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

How reliable are femoropelvic kinematics during deep squats? The influence of subject-specific skeletal modelling on measurement variability

BACKGROUND

Biplanar radiography displays promising results in the production of subject-specific (S.specific) biomechanical models. However, the focus has predominantly centred on methodological investigations in gait analysis. Exploring the influence of such models on the analysis of high range of motion tasks linked to hip pathologies is warranted. The aim of this study is to investigate the effect of S.Specific modelling techniques on the reliability of deep squats kinematics in comparison to generic modelling.

METHODS

8 able-bodied male participants attended 5 motion capture sessions conducted by 3 observers and performed 5 deep squats in each. Prior to each session a biplanar scan was acquired with the reflective-markers attached. Inverse kinematics of pelvis and thigh segments were calculated based on S.specific and Generic model definition. Agreement between the two models femoropelvic orientation in standing was assessed with Bland-Altman plots and paired t- tests. Inter-trial, inter-session, inter-observer variability and observer/trial difference and ratio were calculated for squat kinematic data derived from the two modelling approaches.

RESULTS

Compared to the Generic model, the S.Specific model produced a calibration trial that is significantly offset into more posterior pelvis tilt (-2.8±2.7), hip extension (-2.2±3.8), hip abduction (-1.2±3.6) and external rotation (-13.8±11.4). The S.specific model produced significantly different squat kinematics in the sagittal plane of the pelvis (entire squat cycle) and hip (between 40 % and 60 % of the squat cycle). Variability analysis indicated that the error magnitude between the two models was comparable (difference<2°). The S.specific model exhibited a lower variability in the observer/trial ratio in the sagittal pelvis and hip, the frontal hip, but showed a higher variability in the transverse hip.

SIGNIFICANCE

S.specific modelling appears to introduce a calibration offset that primarily translates into an effect in the sagittal plane kinematics. However, the clinical added value of S.specific modelling in terms of reducing experimental sources of kinematic variability was limited.

Focusing on functional knee parameter determination to develop a better clinical gait analysis protocol

BACKGROUND

Attempts to improve protocol standards of marker-based clinical gait analysis (CGA) have been one of the main focuses of research to enhance robustness and reliability outcomes since the 1990s. Determining joint centres and axes constitutes an important aspect of those protocols. Although the hip joint is more prominent in such studies, knee joint center (KJC) and axis (KJA) directly affect all outcomes.

RESEARCH QUESTION

What recommendations arise from the study of the scientific literature for determining knee joint parameters (KJP) for protocols of CGA?

METHODS

A systematic, electronic search was conducted on November 2018 using three databases with the keyword combination ("functional approach" OR "functional method" OR "functional calibration") AND ("hip joint" OR "knee joint" OR "ankle joint") and analyzed by four reviewers. Given the existence of a recent review about the hip joint and the lack of material about the ankle joint, only papers about the knee joint were kept. The references cited in the selected papers were also screened in the final round of the search for these publications. The quality of the selected papers was assessed and aspects regarding accuracy, repeatability, and feasibility were thoroughly considered to allow for a comparison between studies. Technical aspects, such as marker set choice, KJP determination techniques, demographics, and functional movements, were also included.

RESULTS

Thirty-one papers were included and on average received a rating of about 75 % according to the quality scale used. The results showed that functional methods are superior or equivalent to predictive methods to estimate the KJA, while a regression method was slightly better for KJC prediction.

SIGNIFICANCE

Calibration methods should be applied to CGA whenever feasibility is reached. No study to date has focused on evaluating the in vivo RoM required to obtain reliable and repeatable results and future work should aim in this direction.

A multivariate statistical strategy to adjust musculoskeletal models

In musculoskeletal modelling, adjusting model parameters is challenging. This paper proposes a multivariate statistical methodology to adjust muscle force-generating parameters optimally. Dynamic residuals are minimized as muscle force-generating parameters are varied (maximal isometric force, optimal fiber length, tendon slack length and pennation angle).First, a sensitivity and a Pareto analyses are carried out in order to sort out and screen the set of parameters having the greatest influence regarding the dynamic residuals. These parameters are then used to create a response surface following a Design of Experiments (DoE) approach. Finally, this surface is used to determine the optimum levels of the design variables (muscle force-generating parameters). The proposed methodology is illustrated by the adjustment of a three-dimensional musculoskeletal model of a sheep forelimb. After adjustment, the reserve actuator values of the elbow and wrist joints were reduced, on average, by 18%, and 16%, respectively. These results demonstrate that the use of multivariate statistical strategies is an effective way to adjust model parameters optimally while reducing dynamic inconsistencies. This study constitutes a step towards a more robust methodology in musculoskeletal modelling, focusing on muscular parameter tuning.

