The accuracy, validity and reliability of Theia3D markerless motion capture for studying the biomechanics of human movement: A systematic review

Recent advancements in computer vision recognition combined with the use of pose estimation algorithms has led to a rapid increase in the use of 3D video-based markerless (ML) motion capture to study human movement. One such prominent system is Theia3D. To determine the accuracy, validity, and reliability of Theia3D, a systematic literature review was conducted across five electronic databases using the PRISMA (Preferred Reporting Items for Systematic Review and Meta-Analysis) guidelines. Studies were included if they investigated the accuracy, validity, or reliability of Theia3D against a standardised method and reported on at least one biomechanical measure. A modified version of COSMIN (Consensus-based Standards for the Selection of Health Measurement Instruments) and GRADE (Grading of Recommendations Assessment, Development, and Evaluation) were used to evaluate the quality of evidence. Sixteen studies met the inclusion criteria, the majority of which assessed the validity of kinematics during gait or running. Pooled lower limb kinematics showed reasonable accuracy, whilst hip flexion/extension and rotations of the lower limb joints in the transverse plane suggests poor accuracy. Most spatiotemporal gait parameters measured using Theia3D demonstrated excellent validity (Intraclass correlation coefficient (ICC) > 0.9) and inter-session reliability (gait speed, Standard Error of Measurement (SEM) ≤ 0.07 m/s; step/stride length, SEM ≤ 0.06 m; ICC > 0.95). The accuracy, validity, and reliability of Theia3D used in the biomechanical analysis of functional tasks and in different population groups shows promise. However, there is a need for improved methods by which to compare data and a standardisation of biomechanical modelling approaches.