Effect of Walking Speed on the Reliability of a Smartphone-Based Markerless Gait Analysis System

Highlights: This study tested OpenCap, a smartphone app that tracks movement without markers, by comparing it to a traditional setup at different walking speeds. OpenCap was really reliable for measuring movement timing and joint angles, with errors usually under 2°. However, it was less accurate for joint range of motion at higher speeds, especially at the hip and ankle. Overall, OpenCap is a convenient tool for gait analysis, but be cautious when looking at ROM at faster speeds. What are the main findings? OpenCap showed excellent agreement with MoCap for spatiotemporal gait parameters and continuous joint kinematics across different walking speeds. Discrete joint range of motion (especially at the hip and ankle) exhibited lower and speed-dependent reliability, although systematic biases remained small and clinically acceptable. What is the implication of the main finding? OpenCap can be reliably applied for gait assessment and monitoring of spatiotemporal and continuous kinematic variables across various walking speeds. Clinicians should interpret range of motion outcomes with caution at higher speeds, as their accuracy decreases compared with marker-based measurements. Quantitative gait analysis is essential for understanding motor function and guiding clinical decisions. While marker-based motion capture (MoCap) systems are accurate, they are costly and require specialized facilities. OpenCap, a markerless alternative, offers a more accessible approach; however, its reliability across different walking speeds remains uncertain. This study assessed the agreement between OpenCap and MoCap in measuring spatiotemporal parameters, joint kinematics, and center of mass (CoM) displacement during level walking at three speeds: slow, self-selected, and fast. Fifteen healthy adults performed multiple trials simultaneously, recorded by both systems. Agreement was analyzed using intraclass correlation coefficients (ICC), minimal detectable change (MDC), Bland–Altman analyses, root mean square error (RMSE), Statistical Parametric Mapping (SPM), and repeated-measures ANOVA. Results indicated excellent agreement for spatiotemporal variables (ICC ≥ 0.95) and high consistency for joint waveforms (RMSE < 2°) and CoM displacement (RMSE < 6 mm) across all speeds. However, the joint range of motion (ROM) showed lower reliability, especially at the hip and ankle, at higher speeds. ANOVA revealed no significant System × Speed interactions for most variables, though a significant effect of speed was noted, with OpenCap underestimating walking speed more at fast speeds. Overall, OpenCap is a valuable tool for gait assessment, very accurate for spatiotemporal data and CoM displacement. Still, caution should be taken when interpreting joint kinematics and speed at different walking speeds.