Soft Tissue Artifact Compensation Research Articles

Kinetics influence of multibody kinematics optimisation for soft tissue artefact compensation

Soft tissue artefact (STA) remains a major source of error in human movement analysis. The multibody kinematics optimisation (MKO) approach is widely stated as a solution to reduce the effects of STA. This study aimed at assessing the influence of the MKO STA-compensation on the errors of estimation of the knee intersegment moments. Experimental data were issued from the CAMS-Knee dataset where six participants with instrumented total knee arthroplasty performed five activities of daily living: gait, downhill walking, stair descent, squat, and sit-to-stand. Kinematics was measured both on the basis of skin markers and a mobile mono-plane fluoroscope, used to obtain the STA-free bone movement. For four different lower limb models and one corresponding to a single-body kinematics optimization (SKO), knee intersegmental moments (estimated using model-derived kinematics and ground reaction force) were compared with an estimate based on the fluoroscope. Considering all participants and activities, mean root mean square differences were the largest along the adduction/abduction axis: of 3.22Nm with a SKO approach, 3.49Nm with the three-DoF knee model, and 7.66Nm, 8.52Nm, and 8.54Nm with the one-DoF knee models. Results showed that adding joint kinematics constraints can increase the estimation errors of the intersegmental moment. These errors came directly from the errors in the estimation of the position of the knee joint centre induced by the constraints. When using a MKO approach, we recommend to analyse carefully joint centre position estimates that do not remain close to the one obtained with a SKO approach.

Comparison of scapula soft tissue artefact compensation methods during manual wheelchair locomotion

Comparison of scapula soft tissue artefact compensation methods during manual wheelchair locomotion

Development and evaluation of a new methodology for Soft Tissue Artifact compensation in the lower limb

Skin Marker (SM) based motion capture is the most widespread technique used for motion analysis. Yet, the accuracy is often hindered by Soft Tissue Artifact (STA). This is a major issue in clinical gait analysis where kinematic results are used for decision-making. It also has a considerable influence on the results of rigid body and Finite Element (FE) musculoskeletal models that rely on SM-based kinematics to estimate muscle, contact and ligament forces. Current techniques devised to compensate for STA, in particular multi-body optimization methods, often consider simplified joint models. Although joint personalization with anatomical constraints has improved kinematic estimation, these models yet don’t represent a fully reliable solution to the STA problem, thus allowing us to envisage an alternative approach. In this perspective, we propose to develop a conceptual FE-based model of the lower limb for STA compensation and evaluate it for 66 healthy subjects under level walking motor task.Both hip and knee joint kinematics were analyzed, considering both rotational and translational joint motion. Results showed that STA caused underestimation of the hip joint kinematics (up to 2.2°) for all rotational DoF, and overestimation of knee joint kinematics (up to 12°) except in flexion/extension. Joint kinematics, in particular the knee joint, appeared to be sensitive to soft tissue stiffness parameters (rotational and translational mean difference up to 1.5° and 3.4 mm). Analysis of the results using alternative joint representations highlighted the versatility of the proposed modeling approach. This work paves the way for using personalized models to compensate for STA in healthy subjects and different activities.

Evaluation of a multibody kinematics optimization method for three-dimensional canine pelvic limb gait analysis

BackgroundSkin marker-based three-dimensional kinematic gait analysis were commonly used to assess the functional performance and movement biomechanics of the pelvic limb in dogs. Unfortunately, soft tissue artefact would compromise the accuracy of the reproduced pelvic limb kinematics. Multibody kinematics optimization framework was often employed to compensate the soft tissue artefact for a more accurate description of human joint kinematics, but its performance on the determination of canine pelvic limb skeletal kinematics has never been evaluated. This study aimed to evaluate a multibody kinematics optimization framework used for the determination of canine pelvic limb kinematics during gait by comparing its results to those obtained using computed tomography model-based fluoroscopy analysis.ResultsEight clinically normal dogs were enrolled in the study. Fluoroscopy videos of the stifle joint and skin marker trajectories were acquired when the dogs walked on a treadmill. The pelvic limb kinematics were reconstructed through marker-based multibody kinematics optimization and single-body optimization. The reference kinematics data were derived via a model-based fluoroscopy analysis. The use of multibody kinematics optimization yielded a significantly more accurate estimation of flexion/extension of the hip and stifle joints than the use of single-body optimization. The accuracy of the joint model parameters and the weightings to individual markers both influenced the soft tissue artefact compensation capability.ConclusionsMultibody kinematics optimization designated for soft tissue artefact compensation was established and evaluated for its performance on canine gait analysis, which provided a further step in more accurately describing sagittal plane kinematics of the hip and stifle joints.

