Hip joint centre location: An ex vivo study

The human hip joint is normally represented as a spherical hinge and its centre of rotation is used to construct femoral anatomical axes and to calculate hip joint moments. The estimate of the hip joint centre (HJC) position using a functional approach is affected by stereophotogrammetric errors and soft tissue artefacts. The aims of this study were (1) to assess the accuracy with which the HJC position can be located using stereophotogrammetry and (2) to investigate the effects of hip motion amplitude on this accuracy. Experiments were conducted on four adult cadavers. Cortical pins, each equipped with a marker cluster, were implanted in the pelvis and femur, and eight skin markers were attached to the thigh. Recordings were made while an operator rotated the hip joint exploiting the widest possible range of motion. For HJC determination, a proximal and a distal thigh skin marker cluster and two recent analytical methods, the quartic sphere fit (QFS) method and the symmetrical centre of rotation estimation (SCoRE) method, were used. Results showed that, when only stereophotogrammetric errors were taken into account, the analytical methods performed equally well. In presence of soft tissue artefacts, HJC errors highly varied among subjects, methods, and skin marker clusters (between 1.4 and 38.5 mm). As expected, larger errors were found in the subject with larger soft tissue artefacts. The QFS method and the distal cluster performed generally better and showed a mean HJC location accuracy better than 10 mm over all subjects. The analysis on the effect of hip movement amplitude revealed that a reduction of the amplitude does not improve the HJC location accuracy despite a decrease of the artefact amplitude.     

Statistical shape modelling versus linear scaling: Effects on predictions of hip joint centre location and muscle moment arms in people with hip osteoarthritis

Marker-based dynamic functional or regression methods are used to compute joint centre locations that can be used to improve linear scaling of the pelvis in musculoskeletal models, although large errors have been reported using these methods. This study aimed to investigate if statistical shape models could improve prediction of the hip joint centre (HJC) location. The inclusion of complete pelvis imaging data from computed tomography (CT) was also explored to determine if free-form deformation techniques could further improve HJC estimates. Mean Euclidean distance errors were calculated between HJC from CT and estimates from shape modelling methods, and functional- and regression-based linear scaling approaches. The HJC of a generic musculoskeletal model was also perturbed to compute the root-mean squared error (RMSE) of the hip muscle moment arms between the reference HJC obtained from CT and the different scaling methods. Shape modelling without medical imaging data significantly reduced HJC location error estimates (11.4 ± 3.3 mm) compared to functional (36.9 ± 17.5 mm, p = <0.001) and regression (31.2 ± 15 mm, p = <0.001) methods. The addition of complete pelvis imaging data to the shape modelling workflow further reduced HJC error estimates compared to no imaging (6.6 ± 3.1 mm, p = 0.002). Average RMSE were greatest for the hip flexor and extensor muscle groups using the functional (16.71 mm and 8.87 mm respectively) and regression methods (16.15 mm and 9.97 mm respectively). The effects on moment-arms were less substantial for the shape modelling methods, ranging from 0.05 to 3.2 mm. Shape modelling methods improved HJC location and muscle moment-arm estimates compared to linear scaling of musculoskeletal models in patients with hip osteoarthritis.     

Assessment of a greater trochanter-based method of locating the hip joint center

An alternative, yet unverified, predictive method that places the hip joint center (HJC) at one-quarter of the distance from the ipsolateral to the contralateral greater trochanter (GT method) is currently widely used in the biomechanics community. Therefore, the objective of this study was to confirm that this method is a viable option for estimating HJC coordinates. To accomplish this, HJC coordinates in the pelvic anatomical coordinate system were estimated via the GT method, a functional method, and the regression equations proposed by Bell et al. (1990). The HJC coordinated estimated by the functional method served as a baseline measurement. The results of this study demonstrate that all three methods evaluated offer repeatable estimates of HJC location. In comparison to the functional method, the GT method yielded a HJC estimate that was 7.6 mm medial, 12.2 mm posterior, and 4.8 mm proximal. On the other hand, the Bell regression equations estimated the HJC to be 2.6 mm medial, 7.2 mm posterior, and 21.7 mm proximal relative to the functional method. Additionally, the total 3D difference between the GT and functional methods was 23.5 mm compared to the 30.8 mm difference between the Bell and functional methods. These results suggest that the GT method is a viable option for estimating HJC coordinates.     

