Can a reduction approach predict reliable joint contact and musculo-tendon forces?

Musculoskeletal models generally solve the muscular redundancy by numerical optimisation. They have been extensively validated using instrumented implants. Conversely, a reduction approach considers only one flexor or extensor muscle group at the time to equilibrate the inter-segmental joint moment. It is not clear if such models can still predict reliable joint contact and musculo-tendon forces during gait. Tibiofemoral contact force and gastrocnemii, quadriceps, and hamstrings musculo-tendon forces were estimated using a reduction approach for five subjects walking with an instrumented prosthesis. The errors in the proximal-distal tibiofemoral contact force fell in the range (0.3-0.9 body weight) reported in the literature for musculoskeletal models using numerical optimisation. The musculo-tendon forces were in agreement with the EMG envelops and appeared comparable to the ones reported in the literature with generic musculoskeletal models. Although evident simplifications and limitations, it seems that the reduction approach can provided quite reliable results. It can be a useful pedagogical tool in biomechanics, e.g. to illustrate the theoretical differences between inter-segmental and contact forces, and can provide a first estimate of the joint loadings in subjects with limited musculoskeletal deformities and neurological disorders.

Error performances of a model-based biplane fluoroscopic system for tracking knee prosthesis during treadmill gait task.

Roentgen stereophotogrammetry analysis technique allows an accurate measurement of knee joint prosthesis position and orientation using two X-ray images. Although this technique is used generally during static procedure, it is possible to use it with a biplane fluoroscopic system to measure the prosthesis kinematics during functional tasks (e.g., gait, squat, jump) performed in a laboratory environment. However, the performance of the system in terms of errors for the measurements and the model-based matching algorithm are not well known for dynamic tasks such as walking. The goal of this study was to estimate the static and dynamic errors of a model-based biplane fluoroscopic system for a treadmill gait task and analyze the error performance according to the speed and location of the knee joint prosthesis relative to X-ray sources. The results show a static maximum error (RMSE) of 0.13° for orientation and 0.06 mm for position for prosthesis components. The dynamic errors were different for each axis of the acquisition system and each prosthesis component. The largest dynamic error was along the vertical axis for the position (RMSE = 2.42 mm) and along the medio-lateral axis (perpendicular to movement) for the orientation (RMSE = 0.95°). As expected, the error depends on the distance between the prosthesis and the source in the acquisition system as well as the linear and angular velocity of the movement. The most accurate dynamic measure was around the centroid of the acquisition system, while kinematics measurements close to the X-rays detectors gave the worst errors.

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.

Bone orientation and position estimation errors using Cosserat point elements and least squares methods: Application to gait.

The aim of this study was to analyze the accuracy of bone pose estimation based on sub-clusters of three skin-markers characterized by triangular Cosserat point elements (TCPEs) and to evaluate the capability of four instantaneous physical parameters, which can be measured non-invasively in vivo, to identify the most accurate TCPEs. Moreover, TCPE pose estimations were compared with the estimations of two least squares minimization methods applied to the cluster of all markers, using rigid body (RBLS) and homogeneous deformation (HDLS) assumptions. Analysis was performed on previously collected in vivo treadmill gait data composed of simultaneous measurements of the gold-standard bone pose by bi-plane fluoroscopy tracking the subjects' knee prosthesis and a stereophotogrammetric system tracking skin-markers affected by soft tissue artifact. Femur orientation and position errors estimated from skin-marker clusters were computed for 18 subjects using clusters of up to 35 markers. Results based on gold-standard data revealed that instantaneous subsets of TCPEs exist which estimate the femur pose with reasonable accuracy (median root mean square error during stance/swing: 1.4/2.8deg for orientation, 1.5/4.2mm for position). A non-invasive and instantaneous criteria to select accurate TCPEs for pose estimation (4.8/7.3deg, 5.8/12.3mm), was compared with RBLS (4.3/6.6deg, 6.9/16.6mm) and HDLS (4.6/7.6deg, 6.7/12.5mm). Accounting for homogeneous deformation, using HDLS or selected TCPEs, yielded more accurate position estimations than RBLS method, which, conversely, yielded more accurate orientation estimations. Further investigation is required to devise effective criteria for cluster selection that could represent a significant improvement in bone pose estimation accuracy.

Standardization proposal of soft tissue artefact description for data sharing in human motion measurements.