Accuracy and kinematics consistency of marker-based scaling approaches on a lower limb model: a comparative study with imagery data

Medical images are not typically included in protocol of motion laboratories. Thus, accurate scaling of musculoskeletal models from optoelectronic data are important for any biomechanical analysis. The aim of the current study was to identify a scaling method based on optoelectronic data, inspired from literature, which could offer the best trade-off between accurate geometrical parameters (segment lengths, orientation of joint axes, marker coordinates) and consistent inverse kinematics outputs (kinematic error, joint angles). The methods were applied on 26 subjects and assessed with medical imagery building EOS-based models, considered as a reference. The main contribution of this paper is to show that the marker-based scaling followed by an optimisation of orientation joint axes and markers local coordinates, gives the most consistent scaling and joint angles with EOS-based models. Thus, when a non-invasive mean with an optoelectronic system is considered, a marker-based scaling is preliminary needed to get accurate segment lengths and to optimise joint axes and marker local coordinates to reduce kinematic errors.AbbrevationsAJCAnkle joint centreCKEcumulative kinematic errorDoFdegree of freedomEBEOS-basedHBheight-basedHJChip joint centreKJCknee joint centreMBmarker-basedMSMmusculoskeletal modelsSPMstatistical parametric mappingSTAsoft tissue artifactEB_a.m∗EOS-based with optimised joint axes, and all model markers coordinatesMB_a.m∗marker-based with optimised joint axes, and all model markers coordinatesMB_l.a.mmarker-based with optimised segment lengths, joint axes, and selected model markers coordinatesASISanterior superior illiac spinePSISposterior superior illiac spine.

Depth camera based statistical shape fitting approach for the creation of an individualized lower body biomechanical model: validity and reliability

Systems for instrumented motion analysis depend on an accurate biomechanical model. In this work an existing statistical shape fitting approach was adapted to register a parametrized human surface model with annotated anatomical landmarks to a point cloud obtained from one frontal depth camera view. Based on the obtained landmark positions joint centers, segment lengths and segment orientations of the lower body were calculated. The outcome was validated among two groups of healthy and impaired subjects, using a marker-based optical motion capture system. The results reveal a valid and reliable approach for obtaining an individualized lower body biomechanical model with minimum effort.

A robust method for automatic identification of landmarks on surface models of the pelvis

The recognition of bony landmarks of the pelvis is a required operation in patient-specific orthopedics, subject-specific biomechanics or morphometrics. A fully automatic detection is preferable to a subjective and time-consuming manual identification. In this paper, a new approach, called the iterative tangential plane (ITP) method, for fully automatic identification of landmarks on surface models of the pelvis is introduced. The method includes the landmarks to construct the two most established anatomical reference frames of the pelvis: the anterior pelvic plane (APP) coordinate system and superior inferior spine plane (SISP) coordinate system. The ITP method proved to be robust against the initial alignment of the pelvis in space. A comparison to a manual identification was performed that showed minor but significant (p < 0.05) median differences below 3 mm for the position of the landmarks and below 1° for the orientation of the APP coordinate system. Whether these differences are acceptable, has to be evaluated for each specific use case. There were no significant differences for the orientation of the SISP coordinate system recommended by the International Society of Biomechanics.

Advancing quantitative techniques to improve understanding of the skeletal structure-function relationship

Although all functional movement arises from the interplay between the neurological, skeletal, and muscular systems, it is the skeletal system that forms the basic framework for functional movement. Central to understanding human neuromuscular development, along with the genesis of musculoskeletal pathologies, is quantifying how the human skeletal system adapts and mal-adapts to its mechanical environment. Advancing this understanding is hampered by an inability to directly and non-invasively measure in vivo strains, stresses, and forces on bone. Thus, we traditionally have turned to animal models to garner such information. These models enable direct in vivo measures that are not available for human subjects, providing information in regards to both skeletal adaptation and the interplay between the skeletal and muscular systems. Recently, there has been an explosion of new imaging and modeling techniques providing non-invasive, in vivo measures and estimates of skeletal form and function that have long been missing. Combining multiple modalities and techniques has proven to be one of our most valuable resources in enhancing our understanding of the form-function relationship of the human skeletal, muscular, and neurological systems. Thus, to continue advancing our knowledge of the structural-functional relationship, validation of current tools is needed, while development is required to limit the deficiencies in these tools and develop new ones.

Accuracy and Reliability of Marker-Based Approaches to Scale the Pelvis, Thigh, and Shank Segments in Musculoskeletal Models

Gait analysis together with musculoskeletal modeling is widely used for research. In the absence of medical images, surface marker locations are used to scale a generic model to the individual’s anthropometry. Studies evaluating the accuracy and reliability of different scaling approaches in a pediatric and/or clinical population have not yet been conducted and, therefore, formed the aim of this study. Magnetic resonance images (MRI) and motion capture data were collected from 12 participants with cerebral palsy and 6 typically developed participants. Accuracy was assessed by comparing the scaled model’s segment measures to the corresponding MRI measures, whereas reliability was assessed by comparing the model’s segments scaled with the experimental marker locations from the first and second motion capture session. The inclusion of joint centers into the scaling process significantly increased the accuracy of thigh and shank segment length estimates compared to scaling with markers alone. Pelvis scaling approaches which included the pelvis depth measure led to the highest errors compared to the MRI measures. Reliability was similar between scaling approaches with mean ICC of 0.97. The pelvis should be scaled using pelvic width and height and the thigh and shank segment should be scaled using the proximal and distal joint centers.

