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

Tibiofemoral Slip Velocity in Total Knee Arthroplasty is Design-Invariant but Activity-Dependent

Tibiofemoral slip velocity is a key contributor to total knee arthroplasty (TKA) component wear, yet few studies have evaluated this quantity in vivo. The aim of the present study was to measure and compare tibiofemoral slip velocities in 3 TKA designs for a range of daily activities. Mobile biplane X-ray imaging was used to measure 6-degree-of-freedom tibiofemoral kinematics and the locations of articular contact in 75 patients implanted with a posterior-stabilized, cruciate-retaining, or medial-stabilized design while each patient performed level walking, step up, step down, sit-to-stand, and stand-to-sit. Using these data, tibiofemoral slip velocity was calculated for the duration of each activity for each TKA design. The pattern of tibiofemoral slip velocity was similar for all 3 TKA designs within each activity but markedly different across the 5 activities tested, with the magnitude of peak slip velocity being significantly higher in level walking (range: 158-211 mm/s) than in all other activities (range: 43-75 mm/s). The pattern of tibiofemoral slip velocity in both the medial and lateral compartments closely resembled the pattern of tibiofemoral (knee) flexion angular velocity, with a strong linear relationship observed between slip velocity and flexion angular velocity (r = 0.81-0.97). Tibiofemoral slip velocity was invariant to TKA design but was significantly affected by activity type. Our measurements of slip velocity and articular contact locations for a wide range of daily activities may be used as inputs in joint simulator testing protocols and computational models developed to estimate TKA component wear.

Vertical Center-of-Mass Braking and Motor Performance during Gait Initiation in Young Healthy Adults, Elderly Healthy Adults, and Patients with Parkinson's Disease: A Comparison of Force-Plate and Markerless Motion Capture Systems

BACKGROUND

This study tested the agreement between a markerless motion capture system and force-plate system ("gold standard") to quantify stability control and motor performance during gait initiation.

METHODS

Healthy adults (young and elderly) and patients with Parkinson's disease performed gait initiation series at spontaneous and maximal velocity on a system of two force-plates placed in series while being filmed by a markerless motion capture system. Signals from both systems were used to compute the peak of forward center-of-mass velocity (indicator of motor performance) and the braking index (indicator of stability control).

RESULTS

Descriptive statistics indicated that both systems detected between-group differences and velocity effects similarly, while a Bland-Altman plot analysis showed that mean biases of both biomechanical indicators were virtually zero in all groups and conditions. Bayes factor 01 indicated strong (braking index) and moderate (motor performance) evidence that both systems provided equivalent values. However, a trial-by-trial analysis of Bland-Altman plots revealed the possibility of differences >10% between the two systems.

CONCLUSION

Although non-negligible differences do occur, a markerless motion capture system appears to be as efficient as a force-plate system in detecting Parkinson's disease and velocity condition effects on the braking index and motor performance.

Reliability of Xsens IMU-Based Lower Extremity Joint Angles during In-Field Running

The Xsens Link motion capture suit has become a popular tool in investigating 3D running kinematics based on wearable inertial measurement units outside of the laboratory. In this study, we investigated the reliability of Xsens-based lower extremity joint angles during unconstrained running on stable (asphalt) and unstable (woodchip) surfaces within and between five different testing days in a group of 17 recreational runners (8 female, 9 male). Specifically, we determined the within-day and between-day intraclass correlation coefficients (ICCs) and minimal detectable changes (MDCs) with respect to discrete ankle, knee, and hip joint angles. When comparing runs within the same day, the investigated Xsens-based joint angles generally showed good to excellent reliability (median ICCs > 0.9). Between-day reliability was generally lower than the within-day estimates: Initial hip, knee, and ankle angles in the sagittal plane showed good reliability (median ICCs > 0.88), while ankle and hip angles in the frontal plane showed only poor to moderate reliability (median ICCs 0.38-0.83). The results were largely unaffected by the surface. In conclusion, within-day adaptations in lower-extremity running kinematics can be captured with the Xsens Link system. Our data on between-day reliability suggest caution when trying to capture longitudinal adaptations, specifically for ankle and hip joint angles in the frontal plane.

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.