Prediction of the hip joint centre in adults, children, and patients with cerebral palsy based on magnetic resonance imaging

The location of the hip joint centre (HJC) is required for calculations of hip moments, the location and orientation of the femur, and muscle lengths and lever arms. In clinical gait analysis, the HJC is normally estimated using regression equations based on normative data obtained from adult populations. There is limited relevant anthropometric data available for children, despite the fact that clinical gait analysis is predominantly used for the assessment of children with cerebral palsy. In this study, pelvic MRI scans were taken of eight adults (ages 23-40), 14 healthy children (ages 5-13) and 10 children with spastic diplegic cerebral palsy (ages 6-13). Relevant anatomical landmarks were located in the scans, and the HJC location in pelvic coordinates was found by fitting a sphere to points identified on the femoral head. The predictions of three common regression equations for HJC location were compared to those found directly from MRI. Maximum absolute errors of 31 mm were found in adults, 26 mm in children, and 31 mm in the cerebral palsy group. Results from regression analysis and leave-one-out cross-validation techniques on the MRI data suggested that the best predictors of HJC location were: pelvic depth for the antero-posterior direction; pelvic width and leg length for the supero-inferior direction; and pelvic depth and pelvic width for the medio-lateral direction. For single-variable regression, the exclusion of leg length and pelvic depth from the latter two regression equations is proposed. Regression equations could be generalised across adults, children and the cerebral palsy group.     

Determining the location of hip joint centre: application of a conchoid's shape to the acetabular cartilage surface of magnetic resonance images

Preoperative planning, or intraoperative navigation of hip surgery, including joint-preserving procedures such as osteotomy or joint-replacing procedures such as total arthroplasty, needs to be performed with a high degree of accuracy to ensure a successful outcome. The ability to precisely localise the hip joint rotation centre may prove to be very useful in this context. The human hip joint has been shown to be a conchoid shape, and therefore the accurate location of the hip joint centre (HJC) cannot be computed simply as the centre of a sphere. This study describes a method for determining the HJC by applying a conchoid shape to the acetabular cartilage surface of magnetic resonance images, in order to increase the accuracy of the HJC location which had previously been calculated by a functional method using reconstructed three-dimensional surface bony models. By approximating a conchoid shape to the acetabulum, it was possible to compensate for HJC calculation errors.     

An optimized protocol for hip joint centre determination using the functional method

The functional method identifies the hip joint centre (HJC) as the centre of rotation of the femur relative to the pelvis during an ad hoc movement normally recorded using stereophotogrammetry. This method may be used for the direct determination of subject-specific HJC coordinates or for creating a database from which regression equations may be derived that allow for the prediction of those coordinates. In order to contribute to the optimization of the functional method, the effects of the following factors were investigated: the algorithm used to estimate the HJC coordinates from marker coordinates, the type and amplitude of the movement of the femur relative to the pelvis, marker cluster location and dimensions, and the number of data samples. This was done using a simulation approach which, in turn, was validated using experiments made on a physical analogue of the pelvis and femur system. The algorithms used in the present context were classified and, in some instances, modified in order to optimize both accuracy and computation time, and submitted to a comparative evaluation. The type of movement that allowed for the most accurate results consisted of several flexion-extension/abduction-adduction movements performed on vertical planes of different orientations, followed by a circumduction movement. The accuracy of the HJC estimate improved, with an increasing rate, as a function of the amplitude of these movements. A sharp improvement was found as the number of the photogrammetric data samples used to describe the movement increased up to 500. For optimal performance with the recommended algorithms, markers were best located as far as possible from each other and with their centroid as close as possible to the HJC. By optimizing the analytical and experimental protocol, HJC location error not caused by soft tissue artefacts may be reduced by a factor of ten with a maximal expected value for such error of approximately 1mm.     

Sensitivity analysis of hip joint centre estimation based on three-dimensional CT scans

In morphological analysis of the femur, the hip joint centre (HJC) is generally determined using a 3D model of the femoral head based on medical images. However, the portion of the image selected to represent the femoral head may influence the HJC. We determined if this influence invalidates the results of three HJC calculation methods, one of which we introduce here.

To isolate femoral heads in cadaver CT images, thresholds were applied to the distance between femur and acetabulum models. The sensitivity of the HJC to these thresholds and the differences between methods were quantified.

