Multibody Kinematics Optimization for the Estimation of Upper and Lower Limb Human Joint Kinematics: A Systematized Methodological Review

Implication of inter-joint coordination on the limb symmetry index measured during the seated single-arm horizontal push test

Introduction

The seated single-arm horizontal push test (SSAHPT) could be used to assess unilateral upper-extremity power. While superior performance of the dominant side compared to the nondominant one (LSI) is often observed, causes of this bilateral imbalance remain unclear. This study aimed to assess the influence of upper-extremity dominance on both inter-joint coordination and joint contribution in SSAHPT.

Methods

Twenty-five healthy male athletes were fitted with reflective markers and performed SSAHPT with the dominant and nondominant sides. Humerothoracic, elbow and wrist joint contributions to the horizontal medicine ball velocity were computed. The temporal occurrence of joint peak contribution was used to assess inter-joint coordination.

Results

The temporal occurrence of joint peak contribution occurred in a proximo-to-distal sequence at the dominant side, while at the nondominant side, joint peak contribution first occurred at shoulder, then simultaneously at elbow and wrist. The elbow joint contributed the most to the horizontal medicine ball velocity, but its relative contribution was significantly greater for the nondominant limb than the dominant one (p < 0.05).

Discussion

These findings highlight that SSAHPT bilateral asymmetry is explained by a change in motor patterns, as inter-joint coordination and contribution, between the dominant and nondominant sides. From a practical perspective, our findings suggest that for healthy athletes, firstly the LSI observed during SSAHPT may not be used as a good indicator of bilateral imbalance in upper-extremity power, and secondly SSAHPT performance reflects primarily elbow joint velocity capacities and then shoulder ones.

The effects of markerless inconsistencies are at least as large as the effects of the marker-based soft tissue artefact

The soft tissue artefact is a well-known issue for marker-based motion analysis and markerless motion analysis is by definition free from this artefact. The goal of this study is to compare the limb skeletal inconsistencies generated by the neural networks in markerless motion capture and generated by the soft tissue artefact in marker-based motion capture using retrospective data. Sixteen volunteers were included and were asked to perform four motor tasks (walk, sit-to-stand, stand-to-sit, countermovement jump) acquired with ten optoelectronic cameras and ten video cameras. Keypoint identification was performed in videos using Openpose. Triangulation and data augmentation algorithms were used to get an extension of anatomical landmarks. Then, lower limb skeletal inconsistencies (length variations and apparent joint dislocations) for both marker-based and markerless data were analyzed. The length variation of the lower limbs was generally larger with markerless data (triangulated keypoints and augmented anatomical landmarks) as found with marker-based data. Mean dislocations were found smaller for the markerless data than for the marker-based data for the hip only. The effect of the markerless inconsistencies are at least as large as the effect of the soft tissue artefact except for the hip dislocation, probably due to the soft tissue artefact that is main at the pelvis level. These inconsistencies are related to different phenomena than skin sliding as there are no correlation with joint flexion-extension angles. Thus, compensation methods proposed for soft tissue artefact are not all applicable.

Influence of multibody kinematic optimisation pipeline on marker residual errors

Residual errors are used as a goodness-of-fit metric of the musculoskeletal model to the experimental data in multibody kinematic optimisation (MKO) analyses. Despite many studies reporting residual errors as a criterion for evaluating their proposed algorithm or model, the validity of residual errors as a performance metric has been questioned, with studies indicating a non-causal relationship between residual errors and computed joint angles. Additionally, the impact of different parameters of an MKO pipeline on residual errors has not been analysed. In our study, we have investigated the effect of each step of the MKO pipeline on residual errors, and the existence of a causal relationship between residual errors and joint angles. Increases in residual errors from the baseline model (13.84 [12.72, 15.15]mm) were obtained for: models with marker registration errors of 1.25 cm (16.36 [15.37, 17.57]mm); models with segment scaling errors of 1.25 cm (14.84 [13.77, 16.24]mm); variation in marker weighting scheme (15.28[14.00, 16.85]mm); and models with differing joint constraints (18.21[17.37, 19.11]mm). We also observed that significant variation in residual errors results in significant variation in computed joint angles, with increases in residual error positively correlated with increases in joint angle errors when the same MKO pipeline is employed. Our findings support the existence of a causal relationship and present the significant effect the MKO pipeline has on residual errors. We believe our results can further the discussion of residual errors as a goodness-of-fit metric, specifically in the absence of artefact-free bone movement.

Inverse kinematics in cervical spine models: Effects of scaling and model degrees of freedom for extension and flexion movements

Intervertebral kinematics can affect model-predicted loads and strains in the spine; therefore knowledge of expected vertebral kinematics error is important for understanding the limitations of model predictions. This study addressed how different kinematic models of the neck affect the prediction of intervertebral kinematics from markers on the head and trunk. Eight subjects executed head and neck extension-flexion motion with simultaneous motion capture and biplanar dynamic stereo-radiography (DSX) of vertebrae C1-C7. A generic head and neck model in OpenSim was scaled by marker data, and three versions of the model were used with an inverse kinematics solver. The models differed according to the number of independent degrees of freedom (DOF) between the head and trunk: 3 rotational DOF with constraints defining intervertebral kinematics as a function of overall head-trunk motion; 24DOF with 3 independent rotational DOF at each level, skull-T1; 48DOF with 3 rotational and 3 translational DOF at each level. Marker tracking error was lower for scaled models compared to generic models and decreased as model DOF increased. The largest mean absolute error (MAE) was found in extension-flexion angle and anterior-posterior translation at C1-C2, and superior-inferior translation at C2-C3. Model scaling and complexity did not have a statistically significant effect on most error metrics when corrected for multiple comparisons, but ranges of motion were significantly different from DSX in some cases. This study evaluated model kinematics in comparison to gold standard radiographic data and provides important information about intervertebral kinematics error that are foundational to model validity.

