Level of Agreement between the MotionMetrix System and an Optoelectronic Motion Capture System for Walking and Running Gait Measurements

• Published in: Sensors (Basel, Switzerland) Switzerland), 2023-05, Vol.23 (10), p.4576
• Main Authors: Jaén-Carrillo, Diego, García-Pinillos, Felipe, Chicano-Gutiérrez, José M, Pérez-Castilla, Alejandro, Soto-Hermoso, Víctor, Molina-Molina, Alejandro, Ruiz-Alias, Santiago A
• Format: Article
• Language: English
• Subjects: analysis; Bias; Biomechanics; Calibration; Cameras; Computer animation; Computer programs; Data collection; Fitness equipment; Gait; Humans; Knee; Laboratories; Locomotion; markerless; Measurement; motion; Motion Capture; Open source software; Optoelectronics; Optoelectronics industry; reliability; Running; Sensors; Software packages; Standard error; Thigh; Walking; Young Adult; Young adults
• ISSN: 1424-8220; 1424-8220
• DOI: 10.3390/s23104576

Markerless motion capture systems (MCS) have been developed as an alternative solution to overcome the limitations of 3D MCS as they provide a more practical and efficient setup process given, among other factors, the lack of sensors attached to the body. However, this might affect the accuracy of the measures recorded. Thus, this study is aimed at evaluating the level of agreement between a markerless MSC (i.e., MotionMetrix) and an optoelectronic MCS (i.e., Qualisys). For such purpose, 24 healthy young adults were assessed for walking (at 5 km/h) and running (at 10 and 15 km/h) in a single session. The parameters obtained from MotionMetrix and Qualisys were tested in terms of level of agreement. When walking at 5 km/h, the MotionMetrix system significantly underestimated the stance and swing phases, as well as the load and pre-swing phases ( < 0.05) reporting also relatively low systematic bias (i.e., ≤ -0.03 s) and standard error of the estimate (SEE) (i.e., ≤0.02 s). The level of agreement between measurements was perfect (r > 0.9) for step length left and cadence and very large (r > 0.7) for step time left, gait cycle, and stride length. Regarding running at 10 km/h, bias and SEE analysis revealed significant differences for most of the variables except for stride time, rate and length, swing knee flexion for both legs, and thigh flexion left. The level of agreement between measurements was very large (r > 0.7) for stride time and rate, stride length, and vertical displacement. At 15 km/h, bias and SEE revealed significant differences for vertical displacement, landing knee flexion for both legs, stance knee flexion left, thigh flexion, and extension for both legs. The level of agreement between measurements in running at 15 km/h was almost perfect (r > 0.9) when comparing Qualisys and MotionMetrix parameters for stride time and rate, and stride length. The agreement between the two motion capture systems varied for different variables and speeds of locomotion, with some variables demonstrating high agreement while others showed poor agreement. Nonetheless, the findings presented here suggest that the MotionMetrix system is a promising option for sports practitioners and clinicians interested in measuring gait variables, particularly in the contexts examined in the study.