For thresholds between 6 and 9 mm and healthy hips, differences between methods were below 1 mm and all methods were insensitive to threshold changes. For higher thresholds, the fovea capitis femoris disturbed the HJC. In two deformed hips, the new method performed superiorly. We conclude that for normal hips all methods produce valid results.     

Sensitivity analysis of hip joint centre estimation based on three-dimensional CT scans

In morphological analysis of the femur, the hip joint centre (HJC) is generally determined using a 3D model of the femoral head based on medical images. However, the portion of the image selected to represent the femoral head may influence the HJC. We determined if this influence invalidates the results of three HJC calculation methods, one of which we introduce here. To isolate femoral heads in cadaver CT images, thresholds were applied to the distance between femur and acetabulum models. The sensitivity of the HJC to these thresholds and the differences between methods were quantified. For thresholds between 6 and 9?mm and healthy hips, differences between methods were below 1?mm and all methods were insensitive to threshold changes. For higher thresholds, the fovea capitis femoris disturbed the HJC. In two deformed hips, the new method performed superiorly. We conclude that for normal hips all methods produce valid results.     

A normative database of hip and knee joint biomechanics during dynamic tasks using anatomical regression prediction methods

Many methodologies exist to predict the hip joint center (HJC), of which regression based on anatomical landmarks appear most common. Despite the fact that predicted HJC locations vary depending upon chosen method, inter-study comparisons and inferences about populations are commonly made. The purpose of this study was to create a normative database of hip and knee biomechanics during walking, running, and single leg landings based on five commonly utilized HJC methods to serve as a reference for inter-study comparisons. Secondarily, we devised to provide comparisons of peak knee angles and hip angles, moments, and powers from the five HJC methods. Thirty healthy young adults performed walking, running, and single leg landing tasks at self-selected speeds (walking/running) and at 90% of their maximum jump height (landing). Three-dimensional motion capture and ground reaction forces were collected during all tasks. Five different HJC prediction methods: Bell, Davis, Hara, Harrington, and Greater Trochanter were implemented separately in a 6 degree of freedom model. Predicted HJC locations, direct kinematics, and inverse dynamics were computed for all tasks. Predicted HJC mediolateral, anteroposterior, and superior-inferior locations differed between methods by an average of 1.3, 2.9, and 1.4 cm, respectively. A database was created using the mean of all subjects for all five methods. In addition, one-way ANOVAs were used to compare triplanar peak angles, moments, and powers between the methods. The database of hip and knee biomechanics illustrates (1) variability between methods increases with more dynamic tasks (running/landing vs. walking) and (2) frontal and transverse plane hip and knee biomechanics are more variable between methods. Comparisons between methods found 38 and 16 main effect differences in hip and knee biomechanics, respectively. The Greater Trochanter method provided the most differences compared with other methods, while the Davis method provided the least differences. The database constructed provides an important reference for inter-study comparisons and details the impact of anatomical regression methods for predicting the HJC.     

Effects of hip joint centre mislocation on gait analysis results

Methods to determine the hip joint centre (HJC) location are necessary in gait analysis. It has been demonstrated that the methods proposed in the literature involve large mislocation errors. The choice should be made according to the extent by which HJC location errors distort the estimates of angles and resultant moments at the hip and knee joints. This study aimed at quantifying how mislocation errors propagate to these gait analysis results. Angles and moments at the hip and knee joint were calculated for five able-bodied subjects during level walking. The nominal position of the HJC was determined as the position of the pivot point of a 3D movement of the thigh relative to the pelvis. Angles and moments were then re-calculated after having added to HJC co-ordinates errors in the range of +/-30 mm. Angles and moments at both hip and knee joints were affected by HJC mislocation. The hip moments showed the largest propagation error: a 30 mm HJC anterior mislocation resulted in a propagated error into flexion/extension component of about -22%. The hip abduction/adduction moment was found the second largest affected quantity: a 30 mm lateral HJC mislocation produced a propagated error of about -15%. Finally, a 30 mm posterior HJC mislocation produced a delay of the flexion-to-extension timing in the order of 25% of the stride duration. HJC estimation methods with minimum antero-posterior error should therefore be preferred.     