The future of in-field sports biomechanics: wearables plus modelling compute real-time in vivo tissue loading to prevent and repair musculoskeletal injuries

This paper explores the use of biomechanics in identifying the mechanistic causes of musculoskeletal tissue injury and degeneration. It appraises how biomechanics has been used to develop training programmes aiming to maintain or recover tissue health. Tissue health depends on the functional mechanical environment experienced by tissues during daily and rehabilitation activities. These environments are the result of the interactions between tissue motion, loading, biology, and morphology. Maintaining health of and/or repairing musculoskeletal tissues requires targeting the "ideal" in vivo tissue mechanics (i.e., loading and deformation), which may be enabled by appropriate real-time biofeedback. Recent research shows that biofeedback technologies may increase their quality and effectiveness by integrating a personalised neuromusculoskeletal modelling driven by real-time motion capture and medical imaging. Model personalisation is crucial in obtaining physically and physiologically valid predictions of tissue biomechanics. Model real-time execution is crucial and achieved by code optimisation and artificial intelligence methods. Furthermore, recent work has also shown that laboratory-based motion capture biomechanical measurements and modelling can be performed outside the laboratory with wearable sensors and artificial intelligence. The next stage is to combine these technologies into well-designed easy to use products to guide training to maintain or recover tissue health in the real-world.

A leg model based on anatomical landmarks to study 3D joint kinematics of walking in Drosophila melanogaster

Walking is the most common form of how animals move on land. The model organism Drosophila melanogaster has become increasingly popular for studying how the nervous system controls behavior in general and walking in particular. Despite recent advances in tracking and modeling leg movements of walking Drosophila in 3D, there are still gaps in knowledge about the biomechanics of leg joints due to the tiny size of fruit flies. For instance, the natural alignment of joint rotational axes was largely neglected in previous kinematic analyses. In this study, we therefore present a detailed kinematic leg model in which not only the segment lengths but also the main rotational axes of the joints were derived from anatomical landmarks, namely, the joint condyles. Our model with natural oblique joint axes is able to adapt to the 3D leg postures of straight and forward walking fruit flies with high accuracy. When we compared our model to an orthogonalized version, we observed that our model showed a smaller error as well as differences in the used range of motion (ROM), highlighting the advantages of modeling natural rotational axes alignment for the study of joint kinematics. We further found that the kinematic profiles of front, middle, and hind legs differed in the number of required degrees of freedom as well as their contributions to stepping, time courses of joint angles, and ROM. Our findings provide deeper insights into the joint kinematics of walking in Drosophila, and, additionally, will help to develop dynamical, musculoskeletal, and neuromechanical simulations.

Bridging the sim2real gap. Investigating deviations between experimental motion measurements and musculoskeletal simulation results-a systematic review

Musculoskeletal simulations can be used to estimate biomechanical variables like muscle forces and joint torques from non-invasive experimental data using inverse and forward methods. Inverse kinematics followed by inverse dynamics (ID) uses body motion and external force measurements to compute joint movements and the corresponding joint loads, respectively. ID leads to residual forces and torques (residuals) that are not physically realistic, because of measurement noise and modeling assumptions. Forward dynamic simulations (FD) are found by tracking experimental data. They do not generate residuals but will move away from experimental data to achieve this. Therefore, there is a gap between reality (the experimental measurements) and simulations in both approaches, the sim2real gap. To answer (patho-) physiological research questions, simulation results have to be accurate and reliable; the sim2real gap needs to be handled. Therefore, we reviewed methods to handle the sim2real gap in such musculoskeletal simulations. The review identifies, classifies and analyses existing methods that bridge the sim2real gap, including their strengths and limitations. Using a systematic approach, we conducted an electronic search in the databases Scopus, PubMed and Web of Science. We selected and included 85 relevant papers that were sorted into eight different solution clusters based on three aspects: how the sim2real gap is handled, the mathematical method used, and the parameters/variables of the simulations which were adjusted. Each cluster has a distinctive way of handling the sim2real gap with accompanying strengths and limitations. Ultimately, the method choice largely depends on various factors: available model, input parameters/variables, investigated movement and of course the underlying research aim. Researchers should be aware that the sim2real gap remains for both ID and FD approaches. However, we conclude that multimodal approaches tracking kinematic and dynamic measurements may be one possible solution to handle the sim2real gap as methods tracking multimodal measurements (some combination of sensor position/orientation or EMG measurements), consistently lead to better tracking performances. Initial analyses show that motion analysis performance can be enhanced by using multimodal measurements as different sensor technologies can compensate each other's weaknesses.

A systematic review of instrumented assessments for upper limb function in cerebral palsy: current limitations and future directions

INTRODUCTION

Recently, interest in quantifying upper limb function in cerebral palsy has grown. However, the lack of reference tasks and protocols, have hindered the development of quantified movement analysis in clinical practice. This study aimed to evaluate existing instrumented assessments of upper limb function in cerebral palsy, with a focus on their clinical applicability, to identify reasons for the lack of adoption and provide recommendations for improving clinical relevance and utility.

METHODS

A systematic review was conducted by a multidisciplinary team of researchers and clinicians (Prospero CRD42023402382). PubMed and Web of Science databases were searched using relevant keywords and inclusion/exclusion criteria.

RESULTS

A total of 657 articles were initially identified, and after the selection process, 76 records were included for analysis comprising a total of 1293 patients with cerebral palsy. The quality assessment of the reviewed studies revealed a moderate overall quality, with deficiencies in sample size justification and participant information. Optoelectronic motion capture systems were predominantly used in the studies (N = 57/76). The population mainly consisted of individuals with spastic cerebral palsy (834/1293) with unilateral impairment (N = 1092/1293). Patients with severe functional impairment (MACS IV and V) were underrepresented with 3.4% of the 754 patients for whom the information was provided. Thirty-nine tasks were used across the articles. Most articles focused on unimanual activities (N = 66/76) and reach or reach and grasp (N = 51/76). Bimanual cooperative tasks only represented 3 tasks present in 4 articles. A total of 140 different parameters were identified across articles. Task duration was the most frequently used parameter and 23% of the parameters were used in only one article.

CONCLUSION

Further research is necessary before incorporating quantified motion analysis into clinical practice. Existing protocols focus on extensively studied populations and rely on costly equipment, limiting their practicality. Standardized unimanual tasks provide limited insights into everyday arm use. Balancing methodological requirements and performance evaluation flexibility is a challenge. Exploring the correlation between outcome parameters and therapeutic guidance could facilitate the integration of quantified movement assessment into treatment pathways.

