Arnaud Barré

Biomechanical ToolKit

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).

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.

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.

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.

Estimation of prosthetic knee angles via data fusion of implantable and wearable sensors

In this work, we studied a combination of embedded magnetic measurement system in a knee prosthesis and wearable inertial sensors to estimate two knee joint rotations namely flexion-extension and internal-external rotations. The near optimal sensor configuration was designed for implantable measurement system, and linear estimators were used to estimate the mentioned angles. This system was separately evaluated in a mechanical knee simulator and the effect of the imposed Abduction-Adduction rotation was also studied on the angle estimations. To reduce the power consumption of the internal system, we reduced the sampling rate and duty cycled the implantable sensors. Then we compensated the lack of information via use of kinematic information from wearable sensors to provide accurate angle estimations. As long as this smart prosthesis is not implanted yet on a subject, the angles estimations from implantable sensors and wearable sensors are realistically simulated for four subjects. The simulated angle estimations were fed to the designed data fusion algorithms to boost the estimation performance. The results were considerably improved via use of Maximum Entropy Ordered Weighted Averaging (MEOWA) fusion for flexion angles, but not for internal-external angle estimations.

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.

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.

O 111 - accuracy of the conventional gait model: preliminary results

The Conventional Gait Model (CGM), distributed as Vicon Plugin gait (Vicon PiG) became a standard in the field of 3D Clinical Gait Analysis. Its reliability is assessed thought repeatability tests. On the other hand, accuracy of the CGM in terms of underlying bone motion has never been quantified. It’s all the more important CGM outputs might orientate a patient towards bone surgery. Thanks to a consensus, data from invasive approaches are available in open-access. They can serve as basis for model validation. This communication proposes to assess the knee kinematic accuracy of the CGM with fluoroscopic data during a gait cycle.