In vivo estimation of the glenohumeral joint centre by functional methods: Accuracy and repeatability assessment

Several algorithms have been proposed for determining the centre of rotation of ball joints. These algorithms are used rather to locate the hip joint centre. Few studies have focused on the determination of the glenohumeral joint centre. However, no studies have assessed the accuracy and repeatability of functional methods for glenohumeral joint centre.This paper aims at evaluating the accuracy and the repeatability with which the glenohumeral joint rotation centre (GHRC) can be estimated in vivo by functional methods. The reference joint centre is the glenohumeral anatomical centre obtained by medical imaging. Five functional methods were tested: the algorithm of Gamage and Lasenby (2002), bias compensated (Halvorsen, 2003), symmetrical centre of rotation estimation (Ehrig et al., 2006), normalization method (Chang and Pollard, 2007), helical axis (Woltring et al., 1985). The glenohumeral anatomical centre (GHAC) was deduced from the fitting of the humeral head.Four subjects performed three cycles of three different movements (flexion/extension, abduction/adduction and circumduction). For each test, the location of the glenohumeral joint centre was estimated by the five methods. Analyses focused on the 3D location, on the repeatability of location and on the accuracy by computing the Euclidian distance between the estimated GHRC and the GHAC. For all the methods, the error repeatability was inferior to 8.25 mm. This study showed that there are significant differences between the five functional methods. The smallest distance between the estimated joint centre and the centre of the humeral head was obtained with the method of Gamage and Lasenby (2002).     

Assessment of the functional method of hip joint center location subject to reduced range of hip motion

Motion analysis of the lower extremities usually requires determination of the location of the hip joint center. The results of several recent studies have suggested that kinematic and kinetic variables calculated from motion analysis data are highly sensitive to errors in hip joint center location. "Functional" methods in which the location of the hip joint center is determined from the relative motion of the thigh and pelvis, rather than from the locations of bony landmarks, are promising but may be ineffective when motion is limited. The aims of the present study were to determine whether the accuracy of the functional method is compromised in young and elderly subjects when limitations on hip motion are imposed and to investigate the possibility of locating the hip joint center using data collected during commonly studied motions (walking, sit-to-stand, stair ascent, stair descent) rather than using data from an ad hoc trial in which varied hip motions are performed. The results of the study suggested that functional methods would result in worst-case hip joint center location errors of 26mm (comparable to the average errors previously reported for joint center location based on bony landmarks) when available hip motion is substantially limited. Much larger errors ( approximately 70mm worst-case), however, resulted when hip joint centers were located from data collected during commonly performed motions, perhaps because these motions are, for the most part, restricted to the sagittal plane. It appears that the functional method can be successfully implemented when range of motion is limited but still requires collection of a special motion trial in which hip motion in both the sagittal and frontal planes is recorded.     

Hip joint centre localisation with an unscented Kalman filter

The accurate estimation of the hip joint centre (HJC) in gait analysis and in computer assisted orthopaedic procedures is a basic requirement. Functional methods, based on rigid body localisation, assessing the kinematics of the femur during circumduction movements (pivoting) have been used for estimating the HJC. Localising the femoral segment only, as it is usually done in total knee replacement procedure, can give rise to estimation errors, since the pelvis, during the passive pivoting manoeuvre, might undergo spatial displacements. This paper presents the design and test of an unscented Kalman filter that allows the estimation of the HJC by observing the pose of the femur and the 3D coordinates of a single marker attached to the pelvis. This new approach was validated using a hip joint mechanical simulator, mimicking both hard and soft tissues. The algorithm performances were compared with the literature standards and proved to have better performances in case of pelvis translation greater than 8 mm, thus satisfying the clinical requirements of the application.     

An approach for hip joint center calculation for use in seated postures

In seated postures, such as those in office or automotive seats, locating the hip joint center (HJC) using three markers on the pelvis has been difficult if not impossible. A two-target approach by Bell et al. (J. Biomech. 23 (1990) 617) has been used, however, this method was shown to have inaccuracies when compared to the three-target method developed by Seidel et al. (J. Biomech. 28 (1995) 995). A new two-target method that is specific to the seated environment, has better accuracy than the Bell et al. approach, and is based on the Seidel et al. approach was developed and tested on 13 seated subjects. This new method used three targets and an initial reference file to estimate the HJC location. Once the HJC was located, assumptions were made that the magnitudes between the HJC and the respective anterior superior iliac spine, and the HJC and the respective lateral epicondyle remained constant. The primary concern when evaluating this new method was the affect of seated posture movement, in particular leg splay and spinal flexion on the assumptions. The results obtained with the new approach were compared to Seidel et al. and provided HJC locations with average differences of 3.8, 1.2 and 2.8mm for spinal flexion in the anterior/posterior, medial/lateral and superior/inferior directions, respectively, and 2.3, 1.0 and 1.4mm for knee splay. The proposed method provided better HJC estimation than the Bell et al. approach particularly in the superior/inferior dimensions.     