Does IMU redundancy improve multi-body optimization results to obtain lower-body kinematics? A preliminary study says no

Inertial Measurement Units (IMUs) have been proposed as an ecological alternative to optoelectronic systems for obtaining human body joint kinematics. Tremendous work has been done to reduce differences between kinematics obtained with IMUs and optoelectronic systems, by improving sensor-to-segment calibration, fusion algorithms, and by using Multibody Kinematics Optimization (MKO). However, these improvements seem to reach a barrier, particularly on transverse and frontal planes. Inspired by marker-based MKO approach performed via OpenSim, this study proposes to test whether IMU redundancy with MKO could improve lower-limb kinematics obtained from IMUs. For this study, five subjects were equipped with 11 IMUs and 30 reflective markers tracked by 18 optoelectronic cameras. They then performed gait, cycling, and running actions. Four different lower-limb kinematics were computed: one kinematics based on markers after MKO, one kinematics based on IMUs without MKO, and two based on IMUs after MKO performed with OpenSense (one with, and one without, sensor redundancy). Kinematics were compared via Root Mean Square Difference and correlation coefficients to kinematics based on markers after MKO. Results showed that redundancy does not reduce differences with the kinematics based on markers after MKO on frontal and transverse planes comparatively to classic IMU MKO. Sensor redundancy does not seem to impact lower-limb kinematics on frontal and transverse planes, due to the likelihood of the "rigid component" of soft-tissue artefact impacting all sensors located on one segment.

Is an ellipsoid surface suitable to model the scapulothoracic sliding plane?

Closed loop kinematic chain approaches are commonly used to assess scapular kinematics but with heterogeneous ellipsoid calibration procedures. This study aimed to assess whether an ellipsoid surface can model the scapulothoracic sliding plane and determine the optimal number of static poses to calibrate the ellipsoid parameters. An intracortical pin with a rigid cluster of four reflective markers was inserted into the left scapular spine of two healthy males (P1 and P2). They performed arm elevations, internal rotations, ball throwing, hockey shooting, and eating movements. Ellipsoid radii and center location were functionally calibrated for each participant and each movement, either based on all frames of a movement or based on a reduced number of frames (from 3 to 200 equally position-distributed frames). Across both participants and all movements, ellipsoid radii varied up to 10.2 cm, 3.9 cm, and 18.4 cm in the antero-posterior, medio-lateral, and cranio-caudal directions, respectively. When all frames of a movement were considered for calibration, the median scapula-to-ellipsoid distance was, on average, 0.52 mm and 0.38 mm for P1 and P2, respectively. When only five frames were considered for ellipsoid calibration, the scapula-to-ellipsoid median distance slightly increased with 0.57 mm and 0.47 mm for P1 and P2, respectively. To conclude, this study highlights that an ellipsoid surface may effectively be appropriate to model the scapulothoracic sliding plane, especially when the calibration is functional, participant- and movement-specific. Furthermore, the number of poses required for the ellipsoid calibration can be reduced to five, minimizing the experimental cost.

A simulation study to investigate an extension to the point cluster technique

Joint kinematics are an important and widely utilized metric in quantitative human movement analysis. Typically, trajectory data for skin-mounted markers are collected using stereophotogrammetry, sometimes referred to as optical motion capture, and processed using various mathematical models to estimate joint kinematics (e.g., angles). Among the various sources of noise in optical motion capture data, soft tissue artifacts (STAs) remain a critical source of error. This study investigates the performance of the point cluster technique (PCT), an extension of the PCT using perturbation theory (PCT-PT), and singular value decomposition least squares (SVD-LS) method (as a reference) for 100 different marker configurations on the thigh and shank during treadmill walking. This study provides additional evidence that the PCT method is significantly limited by the underlying mathematical constraints governing its optimization process. Furthermore, the results suggest the PCT-PT method outperforms the PCT method across all performance metrics for both body segments during the entire gait cycle. For position-based metrics, the PCT-PT method provides better estimates than the SVD-LS method for the thigh during majority of the stance phase and provides comparable estimates for the shank during the entire gait cycle. For knee angle estimates, the PCT-PT method provides equivalent results as the SVD-LS method.

Influence of marker weights optimization on scapular kinematics estimated with a multibody kinematic optimization

Scapular kinematic estimates are altered by soft tissue artefacts, therefore experimental and numerical methods should be developed to improve their accuracy. This study aimed to assess the influence of weights applied to the scapula markers within a closed-loop multibody kinematic optimization on scapular kinematic estimates. Fifteen healthy volunteers performed static postures mimicking analytical, daily living and sport movements. Scapulo-thoracic angles were computed either from a scapula locator as the reference, or from a closed-loop multibody-kinematic optimization (MKO) including a participant-specific point-on-ellipsoid scapulothoracic joint. Weights applied to scapula markers in the MKO were optimized to minimize the difference in scapular orientation from the reference. Optimizing weighting sets significantly (p < 0.0001) improved scapular orientation from 0.9° to 12.1° in comparison to scapular kinematics estimated with non-optimized weighting sets. The mean optimized weighting set contained no neglectable weight for all markers from the acromion to the medial border of the scapular spine but showed no significant difference (p = 0.547) compared to homogeneous weights. Optimized weighting sets were participant- and movement- specific. To conclude, homogenous weights applied on redundant markers located from acromion to scapular medial border spine are recommended when estimating scapular kinematics in upper limb MKO.

Estimation of two wear factors for total hip arthroplasty: A simulation study based on musculoskeletal modelling

BACKGROUND

Primary causes of surgical revision after total hip arthroplasty are polyethylene wear and implant loosening. These factors are particularly related to joint friction and thus patients' physical activity. Assessing implant wear over time according to patients' morphology and physical activity level is key to improve follow-up and patients' quality of life.

METHODS

An approach initially proposed for tibiofemoral prosthetic wear estimation was adapted to compute two wear factors (force-velocity, directional wear intensity) using a musculoskeletal model. It was applied on 17 participants with total hip arthroplasty to compute joint angular velocity, contact force, sliding velocity, and wear factors during common daily living activities.