Soft tissue artefact (STA) represents one of the main obstacles for obtaining accurate and reliable skeletal kinematics from motion capture. Many studies have addressed this issue, yet there is no consensus on the best available bone pose estimator and the expected errors associated with relevant results. Furthermore, results obtained by different authors are difficult to compare due to the high variability and specificity of the phenomenon and the different metrics used to represent these data. Therefore, the aim of this study was twofold: firstly, to propose standards for description of STA; and secondly, to provide illustrative STA data samples for body segments in the upper and lower extremities and for a range of motor tasks specifically, level walking, stair ascent, sit-to-stand, hip- and knee-joint functional movements, cutting motion, running, hopping, arm elevation and functional upper-limb movements. The STA dataset includes motion of the skin markers measured in vivo and ex vivo using stereophotogrammetry as well as motion of the underlying bones measured using invasive or bio-imaging techniques (i.e., X-ray fluoroscopy or MRI). The data are accompanied by a detailed description of the methods used for their acquisition, with information given about their quality as well as characterization of the STA using the proposed standards. The availability of open-access and standard-format STA data will be useful for the evaluation and development of bone pose estimators thus contributing to the advancement of three-dimensional human movement analysis and its translation into the clinical practice and other applications.

Evaluation of knee functional calibration with and without the effect of soft tissue artefact.

Functional calibration methods were devised to improve repeatability and accuracy of the knee flexion-extension axis, which is used to define the medio-lateral axis of the femur coordinate system in gait analysis. Repeatability of functional calibration methods has been studied extensively in healthy individuals, but not accuracy in the absence of a benchmark knee axis. We captured bi-plane fluoroscopy data of the knee joint in 17 subjects with unilateral total knee arthroplasty during treadmill walking. The prosthesis provided a benchmark knee axis to evaluate the functional calibration methods. Stereo-photogrammetry data of thigh and shank marker clusters were captured simultaneously to investigate the effect of soft tissue artefact (STA). Three methods were tested, the Axis Transformation Technique (ATT) finds the best single fixed axis of rotation, 2DofKnee finds the axis that minimises knee varus-valgus and trajAJC finds the axis perpendicular to the trajectory, in the transverse plane of the femur, of a point located on the longitudinal axis of the tibia. Using fluoroscopy data, functional axes formed an angle of less than 2° in the transverse plane with the benchmark axis. True internal-external range of movement was correlated with decreased accuracy for ATT, while varus-valgus range of movement was correlated with decreased accuracy for 2DofKnee and trajAJC. STA had negative impact on accuracy and variability. Using stereo-photogrammetry data, the accuracy of 2DofKnee was 1.7°(SD: 5.1°), smaller than ATT 2.9°(SD: 5.1°) but not to trajAJC 1.7°(SD: 5.2°). Our results confirm that of previous studies, which utilised the femur condylar axis as reference.

Soft tissue artifact distribution on lower limbs during treadmill gait: Influence of skin markers' location on cluster design.

Segment poses and joint kinematics estimated from skin markers are highly affected by soft tissue artifact (STA) and its rigid motion component (STARM). While four marker-clusters could decrease the STA non-rigid motion during gait activity, other data, such as marker location or STARM patterns, would be crucial to compensate for STA in clinical gait analysis. The present study proposed 1) to devise a comprehensive average map illustrating the spatial distribution of STA for the lower limb during treadmill gait and 2) to analyze STARM from four marker-clusters assigned to areas extracted from spatial distribution. All experiments were realized using a stereophotogrammetric system to track the skin markers and a bi-plane fluoroscopic system to track the knee prosthesis. Computation of the spatial distribution of STA was realized on 19 subjects using 80 markers apposed on the lower limb. Three different areas were extracted from the distribution map of the thigh. The marker displacement reached a maximum of 24.9 mm and 15.3 mm in the proximal areas of thigh and shank, respectively. STARM was larger on thigh than the shank with RMS error in cluster orientations between 1.2° and 8.1°. The translation RMS errors were also large (3.0 mm to 16.2 mm). No marker-cluster correctly compensated for STARM. However, the coefficient of multiple correlations exhibited excellent scores between skin and bone kinematics, as well as for STARM between subjects. These correlations highlight dependencies between STARM and the kinematic components. This study provides new insights for modeling STARM for gait activity.

Biomechanical ToolKit: Open-source framework to visualize and process biomechanical data.

C3D file format is widely used in the biomechanical field by companies and laboratories to store motion capture systems data. However, few software packages can visualize and modify the integrality of the data in the C3D file. Our objective was to develop an open-source and multi-platform framework to read, write, modify and visualize data from any motion analysis systems using standard (C3D) and proprietary file formats (used by many companies producing motion capture systems). The Biomechanical ToolKit (BTK) was developed to provide cost-effective and efficient tools for the biomechanical community to easily deal with motion analysis data. A large panel of operations is available to read, modify and process data through C++ API, bindings for high-level languages (Matlab, Octave, and Python), and standalone application (Mokka). All these tools are open-source and cross-platform and run on all major operating systems (Windows, Linux, MacOS X).

