Background: Gait analysis is widely utilized for the diagnosis and prognosis of various diseases. Recently, innovative convenient markerless motion capture systems have been developed to replace the traditional marker-based three-dimensional motion capture systems.
Purpose: s:This study is to evaluate the test-retest reliability of a novel video-based markerless motion capture system(Watrix, China) and to assess its concordance with a three-dimensional motion analysis system (BTS, Italy) in a population of young healthy subjects.
Participants and methods: Our study included 36 healthy adult participants. Each subject underwent three assessments using Watrix system and BTS system. To evaluate the validity and reliability of the measurements, we employed paired-sample t-tests, Wilcoxon signed-rank tests, intra-class correlation coefficients, Bland-Altman analysis and Passing Bablok regression analysis.
Results: Both intra-rater and inter-rater reliability demonstrated moderate to excellent correlations, with intraclass correlation coefficient (ICC) values ranging from 0.507 to 0.936, except for cadence(ICC = 0.233). The validity exhibited a good correlation for sagittal plane parameters(ICC ranging from 0.818 to 0.883) and a moderate correlation for the coronal and transverse parameters (ICC ranging from 0.520 to 0.608). The Passing Bablok linear regression analysis indicated that the confidence intervals for the intercepts of all parameters included 0, while the confidence intervals for the slopes of most parameters encompassed 1 except for step width, pelvic obliquity, and hip adduction-abduction angle. The implementation of Watrix system significantly decreased the testing duration for participants.
Conclusions: The Watrix system demonstrated relatively high test-retest reliability. The Watrix and BTS systems demonstrated moderate to good agreement for most parameters. However, the Watrix system tended to underestimate coronal and transverse plane parameters, resulting in lower consistency. In addition, the markerless motion capture system greatly reduces the testing duration.Optimizing algorithms to improve recognition accuracy remains the main direction of research.