FINDINGS

Differences were observed between gait, sitting down, and standing up tasks. An incremental increase of both global wear factors (time-integral) was observed during gait from slow to fast speeds (p ≤ 0.01). Interestingly, these two wear factors did not result in same trend for sitting down and standing up tasks. Compared to gait, one cycle of sitting down or standing up tends to induce higher friction-related wear but lower cross-shear-related wear. Depending on the wear factor, significant differences can be found between sitting down and gait at slow speed (p ≤ 0.05), and between sitting down (p ≤ 0.05) or standing up (p ≤ 0.05) and gait at fast speed. Furthermore, depending on the activity, wear can be fostered by joint contact force and/or sliding velocity.

INTERPRETATION

This study demonstrated the potential of wear estimation to highlight activities inducing a higher risk of implant wear after total hip arthroplasty from motion capture data.

Comparison of a Scaled Cadaver-Based Musculoskeletal Model With a Clinical Upper Extremity Model

Reliably and accurately estimating joint/segmental kinematics from optical motion capture data has remained challenging. Studies objectively characterizing human movement patterns have typically involved inverse kinematics and inverse dynamics techniques. Subsequent research has included scaled cadaver-based musculoskeletal (MSK) modeling for noninvasively estimating joint and muscle loads. As one of the ways to enhance confidence in the validity of MSK model predictions, the kinematics from the preceding step that drives such a model needs to be checked for agreement or compared with established/widely used models. This study rigorously compares the upper extremity (UE) joint kinematics calculated by the Dutch Shoulder Model implemented in the AnyBody Managed Model Repository (involving multibody kinematics optimization (MKO)) with those estimated by the Vicon Plug-in Gait model (involving single-body kinematics optimization (SKO)). Ten subjects performed three trials of (different types of) reaching tasks in a three-dimensional marker-based optical motion capture laboratory setting. Joint angles, processed marker trajectories, and reconstruction residuals corresponding to both models were compared. Scatter plots and Bland-Altman plots were used to assess the agreement between the two model outputs. Results showed the largest differences between the two models for shoulder, followed by elbow and wrist, with all root-mean-squared differences less than 10 deg (although this limit might be unacceptable for clinical use). Strong-to-excellent Spearman's rank correlation coefficients were found between the two model outputs. The Bland-Altman plots showed a good agreement between most of the outputs. In conclusion, results indicate that these two models with different kinematic algorithms broadly agree with each other, albeit with few key differences.

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.

Optimal estimation of complex aerial movements using dynamic optimisation

When estimating full-body motion from experimental data, inverse kinematics followed by inverse dynamics does not guarantee dynamical consistency of the resulting motion, especially in movements where the trajectory depends heavily on the initial state, such as in free-fall. Our objective was to estimate dynamically consistent joint kinematics and kinetics of complex aerial movements. A 42-degrees-of-freedom model with 95 markers was personalised for five elite trampoline athletes performing various backward and forward twisting somersaults. Using dynamic optimisation, our algorithm estimated joint angles, velocities and torques by tracking the recorded marker positions. Kinematics, kinetics, angular and linear momenta, and marker tracking difference were compared to results of an Extended Kalman Filter (EKF) followed by inverse dynamics. Angular momentum and horizontal linear momentum were conserved throughout the estimated motion, as per free-fall dynamics. Marker tracking difference went from 17 ± 4 mm for the EKF to 36 ± 11 mm with dynamic optimisation tracking the experimental markers, and to 49 ± 9 mm with dynamic optimisation tracking EKF joint angles. Joint angles from the dynamic optimisations were similar to those of the EKF, and joint torques were smoother. This approach satisfies the dynamics of complex aerial rigid-body movements while remaining close to the experimental 3D marker dataset.

Wand-mounted lateral markers are less prone to misplacement and soft-tissue artefacts than skin-mounted markers when using the conventional gait model

BACKGROUND

The conventional gait model (CGM1) is extensively used for 3D clinical gait analysis. It uses lateral wand-mounted markers for the thigh and shank segments to avoid colinearity of the tracking markers. However, gait analysts may be tempted to use skin-mounted markers instead.

RESEARCH QUESTION

Does it matter if the lateral markers for the thigh and shank segments are mounted on wands or directly taped to the skin when using the CGM1?

METHODS

Gait sessions from 147 and 73 patients equipped with wand-mounted and skin-mounted markers, respectively, were extracted from the database of a single clinical gait laboratory. The marker trajectories were reprocessed with the CGM1. The risk of marker colinearity was assessed from the planar angle constructed from the proximal joint center, the lateral joint marker and the lateral segmental marker (i.e. skin or wand). We assessed the effect of marker misplacement and soft-tissue artefact on kinematics.

RESULTS

The averaged planar angles calculated from static ranged from 10° to 30° and 7° to 21° for the skin-mounted thigh and shank markers respectively, while planar angles were always larger than 25° with wand-mounted markers. One cm misplacement of the thigh marker altered hip rotation by 10° if skin-mounted against 5° if wand-mounted. Soft tissue artefact led to 7.6° or 4.3° depending if it was skin- or wand-mounted, respectively.

SIGNIFICANCE

Our analysis showed moderate risk of collinearity, increased effect of STA, and larger potential effect of marker misplacement with the use of skin- rather than wand-mounted markers.

The contribution of multibody optimization when using inertial measurement units to compute lower-body kinematics

Kinematics obtained using Inertial Measurement Units (IMUs) still present significant differences when compared to those obtained using optoelectronic systems. Multibody Optimization (MBO) might diminish these differences by reducing soft-tissue artefacts - probably emphasized when using IMUs - as established for optoelectronic-based kinematics. To test this hypothesis, 15 subjects were equipped with 7 IMUs and 38 reflective markers tracked by 18 optoelectronic cameras. The subjects walked, ran, cycled on an ergocycle, and performed a task which induced joint movements in the transverse and frontal planes. In addition to lower-body kinematics computed using the optoelectronical system data, three IMU-based kinematics were computed: from IMU orientations without MBO; from MBO performed using the OpenSense add-on of the OpenSim software (OpenSim 4.2, Stanford, USA); as outputs from the commercialised MVN MBO (Xsens, Netherlands). Root Mean Square Errors (RMSE), coefficients of correlations, and differences in range of motion were calculated between the three IMU-based methods and the reference kinematics. MVN MBO seems to present a slight advantage over Direct kinematics or OpenSense MBO, since it presents 34 times out of 48 (12 degrees of freedom * 4 sports activities) a mean RMSE inferior to the Direct and OpenSense kinematics. However, it was not always significant and the differences rarely exceeded 2°. This study does not therefore conclude on a significant contribution of MBO in improving lower-body kinematics obtained using IMUs. This lack of results can partly be explained by the weakness of both the kinematic constraints applied to the kinematic chain and segment stiffening. Personalization of the kinematic chain, the use of more than one IMU by segment in order to provide information redundancy, or the use of other approaches based on the Kalman Filter might increase this MBO impact.

