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.     

Multibody kinematics optimization with marker projection improves the accuracy of the humerus rotational kinematics

Markers put on the arm undergo large soft tissue artefact (STA). Using markers on the forearm, multibody kinematics optimization (MKO) helps improve the accuracy of the arm kinematics especially its longitudinal rotation. However deleterious effect of STA may persist and affect other segment estimate. The objective was to present an innovative multibody kinematics optimization algorithm with projection of markers onto a requested axis of the local system of coordinates, to cancel their deleterious effect on this degree-of-freedom. Four subjects equipped with markers put on intracortical pins inserted into the humerus, on skin (scapula, arm and forearm) and subsequently on rigid cuffs (arm and forearm) performed analytic, daily-living, sports and range-of-motion tasks. Scapulohumeral kinematics was estimated using 1) pin markers (reference), 2) single-body optimization, 3) MKO, 4) MKO with projection of all arm markers and 5) MKO with projection of a selection of arm markers. Approaches 2–4 were applied to markers put on the skin and the cuff. The main findings were that multibody kinematics optimization improved the accuracy of 40–50% and the projection algorithm added an extra 20% when applied to cuff markers or a selection of skin markers (all but the medial epicondyle). Therefore, the projection algorithm performed better than multibody and single-body optimizations, especially when using markers put on a cuff. Error of humerus orientation was reduced by half to finally be less than 5°. To conclude, this innovative algorithm is a promising approach for estimating accurate upper-limb kinematics.     

In situ comparison of A-mode ultrasound tracking system and skin-mounted markers for measuring kinematics of the lower extremity

Skin-mounted marker based motion capture systems are widely used in measuring the movement of human joints. Kinematic measurements associated with skin-mounted markers are subject to soft tissue artifacts (STA), since the markers follow skin movement, thus generating errors when used to represent motions of underlying bone segments. We present a novel ultrasound tracking system that is capable of directly measuring tibial and femoral bone surfaces during dynamic motions, and subsequently measuring six-degree-of-freedom (6-DOF) tibiofemoral kinematics. The aim of this study is to quantitatively compare the accuracy of tibiofemoral kinematics estimated by the ultrasound tracking system and by a conventional skin-mounted marker based motion capture system in a cadaveric experimental scenario. Two typical tibiofemoral joint models (spherical and hinge models) were used to derive relevant kinematic outcomes. Intra-cortical bone pins equipped with optical markers were inserted in the tibial and femoral bones to serve as a reference to provide ground truth kinematics. The ultrasound tracking system resulted in lower kinematic errors than the skin-mounted markers (the ultrasound tracking system: maximum root-mean-square (RMS) error 3.44° for rotations and 4.88 mm for translations, skin-mounted markers with the spherical joint model: 6.32° and 6.26 mm, the hinge model: 6.38° and 6.52 mm). Our proposed ultrasound tracking system has the potential of measuring direct bone kinematics, thereby mitigating the influence and propagation of STA. Consequently, this technique could be considered as an alternative method for measuring 6-DOF tibiofemoral kinematics, which may be adopted in gait analysis and clinical practice.     

Joint kinematics estimation using a multi-body kinematics optimisation and an extended Kalman filter,and embedding a soft tissue artefact model

To reduce the impact of the soft tissue artefact (STA) on the estimate of skeletal movement using stereophotogrammetric and skin-marker data, multi-body kinematics optimisation (MKO) and extended Kalman filters (EKF) have been proposed. This paper assessed the feasibility and efficiency of these methods when they embed a mathematical model of the STA and simultaneously estimate the ankle, knee and hip joint kinematics and the model parameters. A STA model was used that provides an estimate of the STA affecting the marker-cluster located on a body segment as a function of the kinematics of the adjacent joints. The MKO and the EKF were implemented with and without the STA model. To assess these methods, intra-cortical pin and skin markers located on the thigh, shank, and foot of three subjects and tracked during the stance phase of running were used. Embedding the STA model in MKO and EKF reduced the average RMS of marker tracking from 12.6 to 1.6 mm and from 4.3 to 1.9 mm, respectively, showing that a STA model trial-specific calibration is feasible. Nevertheless, with the STA model embedded in MKO, the RMS difference between the estimated and the reference joint kinematics determined from the pin markers slightly increased (from 2.0 to 2.1 deg) On the contrary, when the STA model was embedded in the EKF, this RMS difference was slightly reduced (from 2.0 to 1.7 deg) thus showing a better potentiality of this method to attenuate STA effects and improve the accuracy of joint kinematics estimate.     

