Research Article
Mapping Kinect-Based In-Home Gait Speed to TUG Time: A Methodology to Facilitate Clinical Interpretation
@INPROCEEDINGS{10.4108/icst.pervasivehealth.2013.252097, author={Erik Stone and Marjorie Skubic}, title={Mapping Kinect-Based In-Home Gait Speed to TUG Time: A Methodology to Facilitate Clinical Interpretation}, proceedings={7th International Conference on Pervasive Computing Technologies for Healthcare}, publisher={IEEE}, proceedings_a={PERVASIVEHEALTH}, year={2013}, month={5}, keywords={gait kinect fall risk tug timed-up-and-go}, doi={10.4108/icst.pervasivehealth.2013.252097} }- Erik Stone
Marjorie Skubic
Year: 2013
Mapping Kinect-Based In-Home Gait Speed to TUG Time: A Methodology to Facilitate Clinical Interpretation
PERVASIVEHEALTH
ICST
DOI: 10.4108/icst.pervasivehealth.2013.252097
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.