Three-Dimensional Quantitative Evaluation of the Scapular Skin Marker Movements in the Upright Posture

Motion capture systems using skin markers are widely used to evaluate scapular kinematics. However, soft-tissue artifact (STA) is a major limitation, and there is insufficient knowledge of the marker movements from the original locations. This study explores a scapular STA, including marker movements with shoulder elevation using upright computed tomography (CT). Ten healthy males (twenty shoulders in total) had markers attached to scapular bony landmarks and underwent upright CT in the reference and elevated positions. Marker movements were calculated and compared between markers. The bone-based and marker-based scapulothoracic rotation angles were also compared in both positions. The median marker movement distances were 30.4 mm for the acromial angle, 53.1 mm for the root of the scapular spine, and 70.0 mm for the inferior angle. Marker movements were significantly smaller on the superolateral aspect of the scapula, and superior movement was largest in the directional movement. Scapulothoracic rotation angles were significantly smaller in the marker-based rotation angles than in the bone-based rotation angles of the elevated position. We noted that the markers especially did not track the inferior movement of the scapular motion with shoulder elevation, resulting in an underestimation of the marker-based rotation angles.

Accuracy of a markerless motion capture system in estimating upper extremity kinematics during boxing

Kinematic analysis of the upper extremity can be useful to assess the performance and skill levels of athletes during combat sports such as boxing. Although marker-based approach is widely used to obtain kinematic data, it is not suitable for “in the field” activities, i.e., when performed outside the laboratory environment. Markerless video-based systems along with deep learning-based pose estimation algorithms show great potential for estimating skeletal kinematics. However, applicability of these systems in assessing upper-limb kinematics remains unexplored in highly dynamic activities. This study aimed to assess kinematics of the upper limb estimated with a markerless motion capture system (2D video cameras along with commercially available pose estimation software Theia3D) compared to those measured with marker-based system during “in the field” boxing. A total of three elite boxers equipped with retroreflective markers were instructed to perform specific sequences of shadow boxing trials. Their movements were simultaneously recorded with 12 optoelectronic and 10 video cameras, providing synchronized data to be processed further for comparison. Comparative assessment showed higher differences in 3D joint center positions at the elbow (more than 3 cm) compared to the shoulder and wrist (&lt;2.5 cm). In the case of joint angles, relatively weaker agreement was observed along internal/external rotation. The shoulder joint revealed better performance across all the joints. Segment velocities displayed good-to-excellent agreement across all the segments. Overall, segment velocities exhibited better performance compared to joint angles. The findings indicate that, given the practicality of markerless motion capture system, it can be a promising alternative to analyze sports-performance.

A penalty method for constrained multibody kinematics optimisation using a Levenberg-Marquardt algorithm

An alternative method for solving constrained multibody kinematics optimisation using a penalty method on constraints and a Levenberg-Marquardt algorithm is proposed. It is compared to an optimisation resolution with hard kinematic constraints. These methods are applied to two pairs of experiments and models. The penalty method was at least 20 times faster than the optimisation resolution while keeping similar reconstruction errors and constraints violation. The potential of the method is shown to accurately solve the multibody kinematics optimisation problem in a reasonable amount of time. A computational gain lies in implementing this resolution with a compiled and optimised program code.

An ISB-consistent Denavit-Hartenberg model of the human upper limb for joint kinematics optimization: validation on synthetic and robot data during a typical rehabilitation gesture

Several biomedical contexts such as diagnosis, rehabilitation, and ergonomics require an accurate estimate of human upper limbs kinematics. Wearable inertial measurement units (IMU s) represent a suitable solution because of their unobtrusiveness, portability, and low-cost. However, the time-integration of the gyroscope angular velocity leads to an unbounded orientation drift affecting both angular and linear displacements over long observation interval. In this work, a Denavit-Hartenberg model of the upper limb was defined in accordance with the guidelines of the International Society of Biomechanics and exploited to design an optimization kinematics process. This procedure estimated the joint angles by minimizing the difference between the modelled and IMU-driven orientation of upper arm and forearm. In addition, reasonable constraints were added to limit the drift influence on the final joint kinematics accuracy. The validity of the procedure was tested on synthetic and experimental data acquired with a robotic arm over 20 minutes. Average rms errors amounted to 2.8 deg and 1.1 for synthetic and robot data, respectively. Clinical Relevance - The proposed method has the potential to improve robustness and accuracy of multi-joint kinematics estimation in the general contexts of home-based tele-rehabilitation interventions. In this respect adoption of multi-segmental kinematic model along with physiological joint constraints could contribute to address current limitations associated to unsupervised analysis in terms of monitoring and outcome assessment.

Reliability Study of Inertial Sensors LIS2DH12 Compared to ActiGraph GT9X: Based on Free Code

The study’s purpose was to assess the reliability of the LIS2DH12 in two different positions, using the commercial sensor Actigraph GT9X as a reference instrument. Five participants completed two gait tests on a treadmill. Firstly, both sensors were worn on the wrist and around the thigh. Each test consisted of a 1 min walk for participants to become accustomed to the treadmill, followed by a 2 min trial at ten pre-set speeds. Data from both sensors were collected in real-time. Intraclass correlation coefficient (ICC) was used to evaluate the equality of characteristics obtained by both sensors: maximum peaks, minimum peaks, and the mean of the complete signal (sequence of acceleration values along the time) by each axis and speed were extracted to evaluate the equality of characteristics obtained with LIS2DH12 compared to Actigraph. Intraclass correlation coefficient (ICC) was extracted, and a standard deviation of the mean was obtained from the data. Our results show that LIS2DH12 measurements present more reliability than Actigraph GT9X, ICC > 0.8 at three axes. This study concludes that LIS2DH12 is as reliable and accurate as Actigraph GT9X Link and, therefore, would be a suitable tool for future kinematic studies.

