA
fYear :
2013
fDate :
5-8 May 2013
Firstpage :
57
Lastpage :
64
Abstract :
A methodology for mapping in-home gait speed (IGS), measured unobtrusively and continuously in the homes of older adults, to Timed-Up-and-Go (TUG) time is presented. A Kinect-based gait system was used to collect in-home gait data on 15 older adults over time periods of up to 16 months. Concurrently, the participants completed a monthly clinician administered fall risk assessment protocol that included TUG and habitual gait speed (HGS) tests. A theoretical analysis of expected performance is presented, and the performance of the IGS-based TUG estimates is compared against that of estimates based on HGS measured at the same time as the TUG. Results indicate that the IGS-based estimates are as accurate as the HGS-based estimates as compared to the observed TUG times. After filtering the TUG times to reduce noise, the IGS-based estimates are more accurate. The mapping of in-home sensor data to well studied domains facilitates clinical interpretation of the in-home data.
Keywords :
image sensors; medical computing; sensor fusion; HGS test; HGS-based estimate; IGS-based estimate; Kinect-based in-home gait speed; TUG time; clinical interpretation; gait data collection; habitual gait speed test; timed-up-and-go time; Analytical models; Atmospheric measurements; Monitoring; Particle measurements; Reliability; Time measurement; Kinect; TUG; Timed-Up-and-Go; fall risk; gait;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Pervasive Computing Technologies for Healthcare (PervasiveHealth), 2013 7th International Conference on
Conference_Location :
Venice
Print_ISBN :
978-1-4799-0296-5
Electronic_ISBN :
978-1-936968-80-0
Type :
conf
Filename :
6563903
Link To Document :
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