Effects of the soft tissue artefact on the hip joint kinematics during unrestricted activities of daily living

Soft tissue artefact (STA) affects the kinematics retrieved with skin marker-based motion capture, and thus influences the outcomes of biomechanical models that rely on such kinematics. In order to be compensated for, the effects of STA must be characterized across a broad sample population and for different motion activities. In this study, the error introduced by STA on the kinematics of the hip joint and of its individual components, and on the location of the hip joint center (HJC) was quantified for fifteen THA subjects during overground gait, stair descent, chair rise and putting on socks. The error due to STA was computed as the difference between the kinematics measured with motion capture and those measured simultaneously with moving fluoroscopy, a STA-free X-ray technique. The main significant effects of STA were: underestimation of the hip range of motion for all four activities, underestimation of the flexion especially during phases of the motion with higher flexion, overestimation of the internal rotation, and lateral misplacement of the HJC mostly due to the functional calibration. The thigh contributed more to the STA error than the pelvis. The STA error of the thigh appeared to be correlated with the hip flexion angles, with a varying degree of linearity depending on the activity and on the phase of the motion cycle. Future kinematic-driven STA compensation models should take into account the non-linearity of the STA error and its dependency of the phase of the motion cycle.

P 054–Evaluation of ground reaction forces by inverse dynamics analysis

Soft tissue artefact (STA) affects the kinematics retrieved with skin marker-based motion capture, and thus influences the outcomes of biomechanical models that rely on such kinematics. In order to be compensated for, the effects of STA must be characterized across a broad sample population and for different motion activities. In this study, the error introduced by STA on the kinematics of the hip joint and of its individual components, and on the location of the hip joint center (HJC) was quantified for fifteen THA subjects during overground gait, stair descent, chair rise and putting on socks. The error due to STA was computed as the difference between the kinematics measured with motion capture and those measured simultaneously with moving fluoroscopy, a STA-free X-ray technique. The main significant effects of STA were: underestimation of the hip range of motion for all four activities, underestimation of the flexion especially during phases of the motion with higher flexion, overestimation of the internal rotation, and lateral misplacement of the HJC mostly due to the functional calibration. The thigh contributed more to the STA error than the pelvis. The STA error of the thigh appeared to be correlated with the hip flexion angles, with a varying degree of linearity depending on the activity and on the phase of the motion cycle. Future kinematic-driven STA compensation models should take into account the non-linearity of the STA error and its dependency of the phase of the motion cycle.

Assessment of the lower limb soft tissue artefact at marker-cluster level with a high-density marker set during walking.

The estimation of joint kinematics from skin markers is hindered by the soft tissue artefact (STA), a well-known phenomenon although not fully characterized. While most assessments of the STA have been performed based on the individual skin markers displacements, recent assessments were based on the marker-cluster geometrical transformations using, e.g., principal component or modal analysis. However, these marker-clusters were generally made of 4-6 markers and the current findings on the STA could have been biased by the limited number of skin makers analysed. The objective of the present study was therefore to confirm them with a high-density marker set, i.e. 40 markers placed on the segments. A larger number of modes than found in the literature was required to describe the STA. Nevertheless, translations and rotations of the marker-cluster remained the main STA modes, archetypally the translation along the proximal-distal and anterior-posterior axes for the shank and the translation along the proximal-distal axis and the rotation about the medial-lateral axis for the thigh. High correlations were also found between the knee flexion angle and the amplitude of these modes for the thigh whereas moderate ones were found for the shank. These findings support the current re-orientation of the STA compensation methods, from bone pose estimators which typically address the non-rigid components of the marker-cluster to kinematic-driven rigid-component STA models.

Multi-slice ultrasound image calibration of an intelligent skin-marker for soft tissue artefact compensation

In this paper, a novel multi-slice ultrasound (US) image calibration of an intelligent skin-marker used for soft tissue artefact compensation is proposed to align and orient image slices in an exact H-shaped pattern. Multi-slice calibration is complex, however, in the proposed method, a phantom based visual alignment followed by transform parameters estimation greatly reduces the complexity and provides sufficient accuracy. In this approach, the Hough Transform (HT) is used to further enhance the image features which originate from the image feature enhancing elements integrated into the physical phantom model, thus reducing feature detection uncertainty. In this framework, slice by slice image alignment and calibration are carried out and this provides manual ease and convenience.

