Accepted for/Published in: JMIR mHealth and uHealth
Date Submitted: Apr 20, 2020
Date Accepted: Sep 13, 2020
Warning: This is an author submission that is not peer-reviewed or edited. Preprints - unless they show as "accepted" - should not be relied on to guide clinical practice or health-related behavior and should not be reported in news media as established information.
Agreement between the spatiotemporal gait parameters from a markerless motion capture system and two different systems: treadmill-based photoelectric cell and high-speed video analysis
ABSTRACT
Background:
Markerless systems require no markers to be attached to the body, improving clinical feasibility and testing time. However, the lack of markers might affect the measurements’ accuracy
Objective:
This study aimed to determine the absolute reliability and concurrent validity of the Kinect™ system with the MotionMetrix™ software for spatiotemporal variables evaluation during running at comfortable velocity by comparing data with two widely used systems (i.e., OptoGait™ and high-speed video-analysis at 1,000 Hz)
Methods:
Twenty-five runners performed a running protocol on a treadmill at 12 km.h-1. The Kinect™-MotionMetrix™ combination reported spatiotemporal parameters during running (i.e. contact time [CT], flight time [FT], step frequency [SF] and step length [SL]) and were compared to two reference systems. The Kinect™-MotionMetrix™ system obtained higher coefficients of variation than the reference systems in every spatiotemporal parameter.
Results:
Regardless of the system, FT displayed the highest values (OptoGait™ 16.4%, video analysis 17.3% and MotionMetrix™ 23.2%). The rest of CVs reported were lower than 8.1%. The correlation analysis reported very large correlations (r>0.8, p<0.001) and almost a perfect association (ICC>0.81) between systems for all the spatiotemporal parameters, except for CT, which reported lower values. The Bland-Altman plots between systems revealed small systematic biases and random errors for SF and SL, but greater systematic biases and random errors for temporal parameters as compared with both OptoGait™ (CT: +3.0%, FT: -7.9%) and high-speed video analysis at 1,000 Hz (CT: +4.2%, FT: -11.3%). Accordingly, heteroscedasticity was found between systems for temporal parameters (r2>0.1).
Conclusions:
Therefore, the results indicate that the Kinect™-MotionMetrix™ combination slightly overestimates CT and strongly underestimates FT according to both OptoGait™ system and high-speed video analysis at 1,000 Hz, but it is a valid tool to measure SF and SL according to those reference systems. The results also question the reliability of this system for determining temporal parameters.
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