Assessing the implementation of the REference FRame Alignment MEthod to compare differences in tibio-femoral kinematics during gait using five different marker sets

<b>Introduction:</b> Gait analysis plays a key role in improving our understanding of joint kinematics during locomotion, often by leveraging marker-based systems. Accessibility to marker-based systems is nevertheless limited, as they are usually associated with high equipment costs, large space requirements, and the need for lengthy data processing. These restrictions have therefore driven the need for tools that facilitate the interpretation and comparison of openly accessible kinematic datasets, even in cases where the data have been collected using distinct equipment and/or protocols. <b>Methods:</b> This study addresses variations in kinematic data arising from the use of different marker sets, focusing specifically on the tibio-femoral joint kinematics of 15 healthy subjects during treadmill walking. By simultaneously capturing joint motion using five distinct marker sets, we were able to confirm the presence of visible differences in the raw kinematic outputs prior to data optimisation, despite their representing the same underlying motion. We subsequently implemented the REference FRame Alignment MEthod (REFRAME) to account for signal differences linked to inconsistent local reference frame orientations. <b>Results and Discussion:</b> After REFRAME optimisation, improved convergence of the kinematic signals was observed, confirming that the differences observed in raw signals stemmed primarily from differing reference frame orientations, rather than genuine variations in joint motion. This study highlights REFRAME's potential to enhance comparability across biomechanical datasets, thus facilitating robust inter-laboratory comparisons and supporting reliable interpretations of data in clinical and research applications.