Soft tissue artifact compensation in knee kinematics by multi-body optimization: Performance of subject-specific knee joint models

Soft tissue artifact (STA) distort marker-based knee kinematics measures and make them difficult to use in clinical practice. None of the current methods designed to compensate for STA is suitable, but multi-body optimization (MBO) has demonstrated encouraging results and can be improved. The goal of this study was to develop and validate the performance of knee joint models, with anatomical and subject-specific kinematic constraints, used in MBO to reduce STA errors. Twenty subjects were recruited: 10 healthy and 10 osteoarthritis (OA) subjects. Subject-specific knee joint models were evaluated by comparing dynamic knee kinematics recorded by a motion capture system (KneeKG™) and optimized with MBO to quasi-static knee kinematics measured by a low-dose, upright, biplanar radiographic imaging system (EOS®). Errors due to STA ranged from 1.6° to 22.4° for knee rotations and from 0.8mm to 14.9mm for knee displacements in healthy and OA subjects. Subject-specific knee joint models were most effective in compensating for STA in terms of abduction–adduction, inter–external rotation and antero–posterior displacement. Root mean square errors with subject-specific knee joint models ranged from 2.2±1.2° to 6.0±3.9° for knee rotations and from 2.4±1.1mm to 4.3±2.4mm for knee displacements in healthy and OA subjects, respectively. Our study shows that MBO can be improved with subject-specific knee joint models, and that the quality of the motion capture calibration is critical. Future investigations should focus on more refined knee joint models to reproduce specific OA knee geometry and physiology.

A model of the soft tissue artefact rigid component

When using stereophotogrammetry and skin-markers, the reconstruction of skeletal movement is affected by soft-tissue artefact (STA). This may be described by considering a marker–cluster as a deformable shape undergoing a geometric transformation formed by a non-rigid (change in size and shape) and a rigid component (translation and rotation displacements). A modal decomposition of the STA, relative to an appropriately identified basis, allows the separation of these components. This study proposes a mathematical model of the STA that embeds only its rigid component and estimates the relevant six mode amplitudes as linear functions of selected proximal and distal joint rotations during the analysed task. This model was successfully calibrated for thigh and shank using simultaneously recorded pin- and skin-marker data of running volunteers. The root mean square difference between measured and model-estimated STA rigid component was 1.1(0.8)mm (median (inter-quartile range) over 3 subjects×5 trials×33 markers coordinates), and it was mostly due to the wobbling not included in the model. Knee joint kinematics was estimated using reference pin-marker data and skin-marker data, both raw and compensated with the model-estimated STA. STA compensation decreased inaccuracy on average from 6% to 1% for flexion/extension, from 43% to 18% for the other two rotations, and from 69% to 25% for the linear displacements. Thus, the proposed mathematical model provides an STA estimate which can be effectively used within optimal bone pose and joint kinematics estimators for artefact compensation, and for simulations aimed at their comparative assessments.

Soft tissue artifact compensation in lower extremities using displacement relationship between anatomical landmarks and skin markers

Soft tissue artifact (STA), the deformation of skin and muscle during motion, is known to be one of the important sources of errors in human motion analysis using stereophotogrammetry. As a way to reduce the STA errors, methods estimating positions of anatomical landmarks (AL) have been proposed that keep them rigidly related to the underlying bone. The previous methods [1,2] used intermediate variables such as joint angles or motion time to adjust AL positions which were calculated from position data of skin markers. The present study proposes a method to estimate AL positions with skin marker positions directly, thereby removing the intermediate variables of the previous methods. The proposed method identifies a systematic relationship between the displacements of ALs and skin markers relative to a technical coordinate frame defined by skin markers in ad hoc motions(Figure ​motions(Figure1).1). Then, AL positions are calibrated directly by using the displacement relationship with skin markers. The proposed method was applied to analyze three lower extremity motions (walking, sit-to-stand/stand-to-sit and step up/down) of ten healthy males. Its performance was compared with the transformation error minimization method (TEM) of [3] and the AL estimation method with joint angle (ALJ) of [2]. The proposed method considerably reduced STA errors relative to the TEM (by 30 – 80% ) and was also slightly more effective than the ALJ, showing 25 – 40% error reductions for seven of 18 kinematic variables(Figure ​variables(Figure22). Figure 1 Scatter plot of AL and skin marker displacement in the thigh of a participant Figure 2 Statistical comparison of compensation methods