Methodological factors affecting joint moments estimation in clinical gait analysis: a systematic review

Quantitative gait analysis can provide a description of joint kinematics and dynamics, and it is recognized as a clinically useful tool for functional assessment, diagnosis and intervention planning. Clinically interpretable parameters are estimated from quantitative measures (i.e. ground reaction forces, skin marker trajectories, etc.) through biomechanical modelling. In particular, the estimation of joint moments during motion is grounded on several modelling assumptions: (1) body segmental and joint kinematics is derived from the trajectories of markers and by modelling the human body as a kinematic chain; (2) joint resultant (net) loads are, usually, derived from force plate measurements through a model of segmental dynamics. Therefore, both measurement errors and modelling assumptions can affect the results, to an extent that also depends on the characteristics of the motor task analysed (i.e. gait speed). Errors affecting the trajectories of joint centres, the orientation of joint functional axes, the joint angular velocities, the accuracy of inertial parameters and force measurements (concurring to the definition of the dynamic model), can weigh differently in the estimation of clinically interpretable joint moments. Numerous studies addressed all these methodological aspects separately, but a critical analysis of how these aspects may affect the clinical interpretation of joint dynamics is still missing. This article aims at filling this gap through a systematic review of the literature, conducted on Web of Science, Scopus and PubMed. The final objective is hence to provide clear take-home messages to guide laboratories in the estimation of joint moments for the clinical practice.

Reliability of functional and predictive methods to estimate the hip joint centre in human motion analysis in healthy adults

In human motion analysis predictive or functional methods are used to estimate the location of the hip joint centre (HJC). It has been shown that the Harrington regression equations (HRE) and geometric sphere fit (GSF) method are the most accurate predictive and functional methods, respectively. To date, the comparative reliability of both approaches has not been assessed. The aims of this study were to (1) compare the reliability of the HRE and the GSF methods, (2) analyse the impact of the number of thigh markers used in the GSF method on the reliability, (3) evaluate how alterations to the movements that comprise the functional trials impact HJC estimations using the GSF method, and (4) assess the influence of the initial guess in the GSF method on the HJC estimation. Fourteen healthy adults were tested on two occasions using a three-dimensional motion capturing system. Skin surface marker positions were acquired while participants performed quite stance, perturbed and non-perturbed functional trials, and walking trials. Results showed that the HRE were more reliable in locating the HJC than the GSF method. However, comparison of inter-session hip kinematics during gait did not show any significant difference between the approaches. Different initial guesses in the GSF method did not result in significant differences in the final HJC location. The GSF method was sensitive to the functional trial performance and therefore it is important to standardize the functional trial performance to ensure a repeatable estimate of the HJC when using the GSF method.

In-vivo quantification of dynamic hip joint center errors and soft tissue artifact

Hip joint center (HJC) measurement error can adversely affect predictions from biomechanical models. Soft tissue artifact (STA) may exacerbate HJC errors during dynamic motions. We quantified HJC error and the effect of STA in 11 young, asymptomatic adults during six activities. Subjects were imaged simultaneously with reflective skin markers (SM) and dual fluoroscopy (DF), an x-ray based technique with submillimeter accuracy that does not suffer from STA. Five HJCs were defined from locations of SM using three predictive (i.e., based on regression) and two functional methods; these calculations were repeated using the DF solutions. Hip joint center motion was analyzed during six degrees-of-freedom (default) and three degrees-of-freedom hip joint kinematics. The position of the DF-measured femoral head center (FHC), served as the reference to calculate HJC error. The effect of STA was quantified with mean absolute deviation. HJC errors were (mean±SD) 16.6±8.4mm and 11.7±11.0mm using SM and DF solutions, respectively. HJC errors from SM measurements were all significantly different from the FHC in at least one anatomical direction during multiple activities. The mean absolute deviation of SM-based HJCs was 2.8±0.7mm, which was greater than that for the FHC (0.6±0.1mm), suggesting that STA caused approximately 2.2mm of spurious HJC motion. Constraining the hip joint to three degrees-of-freedom led to approximately 3.1mm of spurious HJC motion. Our results indicate that STA-induced motion of the HJC contributes to the overall error, but inaccuracies inherent with predictive and functional methods appear to be a larger source of error.

Subject-specific geometrical detail rather than cost function formulation affects hip loading calculation

This study assessed the relative importance of introducing an increasing level of medical image-based subject-specific detail in bone and muscle geometry in the musculoskeletal model, on calculated hip contact forces during gait. These forces were compared to introducing minimization of hip contact forces in the optimization criterion. With an increasing level of subject-specific detail, specifically MRI-based geometry and wrapping surfaces representing the hip capsule, hip contact forces decreased and were more comparable to contact forces measured using instrumented prostheses (average difference of 0.69 BW at the first peak compared to 1.04 BW for the generic model). Inclusion of subject-specific wrapping surfaces in the model had a greater effect than altering the cost function definition.