On the accuracy of the Conventional gait Model: Distinction between marker misplacement and soft tissue artefact errors

There is a lack of knowledge about the accuracy of the Conventional Gait Model (CGM), compared to the true bone motion. Accuracy is hindered by both marker misplacement and soft-tissue artefact (STA). The effect of the lateral knee marker (KNE) misplacement and STA was determined from a secondary analysis of 13 subjects equipped with a total knee prothesis for which simultaneous dual-plane fluoroscopy and marker-based motion capture was available. In average, STA alone led to 3.3°, 2.9° and 6.7° errors for knee flexion, knee abduction, and the absolute hip rotation respectively. In comparison, marker misplacement led to 0.9°, 4.0° and 12.3° errors for the same kinematics. We showed that STA alone may lead to knee flexion-adduction cross-talk. This finding has clinical repercussions for the use of knee cross talk as a qualitative indicator of knee axis alignment. Our study showed that cumulative effects of marker misplacement and STA affect the transverse plane angles, making challenging to track internal/external rotation with less than 5° of errors.

Machine Learning for Optical Motion Capture-Driven Musculoskeletal Modelling from Inertial Motion Capture Data

Marker-based Optical Motion Capture (OMC) systems and associated musculoskeletal (MSK) modelling predictions offer non-invasively obtainable insights into muscle and joint loading at an in vivo level, aiding clinical decision-making. However, an OMC system is lab-based, expensive, and requires a line of sight. Inertial Motion Capture (IMC) techniques are widely-used alternatives, which are portable, user-friendly, and relatively low-cost, although with lesser accuracy. Irrespective of the choice of motion capture technique, one typically uses an MSK model to obtain the kinematic and kinetic outputs, which is a computationally expensive tool increasingly well approximated by machine learning (ML) methods. Here, an ML approach is presented that maps experimentally recorded IMC input data to the human upper-extremity MSK model outputs computed from ('gold standard') OMC input data. Essentially, this proof-of-concept study aims to predict higher-quality MSK outputs from the much easier-to-obtain IMC data. We use OMC and IMC data simultaneously collected for the same subjects to train different ML architectures that predict OMC-driven MSK outputs from IMC measurements. In particular, we employed various neural network (NN) architectures, such as Feed-Forward Neural Networks (FFNNs) and Recurrent Neural Networks (RNNs) (vanilla, Long Short-Term Memory, and Gated Recurrent Unit) and a comprehensive search for the best-fit model in the hyperparameters space in both subject-exposed (SE) as well as subject-naive (SN) settings. We observed a comparable performance for both FFNN and RNN models, which have a high degree of agreement (ravg,SE,FFNN=0.90±0.19, ravg,SE,RNN=0.89±0.17, ravg,SN,FFNN=0.84±0.23, and ravg,SN,RNN=0.78±0.23) with the desired OMC-driven MSK estimates for held-out test data. The findings demonstrate that mapping IMC inputs to OMC-driven MSK outputs using ML models could be instrumental in transitioning MSK modelling from 'lab to field'.

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.

Effects of soft tissue artifacts on the calculated kinematics of the knee during walking and running

Kinematics of the knee during gait has mostly been studied using optical motion capture systems (MCS). The presence of soft tissue artifacts (STA) between the skin markers and the underlying bone presents a major impediment to obtaining a reliable joint kinematics assessment. In this study, we determined the effects of STA on the calculation of knee joint kinematics during walking and running, through the combination of high-speed dual fluoroscopic imaging system (DFIS) and magnetic resonance imaging technique. Ten adults walked and ran while data was collected simultaneously from MCS and high-speed DFIS. The study showed that measured STA underestimated knee flexion angle, but overestimated knee external and varus rotation. The absolute error values of the skin markers derived from knee flexion-extension angle, internal-external rotation, and varus-valgus rotation during walking were -3.2 ± 4.3 deg, 4.6 ± 3.1 deg, and 4.5 ± 3.2 deg respectively, and during running were -5.8 ± 5.4 deg, 6.6 ± 3.7 deg, and 4.8 ± 2.5 deg respectively. Average errors relative to the DFIS for flexion-extension angle, internal-external rotation, and varus-valgus rotation were 78 %, 271 %, 265 % during walking respectively, and were 43 %, 106 %, 200 % during running respectively. This study offers reference for the kinematic differences between MCS and high-speed DFIS, and will contribute to optimizing methods for analyzing knee kinematics during walking and running.