The Human Knee: Gross, Microscopic, Surgical, and Radiological Anatomy

The Human Knee: Gross, Microscopic, Surgical, and Radiological Anatomy

Application of Soft Tissue Artifact Compensation Using Displacement Dependency between Anatomical Landmarks and Skin Markers

Soft tissue artifact is known to be one of the main sources of errors in motion analysis by means of stereophotogrammetry. Among many approaches to reduce such errors, one is to estimate the position of anatomical landmarks during a motion with joint angle or displacement of skin markers, which is the so-called compensation method of anatomical landmarks. The position of anatomical landmarks was modeled from the data of the so-called dynamic calibration, in which anatomical landmark positions are calibrated in an ad hoc motion. This study aimed to apply the compensation methods with joint angle and skin marker displacement to three lower extremity motions (walking, sit-to-stand/stand-to-sit, and step up/down) in ten healthy males and compare their reliability. To compare the methods, two sets of kinematic variables were calculated using two different marker clusters, and the difference was obtained. Results showed that the compensation method with skin marker displacement had less differences by 30–60% compared to without compensation. In addition, it had significantly less difference in some kinematic variables (7 of 18) by 25–40% compared to the compensation method with joint angle.

Soft tissue artifact compensation by linear 3D interpolation and approximation methods

Several compensation methods estimate bone pose from a cluster of skin-mounted makers, each influenced by soft tissue artifact (STA). In this study, linear 3D interpolation and approximation methods (affine mapping, Kriging and radial basis function (RBF)) and the conventional singular value decomposition (SVD) method were examined to determine their suitability for STA compensation. The ability of these four methods to estimate knee angles and displacements was compared using simulated gait data with and without added STA. The knee angle and the displacement estimates of all four methods were similar with root-mean-square errors (RMSEs) near 1.5° and 4 mm, respectively. The 3D interpolation and approximation methods were more complicated to implement than the conventional SVD method. However, these non-standard methods provided additional geometric (homothety, stretch) and time functions that model the deformation of the cluster of markers. This additional information may be useful to model and compensate the STA.

Investigation of soft tissue movement during level walking: Translations and rotations of skin markers

Skin marker-based stereophotogrammetry is the most widely used technique for human motion analysis but its accuracy is mainly limited by soft tissue artifact (STA) which reflects the non-rigidity of human body segments during activities. To compensate for the effects of STA and improve the accuracy of motion analysis, it is critical to understand the behavior and characteristics of soft tissue movement. By using a non-invasive approach, this study investigated the soft tissue movement on the thigh and shank of twenty healthy subjects during level walking which is one of the most important human daily activities and the basic content of clinical gait analysis. With the measurement of inter-marker translations and rotations on each segment, a 4D picture (3D space and time) of soft tissue deformation on the thigh and shank during walking was quantified in terms of the positional and orientational change between different skin locations. Soft tissue deformation showed nonuniform distribution at different locations as well as along different directions. The range of inter-marker movement was found to be up to 19.1 mm/19.6° on the thigh and 9.3 mm/8.6° on the shank. Results in this study provide useful information for understanding soft tissue movement behavior and exploring better marker configurations. Inter-marker movement exhibited similar patterns across subjects. This finding suggests the possibility that STA has inter-subject similarity, which is contrary to the prevailing opinion. This new insight may lead to more effective STA compensation strategies for skin marker-based motion analysis.

Double calibration vs. global optimisation: Performance and effectiveness for clinical application

For clinical application the quantification of the actual subject-specific kinematics is necessary. Soft tissue artefact (STA) propagation to joint kinematics can nullify the clinical interpretability of stereophotogrammetric analysis. STA was assessed to be strongly subject- and task-specific. The global optimisation, whose performance was assessed only on simulated data, is at the basis of several of the STA compensation methods proposed in the literature. On the other hand, the double calibration was recently proposed and resulted very effective on experimental data. In the present work, the performance of double calibration and global optimisation in reducing soft tissue artefact propagation to relevant knee joint kinematics was compared by using 3D fluoroscopy as gold standard. The mean RMSE over the repetitions for the double calibration is in the order of 1–2° for joint rotations and 1–3 mm for translation, while for the global optimisation is in the order of 10° and 10–15 mm, respectively. The double calibration should then be preferred for the quantification of the subject specific kinematics.