Cognitive loading affects motor awareness and movement kinematics but not locomotor trajectories during goal-directed walking in a virtual reality environment.

The primary purpose of this study was to investigate the effects of cognitive loading on movement kinematics and trajectory formation during goal-directed walking in a virtual reality (VR) environment. The secondary objective was to measure how participants corrected their trajectories for perturbed feedback and how participants' awareness of such perturbations changed under cognitive loading. We asked 14 healthy young adults to walk towards four different target locations in a VR environment while their movements were tracked and played back in real-time on a large projection screen. In 75% of all trials we introduced angular deviations of ±5° to ±30° between the veridical walking trajectory and the visual feedback. Participants performed a second experimental block under cognitive load (serial-7 subtraction, counter-balanced across participants). We measured walking kinematics (joint-angles, velocity profiles) and motor performance (end-point-compensation, trajectory-deviations). Motor awareness was determined by asking participants to rate the veracity of the feedback after every trial. In-line with previous findings in natural settings, participants displayed stereotypical walking trajectories in a VR environment. Our results extend these findings as they demonstrate that taxing cognitive resources did not affect trajectory formation and deviations although it interfered with the participants' movement kinematics, in particular walking velocity. Additionally, we report that motor awareness was selectively impaired by the secondary task in trials with high perceptual uncertainty. Compared with data on eye and arm movements our findings lend support to the hypothesis that the central nervous system (CNS) uses common mechanisms to govern goal-directed movements, including locomotion. We discuss our results with respect to the use of VR methods in gait control and rehabilitation.

Soft tissue artifact assessment during treadmill walking in subjects with total knee arthroplasty.

Accurate measurement of knee kinematics during functional activities suffers mainly from soft tissue artifact (STA): the combination of local surface deformations and rigid movement of markers relative to the underlying bone (also called rigid STA movement: RSTAM). This study proposes to assess RSTAM on the thigh, shank, and knee joint and to observe possible features between subjects. Nineteen subjects with knee arthroplasty were asked to walk on a treadmill while a biplane fluoroscopic system (X-rays) and a stereophotogrammetric system (skin markers) recorded their knee movement. The RSTAM was defined as the rigid movement of the cluster of skin markers relative to the prosthesis. The results showed that RSTAM amplitude represents approximately 80-100% of the STA. The vertical axis of the anatomical frame of the femur was influenced the most by RSTAM. Combined with tibial error, internal/external rotation angle and distraction-compression were the knee kinematics parameters most affected by RSTAM during the gait cycle, with average rms values of 3.8° and 11.1 mm. This study highlighted higher RSTAM during the swing phase particularly in the thigh segment and suggests new features for RSTAM such as the particular shape of some RSTAM waveforms and the absence of RSTAM in certain kinematics during the gait phases. The comparison of coefficient of multiple correlations showed some similarities of RSTAM between subjects, while some correlations were found with gait speed and BMI. These new insights could potentially allow the development of new methods of compensation to avoid STA.

In vitro quantification of the performance of model-based mono-planar and bi-planar fluoroscopy for 3D joint kinematics estimation.

Model-based mono-planar and bi-planar 3D fluoroscopy methods can quantify intact joints kinematics with performance/cost trade-off. The aim of this study was to compare the performances of mono- and bi-planar setups to a marker-based gold-standard, during dynamic phantom knee acquisitions. Absolute pose errors for in-plane parameters were lower than 0.6 mm or 0.6° for both mono- and bi-planar setups. Mono-planar setups resulted critical in quantifying the out-of-plane translation (error < 6.5 mm), and bi-planar in quantifying the rotation along bone longitudinal axis (error < 1.3°). These errors propagated to joint angles and translations differently depending on the alignment of the anatomical axes and the fluoroscopic reference frames. Internal-external rotation was the least accurate angle both with mono- (error < 4.4°) and bi-planar (error < 1.7°) setups, due to bone longitudinal symmetries. Results highlighted that accuracy for mono-planar in-plane pose parameters is comparable to bi-planar, but with halved computational costs, halved segmentation time and halved ionizing radiation dose. Bi-planar analysis better compensated for the out-of-plane uncertainty that is differently propagated to relative kinematics depending on the setup. To take its full benefits, the motion task to be investigated should be designed to maintain the joint inside the visible volume introducing constraints with respect to mono-planar analysis.