Subject-specific model-derived kinematics of the shoulder based on skin markers during arm abduction up to 180° - assessment of 4 gleno-humeral joint models

Accuracy of shoulder kinematics predicted by multi-body kinematics optimisation depend on the joint models used. This study assesses the influence of four different subject-specific gleno-humeral joint models within multi-body kinematics optimisation: a 6-degree-of-freedom joint (i.e. single-body kinematics optimisation), a sphere-on-sphere joint (with two spheres of different radii) and a spherical joint with or without penalised translation. To drive these models, the 3D coordinates of 12 skin markers of 6 subjects performing static arm abduction poses up to 180° were used. The reference data was obtained using biplane X-rays from which 3D bone reconstructions were generated: scapula and humerus were 3D reconstructed by fitting a template model made of geometrical primitives on the two bones' X-rays. Without any motion capture system, the recording of the skin markers was performed at the very same time than the X-rays with radiopaque markers. The gleno-humeral displacements and angles, and scapula-thoracic angles were computed. The gleno-humeral sphere-on-sphere joint provided slightly better results than the spherical joint with or without penalised translation, but considerably better gleno-humeral displacements than the 6-DoF joint. Considering that it can easily be personalised from medical images, this sphere-on-sphere model seems promising for shoulder multi-body kinematics optimisation.

A SWOT Analysis of Portable and Low-Cost Markerless Motion Capture Systems to Assess Lower-Limb Musculoskeletal Kinematics in Sport

Markerless motion capture systems are promising for the assessment of movement in more real world research and clinical settings. While the technology has come a long way in the last 20 years, it is important for researchers and clinicians to understand the capacities and considerations for implementing these types of systems. The current review provides a SWOT (Strengths, Weaknesses, Opportunities, and Threats) analysis related to the successful adoption of markerless motion capture technology for the assessment of lower-limb musculoskeletal kinematics in sport medicine and performance settings. 31 articles met the a priori inclusion criteria of this analysis. Findings from the analysis indicate that the improving accuracy of these systems via the refinement of machine learning algorithms, combined with their cost efficacy and the enhanced ecological validity outweighs the current weaknesses and threats. Further, the analysis makes clear that there is a need for multidisciplinary collaboration between sport scientists and computer vision scientists to develop accurate clinical and research applications that are specific to sport. While work remains to be done for broad application, markerless motion capture technology is currently on a positive trajectory and the data from this analysis provide an efficient roadmap toward widespread adoption.

A Systematic Review of Diagnostic Accuracy and Clinical Applications of Wearable Movement Sensors for Knee Joint Rehabilitation

In clinical practice, only a few reliable measurement instruments are available for monitoring knee joint rehabilitation. Advances to replace motion capturing with sensor data measurement have been made in the last years. Thus, a systematic review of the literature was performed, focusing on the implementation, diagnostic accuracy, and facilitators and barriers of integrating wearable sensor technology in clinical practices based on a Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement. For critical appraisal, the COSMIN Risk of Bias tool for reliability and measurement of error was used. PUBMED, Prospero, Cochrane database, and EMBASE were searched for eligible studies. Six studies reporting reliability aspects in using wearable sensor technology at any point after knee surgery in humans were included. All studies reported excellent results with high reliability coefficients, high limits of agreement, or a few detectable errors. They used different or partly inappropriate methods for estimating reliability or missed reporting essential information. Therefore, a moderate risk of bias must be considered. Further quality criterion studies in clinical settings are needed to synthesize the evidence for providing transparent recommendations for the clinical use of wearable movement sensors in knee joint rehabilitation.

Sparse Visual-Inertial Measurement Units Placement for Gait Kinematics Assessment

This study investigates the possibility of estimating lower-limb joint kinematics and meaningful performance indexes for physiotherapists, during gait on a treadmill based on data collected from a sparse placement of new Visual Inertial Measurement Units (VIMU) and the use of an Extended Kalman Filter (EKF). The proposed EKF takes advantage of the biomechanics of the human body and of the investigated task to reduce sensor inaccuracies. Two state-vector formulations, one based on the use of constant acceleration model and one based on Fourier series, and the tuning of their corresponding parameters were analyzed. The constant acceleration model, due to its inherent inconsistency for human motion, required a cumbersome optimisation process and needed the a-priori knowledge of reference joint trajectories for EKF parameters tuning. On the other hand, the Fourier series formulation could be used without a specific parameters tuning process. In both cases, the average root mean square difference and correlation coefficient between the estimated joint angles and those reconstructed with a reference stereophotogrammetric system was 3.5deg and 0.70, respectively. Moreover, the stride lengths were estimated with a normalized root mean square difference inferior to 2% when using the forward kinematics model receiving as input the estimated joint angles. The popular gait deviation index was also estimated and showed similar results very close to 100, using both the proposed method and the reference stereophotogrammetric system. Such consistency was obtained using only three wireless and affordable VIMU located at the pelvis and both heels and tracked using two affordable RGB cameras. Being further easy-to-use and suitable for applications taking place outside of the laboratory, the proposed method thus represents a good compromise between accurate reference stereophotogrammetric systems and markerless ones for which accuracy is still under debate.

Statistical-Shape Prediction of Lower Limb Kinematics During Cycling, Squatting, Lunging, and Stepping-Are Bone Geometry Predictors Helpful?