Kinematic models of the upper limb joints for multibody kinematics optimisation: An overview

Soft tissue artefact (STA), i.e. the motion of the skin, fat and muscles gliding on the underlying bone, may lead to a marker position error reaching up to 8.7 cm for the particular case of the scapula. Multibody kinematics optimisation (MKO) is one of the most efficient approaches used to reduce STA. It consists in minimising the distance between the positions of experimental markers on a subject skin and the simulated positions of the same markers embedded on a kinematic model. However, the efficiency of MKO directly relies on the chosen kinematic model. This paper proposes an overview of the different upper limb models available in the literature and a discussion about their applicability to MKO.The advantages of each joint model with respect to its biofidelity to functional anatomy are detailed both for the shoulder and the forearm areas. Models capabilities of personalisation and of adaptation to pathological cases are also discussed. Concerning model efficiency in terms of STA reduction in MKO algorithms, a lack of quantitative assessment in the literature is noted. In priority, future studies should concern the evaluation and quantification of STA reduction depending on upper limb joint constraints.     

Effect of various upper limb multibody models on soft tissue artefact correction: A case study

Soft tissue artefacts (STA) introduce errors in joint kinematics when using cutaneous markers, especially on the scapula. Both segmental optimisation and multibody kinematics optimisation (MKO) algorithms have been developed to improve kinematics estimates. MKO based on a chain model with joint constraints avoids apparent joint dislocation but is sensitive to the biofidelity of chosen joint constraints. Since no recommendation exists for the scapula, our objective was to determine the best models to accurately estimate its kinematics. One participant was equipped with skin markers and with an intracortical pin screwed in the scapula. Segmental optimisation and MKO for 24-chain models (including four variations of the scapulothoracic joint) were compared against the pin-derived kinematics using root mean square error (RMSE) on Cardan angles. Segmental optimisation led to an accurate scapula kinematics (1.1° ≤ RMSE ≤ 3.3°) even for high arm elevation angles. When MKO was applied, no clinically significant difference was found between the different scapulothoracic models (0.9° ≤ RMSE ≤ 4.1°) except when a free scapulothoracic joint was modelled (1.9° ≤ RMSE ≤ 9.6°). To conclude, using MKO as a STA correction method was not more accurate than segmental optimisation for estimating scapula kinematics.     

A regression-based 3-D shoulder rhythm

In biomechanical modeling of the shoulder, it is important to know the orientation of each bone in the shoulder girdle when estimating the loads on each musculoskeletal element. However, because of the soft tissue overlying the bones, it is difficult to accurately derive the orientation of the clavicle and scapula using surface markers during dynamic movement. The purpose of this study is to develop two regression models which predict the orientation of the clavicle and the scapula. The first regression model uses humerus orientation and individual factors such as age, gender, and anthropometry data as the predictors. The second regression model includes only the humerus orientation as the predictor. Thirty-eight participants performed 118 static postures covering the volume of the right hand reach. The orientation of the thorax, clavicle, scapula and humerus were measured with a motion tracking system. Regression analysis was performed on the Euler angles decomposed from the orientation of each bone from 26 randomly selected participants. The regression models were then validated with the remaining 12 participants. The results indicate that for the first model, the r² of the predicted orientation of the clavicle and the scapula ranged between 0.31 and 0.65, and the RMSE obtained from the validation dataset ranged from 6.92° to 10.39°. For the second model, the r² ranged between 0.19 and 0.57, and the RMSE obtained from the validation dataset ranged from 6.62° and 11.13°. The derived regression-based shoulder rhythm could be useful in future biomechanical modeling of the shoulder.     

On the kinematic modelling and the parameter estimation of the human shoulder.

