TY  - JOUR
PY  - 2018//
TI  - Validation of an ambient system for the measurement of gait parameters
JO  - Journal of biomechanics
A1  - Dubois, Amandine
A1  - Bresciani, Jean-Pierre
SP  - 175
EP  - 180
VL  - 69
IS  - 
N2  - Fall risk in elderly people is usually assessed using clinical tests. These tests consist in a subjective evaluation of gait performed by healthcare professionals, most of the time shortly after the first fall occurrence. We propose to complement this one-time, subjective evaluation, by a more quantitative analysis of the gait pattern using a Microsoft Kinect. To evaluate the potential of the Kinect sensor for such a quantitative gait analysis, we benchmarked its performance against that of a gold-standard motion capture system, namely the OptiTrack. The "Kinect" analysis relied on a home-made algorithm specifically developed for this sensor, whereas the OptiTrack analysis relied on the "built-in" OptiTrack algorithm. We measured different gait parameters as step length, step duration, cadence, and gait speed in twenty-five subjects, and compared the results respectively provided by the Kinect and OptiTrack systems. These comparisons were performed using Bland-Altman plot (95% bias and limits of agreement), percentage error, Spearman's correlation coefficient, concordance correlation coefficient and intra-class correlation. The agreement between the measurements made with the two motion capture systems was very high, demonstrating that associated with the right algorithm, the Kinect is a very reliable and valuable tool to analyze gait. Importantly, the measured spatio-temporal parameters varied significantly between age groups, step length and gait speed proving the most effective discriminating parameters. Kinect-monitoring and quantitative gait pattern analysis could therefore be routinely used to complete subjective clinical evaluation in order to improve fall risk assessment during rehabilitation.<br><br>Copyright © 2018 Elsevier Ltd. All rights reserved.<p />  <p>Language: en</p>
LA  - en
SN  - 0021-9290
UR  - http://dx.doi.org/10.1016/j.jbiomech.2018.01.024
ID  - ref1
ER  -