The effect on conventional gait model kinematics and kinetics of hip joint centre equations in adult healthy gait

The Conventional Gait Model (CGM) needs to benefit from large investigations on localization of the hip joint centre (HJC). Incorrect positions from the native equations were demonstrated (Sangeux et al., 2014; Harrington et al., 2007). More accurate equations were proposed but their impact on kinematics and kinetic CGM outputs was never evaluated. This short communication aims at examining if adoption of new HJC equations would alter standard CGM outputs. Sixteen able bodied participants underwent a full 3-D optoelectronic gait analysis followed by a 3-D ultrasound localization of their hips. Data were processed through the open source python package pyCGM2 replicating kinematic and kinetic processing of the native CGM. Compared with 3D ultrasound location, Hara equations improved the accuracy of sagittal plane kinematics (0.6°) and kinetics (0.02 N m kg⁻¹) for the hip. The worst case participant exhibited Harrington’s equations reached a deviation of 3° for the sagittal kinematics. In the coronal plane, Hara and Harrington equations presented similar differences (1°) for the hip whilst Davis equations had the largest deviation for hip abduction (2.7°) and hip abductor moment (0.10 N m kg⁻¹).Both Harrington and Hara equations improved the CGM location of the HJC. Hara equations improved results in the sagittal plane, plus utilise a single anthropometrics measurement, leg length, that may be more robust. However, neither set of equations had significant effect on kinematics. We reported some effects on kinetics, particularly in the coronal plane, which warrant caution in interpreting outputs using different sets of equations.     

Subject-specific hip geometry and hip joint centre location affects calculated contact forces at the hip during gait

Hip loading affects the development of hip osteoarthritis, bone remodelling and osseointegration of implants. In this study, we analyzed the effect of subject-specific modelling of hip geometry and hip joint centre (HJC) location on the quantification of hip joint moments, muscle moments and hip contact forces during gait, using musculoskeletal modelling, inverse dynamic analysis and static optimization. For 10 subjects, hip joint moments, muscle moments and hip loading in terms of magnitude and orientation were quantified using three different model types, each including a different amount of subject-specific detail: (1) a generic scaled musculoskeletal model, (2) a generic scaled musculoskeletal model with subject-specific hip geometry (femoral anteversion, neck-length and neck-shaft angle) and (3) a generic scaled musculoskeletal model with subject-specific hip geometry including HJC location. Subject-specific geometry and HJC location were derived from CT. Significant differences were found between the three model types in HJC location, hip flexion–extension moment and inclination angle of the total contact force in the frontal plane. No model agreement was found between the three model types for the calculation of contact forces in terms of magnitude and orientations, and muscle moments. Therefore, we suggest that personalized models with individualized hip joint geometry and HJC location should be used for the quantification of hip loading. For biomechanical analyses aiming to understand modified hip joint loading, and planning hip surgery in patients with osteoarthritis, the amount of subject-specific detail, related to bone geometry and joint centre location in the musculoskeletal models used, needs to be considered.     

Computed tomography-based joint locations affect calculation of joint moments during gait when compared to scaling approaches

Hip joint moments are an important parameter in the biomechanical evaluation of orthopaedic surgery. Joint moments are generally calculated using scaled generic musculoskeletal models. However, due to anatomical variability or pathology, such models may differ from the patient's anatomy, calling into question the accuracy of the resulting joint moments. This study aimed to quantify the potential joint moment errors caused by geometrical inaccuracies in scaled models, during gait, for eight test subjects. For comparison, a semi-automatic computed tomography (CT)-based workflow was introduced to create models with subject-specific joint locations and inertial parameters. 3D surface models of the femora and hemipelves were created by segmentation and the hip joint centres and knee axes were located in these models. The scaled models systematically located the hip joint centre (HJC) up to 33.6 mm too inferiorly. As a consequence, significant and substantial peak hip extension and abduction moment differences were recorded, with, respectively, up to 23.1% and 15.8% higher values in the image-based models. These findings reaffirm the importance of accurate HJC estimation, which may be achieved using CT- or radiography-based subject-specific modelling. However, obesity-related gait analysis marker placement errors may have influenced these results and more research is needed to overcome these artefacts.     