Purpose: Statistical shape methods have proven to be useful tools in providing statistical predications of several clinical and biomechanical features as to analyze and describe the possible link with them. In the present study, we aimed to explore and quantify the relationship between biometric features derived from imaging data and model-derived kinematics. Methods: Fifty-seven healthy males were gathered under strict exclusion criteria to ensure a sample representative of normal physiological conditions. MRI-based bone geometry was established and subject-specific musculoskeletal simulations in the Anybody Modeling System enabled us to derive personalized kinematics. Kinematic and shape findings were parameterized using principal component analysis. Partial least squares regression and canonical correlation analysis were then performed with the goal of predicting motion and exploring the possible association, respectively, with the given bone geometry. The relationship of hip flexion, abduction, and rotation, knee flexion, and ankle flexion with a subset of biometric features (age, length, and weight) was also investigated. Results: In the statistical kinematic models, mean accuracy errors ranged from 1.60° (race cycling) up to 3.10° (lunge). When imposing averaged kinematic waveforms, the reconstruction errors varied between 4.59° (step up) and 6.61° (lunge). A weak, yet clinical irrelevant, correlation between the modes describing bone geometry and kinematics was observed. Partial least square regression led to a minimal error reduction up to 0.42° compared to imposing gender-specific reference curves. The relationship between motion and the subject characteristics was even less pronounced with an error reduction up to 0.21°. Conclusion: The contribution of bone shape to model-derived joint kinematics appears to be relatively small and lack in clinical relevance.

Simultaneous identification of human body model parameters and gait trajectory from 3D motion capture data

The analysis of human movements rests on a realistic human body model. Deducing model parameters from anthropomorphic data is challenging since these are inherently imprecise. An approach to improve model accuracy is the parameter adaptation based on motion data. 3D motion capture data are already being used for generating the trajectories of a human body model, so combining motion tracking and parameter identification seems most natural. This paper introduces a holistic approach to simultaneously identify the geometric parameters of a kinematic human lower limb model and the parameters defining a (cyclic) gait trajectory, based on 3D marker positions. The result is a time-continuous description of a physiologically compatible lower extremity movement along with optimal model parameters so to best reproduce the captured motion. The method takes into account restrictions such as the range of motion of human body joints and is robust against missing data due to marker occlusions or failures of the measurement system. Considering multiple gait cycles of a movement trial, we derive the characteristic motion pattern (CMP) of a specific subject walking at a specific speed. Our method further allows for motion analysis and assessment, but also for motion synthesis with arbitrary time span and time resolution and can thus be used for simulations and trajectory planning of rehabilitation and movement assistance systems, such as exoskeletons.

Development and Evaluation of a Subject-Specific Lower Limb Model With an Eleven-Degrees-of-Freedom Natural Knee Model Using Magnetic Resonance and Biplanar X-Ray Imaging During a Quasi-Static Lunge

Musculoskeletal (MS) models can be used to study the muscle, ligament, and joint mechanics of natural knees. However, models that both capture subject-specific geometry and contain a detailed joint model do not currently exist. This study aims to first develop magnetic resonance image (MRI)-based subject-specific models with a detailed natural knee joint capable of simultaneously estimating in vivo ligament, muscle, tibiofemoral (TF), and patellofemoral (PF) joint contact forces and secondary joint kinematics. Then, to evaluate the models, the predicted secondary joint kinematics were compared to in vivo joint kinematics extracted from biplanar X-ray images (acquired using slot scanning technology) during a quasi-static lunge. To construct the models, bone, ligament, and cartilage structures were segmented from MRI scans of four subjects. The models were then used to simulate lunges based on motion capture and force place data. Accurate estimates of TF secondary joint kinematics and PF translations were found: translations were predicted with a mean difference (MD) and standard error (SE) of 2.13 ± 0.22 mm between all trials and measures, while rotations had a MD ± SE of 8.57 ± 0.63 deg. Ligament and contact forces were also reported. The presented modeling workflow and the resulting knee joint model have potential to aid in the understanding of subject-specific biomechanics and simulating the effects of surgical treatment and/or external devices on functional knee mechanics on an individual level.

Physically Consistent Whole-Body Kinematics Assessment Based on an RGB-D Sensor. Application to Simple Rehabilitation Exercises

This work proposes to improve the accuracy of joint angle estimates obtained from an RGB-D sensor. It is based on a constrained extended Kalman Filter that tracks inputted measured joint centers. Since the proposed approach uses a biomechanical model, it allows physically consistent constrained joint angles and constant segment lengths to be obtained. A practical method that is not sensor-specific for the optimal tuning of the extended Kalman filter covariance matrices is provided. It uses reference data obtained from a stereophotogrammetric system but it has to be tuned only once since it is task-specific only. The improvement of the optimal tuning over classical methods in setting the covariance matrices is shown with a statistical parametric mapping analysis. The proposed approach was tested with six healthy subjects who performed four rehabilitation tasks. The accuracy of joint angle estimates was assessed with a reference stereophotogrammetric system. Even if some joint angles, such as the internal/external rotations, were not well estimated, the proposed optimized algorithm reached a satisfactory average root mean square difference of 9.7∘ and a correlation coefficient of 0.8 for all joints. Our results show that an affordable RGB-D sensor can be used for simple in-home rehabilitation when using a constrained biomechanical model.

ISB recommendations on the reporting of intersegmental forces and moments during human motion analysis

The International Society of Biomechanics (ISB) has charged this committee with development of a standard similar in scope to the kinematic standard proposed in Wu et al. (2002) and Wu et al. (2005). Given the variety of purposes for which intersegmental forces and moments are used in biomechanical research, it is not possible to recommend a particular set of analysis standards that will be acceptable in all applications. Instead, it is the purpose of this paper to recommend a set of reporting standards that will result in an understanding of the differences between investigations and the ability to reproduce the research. The end products of this standard are (1) a critical checklist that can be used during submission of manuscripts and abstracts to insure adequate description of methods, and (2) a web based visualization tool that can be used to alter the coordinate system, normalization technique and internal/external perspective of intersegmental forces and moments during walking and running so that the shape and magnitude of the curves can be compared to one's own data.

Age-related differences of inter-joint coordination in elderly during squat jumping

Background

Explosive movement requires that the individual exerts force and power with appropriate magnitude and timing. These coordination aspects have received less attention despite being a basic prerequisite for daily mobility and physical autonomy, especially in older people. Therefore, the purpose of this study is to characterize the effect of age on inter-joint coordination during explosive movement.

Methods

Twenty-one elderly and twenty young participants performed three maximal vertical jumps, while kinematics were recorded throughout each squat jump. Inter-joint coordination and coordination variability were calculated for selected sagittal hip-knee, knee-ankle, and hip-ankle joint couplings using the continuous relative phase method.