Soft tissue artifact compensation using displacement dependency between anatomical landmarks and skin markers – a preliminary study

Soft tissue artifact is known to be one of the principal sources of errors using human motion analysis by means of stereophotogrammetry. As one of the ways to reduce such errors, Lucchetti, L., Cappozo, A., Cappello, A., Croce, U.D. [1998. Skin movement artefact assessment and compensation in the estimation of knee-joint kinematics. Journal of Biomechanics 31, 977–984] proposed the so-called dynamic calibration in which anatomical landmark positions are calibrated in an ad hoc motion after which they are compensated with joint angles in a motor task. However, the method was proven partially inefficient during the repetitive calculation of joint angles for anatomical landmark compensation. The present study herein attempted to offset the anatomical landmark position by using a skin marker displacement as an alternative to the compensation method with joint angles. The feasibility of the proposed method was tested by analyzing the knee motions of a patient wearing an external fixator on the shank. Its performance was later compared with the compensation method with joint angles. In the test, the proposed method was identified as effective in reducing soft tissue artifact errors by 40–80%. The errors of some of kinematic variables were significantly reduced by 25–60% compared to the compensation method with joint angles. Relevance to industry Motion analysis with stereophotogrammetry is utilized for various purposes, including clinical diagnosis, product design, and workload assessment. However, it has been known to accommodate significant errors due to the deformation of soft tissues such as those in the skin and muscles. Methods known to efficiently reduce errors due to the soft tissues are required to improve the utilization of motion analysis. The proposed method simplifies the procedure in reducing the error, and it can be implemented more easily during routine lower extremity motion analysis. But an application of this method during measurements of motions at workplaces would require a validation of the method based on scientific standards.

Effectiveness of soft tissue artifact compensation for clinical application: Double calibration vs. global optimisation

Effectiveness of soft tissue artifact compensation for clinical application: Double calibration vs. global optimisation

Soft Tissue Artifact Compensation in Knee Kinematics by Double Anatomical Landmark Calibration: Performance of a Novel Method During Selected Motor Tasks

The purpose of the present work was to describe and assess the performance on two selected subjects of a new method for the compensation of soft tissue artifact on knee rotations and translations during the execution of step up/down, sit-to-stand/stand-to-sit, and flexion against gravity. Soft tissue artifact has been recognized as the most critical source of error in gait analysis data. Its propagation strongly affects joint angles, in particular those characterized by a small range of motion, such as knee ab/adduction and internal/external rotation. This may be critical in the exploitation of gait analysis data for clinical decisions. The proposed method is based on the flexion/extension angle interpolation of two anatomical landmark calibrations taken at the extremes of motion. Its performance on knee rotation and translations was tested on a kinematics data-set obtained by the synchronous combination of traditional stereophotogrammetry and 3-D fluoroscopy. The newly proposed method was extremely effective on the compensation of soft tissue artifact propagation to knee rotations, in particular mean values of the root mean square error on ab/adduction and internal/external rotation angles decreased from 3.7 degrees and 3.7 degrees to 1.4 degrees and 1.6 degrees, respectively, with respect to single calibration. Mainly, knee translations calculated from stereophotogrammetric data using the proposed compensation method were found to be reliable with respect to the fluoroscopy-based gold standard. The residual mean values of the root mean square error were 2.0, 2.8, and 2.1 mm for anterior/posterior, vertical, and medio/lateral translations, respectively.

Soft tissue artefact assessment in humeral axial rotation

The accuracy of upper-limb kinematic data acquired from optoelectronic systems with retro-reflective markers is poor, mainly due to soft tissue artefact (STA). For the upper-arm, humeral internal/external rotation (HIER) is the movement most affected by STA, which is measured as a percentile fraction (K) of the effective humeral axial rotation performed. The aim of this work was to quantify STA during HIERs, with independently varying attitude of the humerus and elbow flexion, and to test the possibility of estimating its mean value over the tested upper-limb orientations using one simple trial. Six able-bodied subjects performed a series of HIERs in combination with elbow flexion for different humeral planes and degrees of elevation. During the trials the instantaneous attitudes of two humeral anatomical frames were compared, one being affected by the STA to be measured, and the other assumed as the gold standard. K was found to range from 20% to 48% of the effective humeral axial rotation performed, depending on the subject, humeral attitude and elbow flexion. These last two factors comparably affect STA and resulted in mean K coefficients of variation among the subjects of about 9% and 7%, respectively. Common patterns of K with elbow flexion and humerus elevation are discussed. The data also show that the mean of K of a subject is very close to the value assessed in a specific upper-limb configuration consistent among the subjects. This result from this study could be used to build up a time-saving STA compensation procedure suitable for clinical applications.