Evaluation of functional methods of joint centre determination for quasi-planar movement

Abstract

Functional methods identify joint centres as the centre of rotation (CoR) of two adjacent movements during an ad-hoc movement. The methods have been used for functionally determining hip joint centre in gait analysis and have revealed advantages compared to predictive regression techniques. However, the current implementation of functional methods hinders its application in clinical use when subjects have difficulties performing multi-plane movements over the required range. In this study, we systematically investigated whether functional methods can be used to localise the CoR during a quasi-planar movement. The effects of the following factors were analysed: the algorithms, the range and speed of the movement, marker cluster location, marker cluster size and distance to the joint centre. A mechanical linkage was used in our study to isolate the factors of interest and give insight to variation in implementation of functional methods. Our results showed the algorithms and cluster locations significantly affected the estimate results. For all algorithms, a significantly positive relationship between CoR errors and the distance of proximal cluster coordinate location to the joint centre along the medial-lateral direction was observed while the distal marker clusters were best located as close as possible to the joint centre. By optimising the analytical and experimental factors, the transformation algorithms achieved a root mean square error (RMSE) of 5.3 mm while the sphere fitting methods yielded the best estimation with an RMSE of 2.6 mm. The transformation algorithms performed better in presence of random noise and simulated soft tissue artefacts.

A strathclyde cluster model for gait kinematic measurement using functional methods: a study of inter-assessor reliability analysis with comparison to anatomical models

“…On the other side, the STA also plays a significant role in causing inaccuracies in the functional joint centre estimation (Kratzenstein et al 2012). The use of rigid marker clusters may improve the accuracy of functional methods by eliminating the marker cluster deformation, especially for the CTT method (Meng et al 2019). However, the STAs caused by the skin sliding cannot be ignored.…”

“…As shown in Figure 2(A), the pelvis coordinate origin was located at the midpoint of L/RASI (left/ right anterior superior iliac spine) and L/RPSI (left/ right posterior superior iliac spine) markers and the CTT was used to calculate the functional HJC. The KJC was determined using an optimised protocol from our previous study (Meng et al 2019). The origin of the proximal coordinate system T femur was shifted to the midpoint between the estimated HJC and the medial knee marker.…”

“…It may be due to difficulties in the precise location of the knee joint centre (KJC) when the joint is considered a modified hinged joint with reduced movement. Meng et al (2019) proposed an optimised functional method-based protocol for the determination of the KJC location during knee flexion/extension. Based on the previous work, the novel Strathclyde Functional Cluster Model (SFCM) was developed, in which joint kinematics were obtained with the joint centres (hip, knee and ankle) and helical axes of the knee and ankle joints determined functionally.…”

A regularized functional method to determine the hip joint center of rotation in subjects with limited range of motion

“…Since the HJC cannot be palpated, its location must be estimated by using regression approaches (called predictive methods) or functional methods from either marker data trials or medical images techniques (Kainz et al, 2017b). Regardless the method used to estimate the HJC location, for further built biomechanical models of human gait, such an estimate must be as accurate as possible (Bahl et al, 2019;Meng et al, 2019;Leboeuf et al, 2019).…”

“…Several functional methods have been proposed in the literature to compute the HJC (Leardini et al, 1999;Piazza et al, 2001;Gamage and Lasenby, 2002;Schwartz and Rozumalski, 2005;Ehrig et al, 2006). Most probably, the combination of accurate results with the fast computational time together with its implementation in one of the most important commercial software (Nexus from Vicon Motion Systems Ltd, Oxford, UK) had made the symmetrical center of rotation estimation (SCoRE) (Ehrig et al, 2006) with a Procruster algorithm be widely adopted in clinical settings (Rozumalski et al, 2013) Since the performance of functional methods in estimating HJC are sensitive to the complexity of the calibration movement task used (Meng et al, 2019), many studies have concluded that the multi-plane StarArc movement proposed 3 J o u r n a l P r e -p r o o f by Camomilla et al (2006) (Siston andDelp, 2006;Kainz et al, 2015) is the best calibration movement. Thus, accurate HJC estimation based on SCoRE for people with limited ROM is still an open challenge in the biomechanical community.…”