This paper presents some results on the modelling and the corresponding parameter estimation of the human shoulder. This system consists of the clavicle, the scapula, the humerus and the various joints between these bodies and the trunk through the sternum; it will be represented as a succession of a rotational joint between the sternum and the clavicle and a constant distance joint, representing the scapula between, the clavicle and the humerus head. The parameters of this system are the components of the position vectors of the joint characteristic points (the corresponding centres of the rotations). Experimental results are presented as well as a validation of the proposed model.     

Multi-body optimization with subject-specific knee models: performance at high knee flexion angles

When estimating knee kinematics from skin markers and stereophotogrammetry, multi-body optimization (MBO) has provided promising results for reducing soft tissue artefacts (STA), but can still be improved. The goal of this study was to assess the performance of MBO with subject-specific knee models at high knee flexion angles (up to 110°) against knee joint kinematics measured by magnetic resonance imaging. Eight subjects were recruited. MBO with subject-specific knee models was more effective in compensating STA compared to no kinematic and spherical constraints, in particular for joint displacements. Moreover, it seems to be more reliable over large ranges of knee flexion angle. The ranges of root mean square errors for knee rotations/displacements were 3.0°–9.2°/1.3–3.5 mm for subject-specific knee models, 6.8°–8.7°/6.0–12.4 mm without kinematic constraint and 7.1°–9.8°/4.9–12.5 mm for spherical constraints.     

Evaluation of regression-based 3-D shoulder rhythms

The movements of the humerus, the clavicle, and the scapula are not completely independent. The coupled pattern of movement of these bones is called the shoulder rhythm. To date, multiple studies have focused on providing regression-based 3-D shoulder rhythms, in which the orientations of the clavicle and the scapula are estimated by the orientation of the humerus. In this study, six existing regression-based shoulder rhythms were evaluated by an independent dataset in terms of their predictability. The datasets include the measured orientations of the humerus, the clavicle, and the scapula of 14 participants over 118 different upper arm postures. The predicted orientations of the clavicle and the scapula were derived from applying those regression-based shoulder rhythms to the humerus orientation. The results indicated that none of those regression-based shoulder rhythms provides consistently more accurate results than the others. For all the joint angles and all the shoulder rhythms, the RMSE are all greater than 5°. Among those shoulder rhythms, the scapula lateral/medial rotation has the strongest correlation between the predicted and the measured angles, while the other thoracoclavicular and thoracoscapular bone orientation angles only showed a weak to moderate correlation. Since the regression-based shoulder rhythm has been adopted for shoulder biomechanical models to estimate shoulder muscle activities and structure loads, there needs to be further investigation on how the predicted error from the shoulder rhythm affects the output of the biomechanical model.     

The accuracy of measuring glenohumeral motion with a surface humeral cuff

Conclusions about normal and pathologic shoulder motion are frequently made from studies using skin surface markers, yet accuracy of such sensors representing humeral motion is not well known. Nineteen subjects were investigated with flock of birds electromagnetic sensors attached to transcortical pins placed into the scapula and humerus, and a thermoplastic cuff secured on the arm. Subjects completed two repetitions of raising and lowering the arm in the sagittal, scapular and coronal planes, as well as shoulder internal and external rotation with the elbow at the side and abducted to 90°. Humeral motion was recorded simultaneously from surface and bone fixed sensors. The average magnitude of error was calculated for the surface and bone fixed measurements throughout the range of motion. ANOVA tested for differences across angles of elevation, raising and lowering, and differences in body mass index. For all five motions tested, the plane of elevation rotation average absolute error ranged from 0-2°, while the humeral elevation rotation average error ranged from 0-4°. The axial rotation average absolute error was much greater, ranging from 5° during elevation motions to approaching 30° at maximum excursion of internal/external rotation motions. Average absolute error was greater in subjects with body mass index greater than 25. Surface sensors are an accurate way of measuring humeral elevation rotations and plane of elevation rotations. Conversely, there is a large amount of average error for axial rotations when using a humeral cuff to measure glenohumeral internal/external rotation as the primary motion.     