Accuracy of the functional method of hip joint center location: effects of limited motion and varied implementation.

Accurate location of the hip joint center is essential for computation of hip kinematics and kinetics as well as for determination of the moment arms of muscles crossing the hip. The functional method of hip joint center location involves fitting a pelvis-fixed sphere to the path traced by a thigh-fixed point while a subject performs hip motions; the center of this sphere is the hip joint center. The aim of the present study was to evaluate the potential accuracy of the functional method and the dependence of its accuracy on variations in its implementation and the amount of available hip motion. The motions of a mechanical linkage were studied to isolate the factors of interest, removing errors due to skin movement and the palpation of bony landmarks that are always present in human studies. It was found that reducing the range of hip motion from 30 degrees to 15 degrees did significantly increase hip joint center location errors, but that restricting motion to a single plane did not. The magnitudes of these errors, however, even in the least accurate cases, were smaller than those previously reported for either the functional method or other methods based on pelvis measurements of living subjects and cadaver specimens. Neither increasing the number of motion data observations nor analyzing the motion of a single thigh marker (rather than the centroid of multiple markers) was found to significantly increase error. The results of this study (1) imply that the limited range of motion that is often evident in subjects with hip pathology does not preclude accurate determination of the hip joint center when the functional method is used; and (2) provide guidelines for the use of the functional method in human subjects.     

MRI development and validation of two new predictive methods of glenohumeral joint centre location identification and comparison with established techniques

Identification of the centre of the glenohumeral joint (GHJ) is essential for three-dimensional (3D) upper limb motion analysis. A number of convenient, yet un-validated methods are routinely used to estimate the GHJ location in preference to the International Society of Biomechanics (ISB) recommended methods. The current study developed a new regression model, and simple 3D offset method for GHJ location estimation, employing easy to administer measures, and compared the estimates with the known GHJ location measured with magnetic resonance imaging (MRI). The accuracy and reliability of the new regression and simple 3D offset techniques were compared with six established predictive methods. Twenty subjects wore a 3D motion analysis marker set that was also visible in MRI. Immediately following imaging, they underwent 3D motion analysis acquisition. The GHJ and anatomical landmark positions of 15 participants were used to determine the new regression and simple 3D generic offset methods. These were compared for accuracy with six established methods using 10 subject's data. A cross validation on 5 participants not used for regression model development was also performed. Finally, 10 participants underwent a further two MRI's and subsequent 3D motion analysis analyses for inter-tester and intra-tester reliability quantification. When compared with any of the other established methods, our newly developed regression model found an average GHJ location closer to the actual MRI location, having an GHJ location error of 13±2 mm, and had significantly lower inter-tester reliability error, 6±4 mm (p<0.01).     

Repeatability assessment of functional methods to estimate the glenohumeral joint centre

Functional methods can be used to determine the centre of rotation (CoR) of a ball-and-socket joint. The algorithms are used to locate rather the hip joint centre than the glenohumeral joint centre. The choice of the most suitable method depends especially on the intra- and inter-session repeatability of these methods. This paper aims at evaluating the intra- and inter-session repeatability of functional methods with which the glenohumeral joint rotation centre (GHRC) can be estimated in vivo. It also estimates the most suitable amplitude of functional movements. Five functional methods were tested: the algorithms of Gamage and Lasenby, bias compensation, symmetrical CoR estimation, normalisation method and helical axis. Ten subjects performed three cycles of three different movements (flexion–extension, abduction–adduction and circumduction). These movements were repeated three times with three different ranges of motion. Six subjects came back in order to evaluate the inter-session repeatability. For each test, the location of the GHRC was estimated by the five methods. The method to solve the functional problem and the range of functional movement affected the GHRC location. The results showed a good to excellent intra-session repeatability. The lowest repeatability error was found for the high amplitude whatever the methods used. The inter-session reliability was moderate. Finally, we suggest the use of functional methods with high amplitude movement in order to locate the GHRC with the best reliability.