Results

The young participants produced significantly greater jump height performance (0.36 ± 0.07 m vs. 0.12 ± 0.04 m, p < 0.001). The mean absolute continuous relative phase for ankle-knee and knee-hip joint couplings were significantly greater for the elderly in comparison to the young group (p < 0.01 for the both). No significant differences between senior and young participants in the mean absolute continuous relative phase for ankle-hip joint couplings (p = 0.25) was observed. However, there was significantly more variability in inter-joint coordination in the elderly marked by greater continuous relative phase variabilities in ankle-knee, ankle-hip and knee-hip joint couplings (p < 0.001) than those observed in young adults.

Conclusion

In this study, seniors demonstrated proximodistal inter-joint coordination but with different delays in the pattern of inter-joint coordination during squat jumps compared to young adults. In addition, a higher continuous relative phase variability in the elderly may be needed to improve stability or compensate for strength deficits in jump achievement.

IMU-based sensor-to-segment multiple calibration for upper limb joint angle measurement-a proof of concept

A lot of attention has been paid to wearable inertial sensors regarded as an alternative solution for outdoor human motion tracking. Relevant joint angles can only be calculated from anatomical orientations, but they are negatively impacted by soft tissue artifact (STA) defined as skin motion with respect to the underlying bone; the accuracy of measured joint angle during movement is affected by the ongoing misalignment of the sensor. In this work, a new sensor-to-segment calibration using inertial measurement units is proposed. Inspired by the multiple calibration for a cluster of skin markers, it consists in performing first multiple static postures of the upper limb in all anatomical planes. The movements that affect sensor alignment are identified then alignment differences between sensors and segment frames are calculated for each posture and linearly interpolated. Experimental measurements were carried out on a mechanical model and on a subject who performed different movements of right elbow and shoulder. Multiple calibration showed significant improvement in joint angle measurement on the mechanical model as well as on human joint angle comparing to those obtained from attached sensors after technical calibration. During shoulder internal-external rotation, the maximal error value decreased more than 50% after correction. Graphical abstract Elbow flexion-extension joint angle values obtained from IMUs are well-corrected after applying multiple calibration procedure. Though shoulder internal-external rotation joint angle is more affected by soft tissue artifact, multiple calibration procedure improves the angle values obtained from IMUs.

Correcting lower limb segment axis misalignment in gait analysis: A simple geometrical method

BACKGROUND

Obtaining precise and repeatable measurements is essential to clinical gait analysis. However, defining the thigh medial-lateral axis segment remains a challenge, with particular implications for the hip rotation profile. Thigh medial-lateral axis misalignment modifies the hip rotation profile and can result in a phenomenon called crosstalk, which increases knee adduction-abduction amplitude artificially.

RESEARCH QUESTION

This study proposes an a posteriori geometrical method based solely on segment anatomy that aims to correct the thigh medial-lateral axis definition and crosstalk-related error.

METHODS

The proposed method considers the thigh medial-lateral axis as the normal to the mean sagittal plane of the lower limb defined by hip, knee and ankle joint centres during one gait cycle. Its performance was compared to that of an optimisation method which repositions the axis to reduce knee abduction-adduction variance. An existing dataset was used: 75 patients with a knee prosthesis undergoing gait analysis three months and one-year post-surgery. Three-dimensional hip and knee angles were computed for two gait analysis sessions. Crosstalk was quantified using both the coefficient of determination (r²) between knee flexion-extension and adduction-abduction and the amplitude of knee adduction-abduction. The reproducibility of hip internal-external rotation was also quantified using the inter-trial, inter-session and inter-subject standard deviations and the intraclass coefficient (ICC).

RESULTS

Crosstalk was significantly reduced from r² = 0.67 to r² = 0.51 by the geometrical method but remained significantly higher than with the optimisation method with a r² < 0.01.

SIGNIFICANCES

Both methods allowed to improve the hip internal-external reproducibility from poor to moderate (original data: ICC = 0.34, geometrical method: ICC = 0.65, optimisation method ICC = 0.73). One advantage of the geometrical method is that, unlike the optimisation method, it does not require much movement, making it suitable for a wider range of patients.

A screening method to analyse the sensitivity of a lower limb multibody kinematic model

The study presents a screening method used to identify the influential parameters of a lower limb model including ligaments, at low numerical cost. Concerning multibody kinematics optimisation, the ligament parameters (isometric length) were found the most influential ones in a previous study. The screening method tested if they remain influential with minimised length variations. The most important parameters for tibiofemoral kinematics were the skin markers, segment lengths and joint parameters, including two ligaments. This was confirmed by a quantitative sensitivity analysis. The screening method has the potential to be used as a stand-alone procedure for a sensitivity analysis.

On the influence of the shoulder kinematic chain on joint kinematics and musculotendon lengths during wheelchair propulsion estimated from multibody kinematics optimization

Multibody kinematic optimization is frequently used to assess shoulder kinematics during manual wheelchair (MWC) propulsion but multiple kinematics chains are available. It is hypothesized that these different kinematic chains affect marker tracking, shoulder kinematics and resulting musculotendon (MT) lengths. In this study, shoulder kinematics and MT lengths obtained from four shoulder kinematic chains (open-loop thorax-clavicle-scapula-humerus (M1), closed-loop with contact ellipsoid (M2), scapula rhythm from regression equations (M3), and a single ball-and- socket joint between the thorax and the humerus (M4) were compared. Right-side shoulder kinematics from seven subjects were obtained with 34 reflective markers and a scapula locator using an optoelectronic motion capture system while propelling on a MWC simulator. Data was processed based on the four models. Results showed the impact of shoulder kinematic chains on all studied variables. Marker reconstruction errors were found similar between M1 and M2 and lower than for M3 and M4. Few degrees of freedom (DoF) were noticeably different between M1 and M2, but all shoulder DoFs were significantly affected between M1 and M4. As a consequence of differences in joint kinematics, MT lengths were affected by the kinematic chain definition. The contact ellipsoid (M2) was found as a good trade-off between marker tracking and penetration avoidance of the scapula. The regression-based model (M3) was less efficient due to limited humerus elevation during MWC propulsion, as well as the ball-and-socket model (M4) which appeared not suitable for upper limbs activities, including MWC propulsion.