Scapular taping alters kinematics in asymptomatic subjects

BackgroundScapular taping is frequently used in the management of shoulder pain and as a part of injury prevention strategies in sports. It is believed to alter scapular kinematics and restore normal motion. However, there is little evidence to support its use. The aim of the study was to investigate the effect of shoulder taping on the scapular kinematics of asymptomatic subjects.MethodThirteen asymptomatic subjects performed elevations in the sagittal and scapular planes with no tape and after the application of tape. A motion tracking system and a scapula locator method were used to measure the shoulder movement. Co-ordinate frames were defined for the thorax, humerus and scapula and Euler angles were used to calculate joints rotations.ResultsScapular taping increased the scapular external and upward rotations and posterior tilt in elevations in the sagittal plane (p < 0.001). In the scapular plane, taping increased scapular external rotation (p < 0.05).ConclusionsTaping affects scapulothoracic kinematics in asymptomatic subjects. The effect may be different for different planes of movement. The findings have implications on the use of taping as a preventive measure in high-risk groups. Further work is needed to assess the effect of taping on symptomatic populations.     

Error propagation from kinematic data to modeled muscle-tendon lengths during walking

Kinematic data from 3D gait analysis together with musculoskeletal modeling techniques allow the derivation of muscle-tendon lengths during walking. However, kinematic data are subject to soft tissue artifacts (STA), referring to skin marker displacements during movement. STA are known to significantly affect the computation of joint kinematics, and would therefore also have an effect on muscle-tendon lengths which are derived from the segmental positions. The present study aimed to introduce an analytical approach to calculate the error propagation from STA to modeled muscle-tendon lengths. Skin marker coordinates were assigned uncorrelated, isotropic error functions with given standard deviations accounting for STA. Two different musculoskeletal models were specified; one with the joints moving freely in all directions, and one with the joints constrained to rotation but no translation. Using reference kinematic data from two healthy boys (mean age 9 y 5 m), the propagation of STA to muscle-tendon lengths was quantified for semimembranosus, gastrocnemius and soleus. The resulting average SD ranged from 6% to 50% of the normalized muscle-tendon lengths during gait depending on the muscle, the STA magnitudes and the musculoskeletal model. These results highlight the potential impact STA has on the biomechanical analysis of modeled muscle-tendon lengths during walking, and suggest the need for caution in the clinical interpretation of muscle-tendon lengths derived from joint kinematics.     

A new method for motion capture of the scapula using an optoelectronic tracking device: a feasibility study

Optoelectronic tracking systems are rarely used in 3D studies examining shoulder movements including the scapula. Among the reasons is the important slippage of skin markers with respect to scapula. Methods using electromagnetic tracking devices are validated and frequently applied. Thus, the aim of this study was to develop a new method for in vivo optoelectronic scapular capture dealing with the accepted accuracy issues of validated methods.

Eleven arm positions in three anatomical planes were examined using five subjects in static mode. The method was based on local optimisation, and recalculation procedures were made using a set of five scapular surface markers.

The scapular rotations derived from the recalculation-based method yielded RMS errors comparable with the frequently used electromagnetic scapular methods (RMS up to 12.6° for 150° arm elevation). The results indicate that the present method can be used under careful considerations for 3D kinematical studies examining different shoulder movements.     

Effect of axis alignment on in vivo shoulder kinematics

Background. To describe 3D shoulder joint movements, the International Society of Biomechanics (ISB) recommends using segment coordinate systems (SCSs) on the humerus, scapula and thorax, and joint coordinate systems (JCSs) on the shoulder. However, one of the remaining problems is how to define the zero angles when the arm is in an initial reference position. The aim of this paper is to compare various methods of determining the JCSs of the shoulder that make it possible to define the zero angles of the arm in the resting position.

Methods. Able-bodied subjects performed elevation movements in the scapular plane, specifically neutral, internal and external rotations of the humerus. The initial humerus position (at the beginning of the arm movement) and range of motion were analysed for the purpose of clinical interpretation of arm attitude and movement. The following four different JCSs were explored: (1) the standard JCS, defined as recommended by the ISB, (2) a first aligned JCS, where the humerus SCS is initially aligned with the scapula SCS, (3) a second aligned JCS, where the opposite operation is performed and 4) a third aligned JCS, where both the humerus and the scapular SCS are initially aligned with the thorax SCS.

Findings. The second aligned JCS was the only method that did not produce any exaggerated range of movement in either anatomical plane.

Interpretation. Mathematical JCS alignment allows clearer clinical interpretation of arm attitude and movement.     

Effect of axis alignment on in vivo shoulder kinematics

BACKGROUND. To describe 3D shoulder joint movements, the International Society of Biomechanics (ISB) recommends using segment coordinate systems (SCSs) on the humerus, scapula and thorax, and joint coordinate systems (JCSs) on the shoulder. However, one of the remaining problems is how to define the zero angles when the arm is in an initial reference position. The aim of this paper is to compare various methods of determining the JCSs of the shoulder that make it possible to define the zero angles of the arm in the resting position. METHODS. Able-bodied subjects performed elevation movements in the scapular plane, specifically neutral, internal and external rotations of the humerus. The initial humerus position (at the beginning of the arm movement) and range of motion were analysed for the purpose of clinical interpretation of arm attitude and movement. The following four different JCSs were explored: (1) the standard JCS, defined as recommended by the ISB, (2) a first aligned JCS, where the humerus SCS is initially aligned with the scapula SCS, (3) a second aligned JCS, where the opposite operation is performed and 4) a third aligned JCS, where both the humerus and the scapular SCS are initially aligned with the thorax SCS. FINDINGS. The second aligned JCS was the only method that did not produce any exaggerated range of movement in either anatomical plane. INTERPRETATION. Mathematical JCS alignment allows clearer clinical interpretation of arm attitude and movement.     

Soft tissue artefacts of skin markers on the lower limb during cycling: Effects of joint angles and pedal resistance

Soft tissue artefacts (STA) are a major error source in skin marker-based measurement of human movement, and are difficult to eliminate non-invasively. The current study quantified in vivo the STA of skin markers on the thigh and shank during cycling, and studied the effects of knee angles and pedal resistance by using integrated 3D fluoroscopy and stereophotogrammetry. Fifteen young healthy adults performed stationary cycling with and without pedal resistance, while the marker data were measured using a motion capture system, and the motions of the femur and tibia/fibula were recorded using a bi-plane fluoroscopy-to-CT registration method. The STAs with respect to crank and knee angles over the pedaling cycle, as well as the within-cycle variations, were obtained and compared between resistance conditions. The thigh markers showed greater STA than the shank ones, the latter varying linearly with adjacent joint angles, the former non-linearly with greater within-cycle variability. Both STA magnitudes and within-cycle variability were significantly affected by pedal resistance (p < 0.05). The STAs appeared to be composed of one component providing the stable and consistent STA patterns and another causing their variations. Mid-segment markers experienced smaller STA ranges than those closer to a joint, but tended to have greater variations primarily associated with pedal resistance and muscle contractions. The current data will be helpful for a better choice of marker positions for data collection, and for developing methods to compensate for both stable and variation components of the STA.     

Improvements in measuring shoulder joint kinematics

For many clinical applications it is necessary to non-invasively determine shoulder motion during dynamic movements, and in such cases skin markers are favoured. However, as skin markers may not accurately track the underlying bone motion the methods currently used must be refined. Furthermore, to determine the motion of the shoulder a model is required to relate the obtained marker trajectories to the shoulder kinematics. In Wu et al. (2005) the International Society of Biomechanics (ISB) proposed a shoulder model based on the position of bony landmarks. A limitation of the ISB recommendations is that the reference positions of the shoulder joints are not standardized. The aims of this research project were to develop a method to accurately determine shoulder kinematics using skin markers, and to investigate the effect of introduction of a standardized reference configuration. Fifteen subjects, free from shoulder pathology, performed arm elevations while skin marker trajectories were tracked. Shoulder kinematics were reconstructed using a chain model and extended Kalman filter. The results revealed significant differences between the kinematics obtained with and without introduction of the reference configuration. The curves of joint angle tended towards 0° for 0° of humerus elevation when the reference configuration was introduced. In conclusion, the shoulder kinematics obtained with introduction of the reference configuration were found to be easier to interpret than those obtained without introduction of the reference configuration.