Study of Windlass Mechanism in the Lower Limb Using Inertial Sensors

AIMS

This study aimed to quantify the degrees of movement that occur in the lower limb using a kinematic system after taking two measurements of 45° and 60° of extension at the first metatarsophalangeal joint (1st MTPJ) and to test the validity of this sensor system using radiography.

METHODOLOGY

This was a quasi-experimental test-post-test study with a single intervention group (25 subjects). Four inertial sensors were placed on the proximal phalange of the first toe, dorsum of the foot, medial-lateral of the leg (level of tibia), and medial-lateral of the thigh (level of femur). The extension of the 1st MTPJ produced movements of supination in the foot and rotation at the level of leg and thigh. We studied this mechanism in three situations (relaxed, 45°, and 60°) both with the sensors and with X-rays.

RESULTS

With the kinematic system, there was an increase in the range of movement in each of the variables, with a value of p < 0.05. The relationship between the kinematic system and the radiography was tested using Spearman's rho test, obtaining a correlation coefficient of 0.624 and a value of p < 0.05, and the Bland-Altman graph, with 90% of the cases within the tolerance limits.

CONCLUSIONS

The extension of the 1st MTPJ generated kinematic changes associated with supination movement in the midfoot and external rotation on the tibia and femur level. Both measurement techniques were very similar in the way that they quantified the degrees of extension of the 1st MTPJ. If we extrapolate this result to the measurement technique used by the inertial sensors, we could affirm that the values recorded in the supination and external rotation movements were reliable.

Mobility recorded by wearable devices and gold standards: the Mobilise-D procedure for data standardization

Wearable devices are used in movement analysis and physical activity research to extract clinically relevant information about an individual's mobility. Still, heterogeneity in protocols, sensor characteristics, data formats, and gold standards represent a barrier for data sharing, reproducibility, and external validation. In this study, we aim at providing an example of how movement data (from the real-world and the laboratory) recorded from different wearables and gold standard technologies can be organized, integrated, and stored. We leveraged on our experience from a large multi-centric study (Mobilise-D) to provide guidelines that can prove useful to access, understand, and re-use the data that will be made available from the study. These guidelines highlight the encountered challenges and the adopted solutions with the final aim of supporting standardization and integration of data in other studies and, in turn, to increase and facilitate comparison of data recorded in the scientific community. We also provide samples of standardized data, so that both the structure of the data and the procedure can be easily understood and reproduced.

Quantification of Error Sources with Inertial Measurement Units in Sports

BACKGROUND

Inertial measurement units (IMUs) offer the possibility to capture the lower body motions of players of outdoor team sports. However, various sources of error are present when using IMUs: the definition of the body frames, the soft tissue artefact (STA) and the orientation filter. Methods to minimize these errors are currently being used without knowing their exact influence on the various sources of errors. The goal of this study was to present a method to quantify each of the sources of error of an IMU separately.

METHODS

An optoelectronic system was used as a gold standard. Rigid marker clusters (RMCs) were designed to construct a rigid connection between the IMU and four markers. This allowed for the separate quantification of each of the sources of error. Ten subjects performed nine different football-specific movements, varying both in the type of movement, and in movement intensity.

RESULTS

The error of the definition of the body frames (11.3-18.7 deg RMSD), the STA (3.8-9.1 deg RMSD) and the error of the orientation filter (3.0-12.7 deg RMSD) were all quantified separately for each body segment.

CONCLUSIONS

The error sources of IMU-based motion analysis were quantified separately. This allows future studies to quantify and optimize the effects of error reduction techniques.

Novel Method for Estimating Propulsive Force Generated by Swimmers' Hands Using Inertial Measurement Units and Pressure Sensors

Propulsive force is a determinant of swimming performance. Several methods have been proposed to estimate the propulsive force in human swimming; however, their practical use in coaching is limited. Herein, we propose a novel method for estimating the propulsive force generated by swimmers' hands using an inertial measurement unit (IMU) and pressure sensors. In Experiment 1, we use a hand model to examine the effect of a hand-mounted IMU on pressure around the hand model at several flow velocities and water flow directions. In Experiment 2, we compare the propulsive force estimated using the IMU and pressure sensors (FIMU) via an underwater motion-capture system and pressure sensors (FMocap). Five swimmers had markers, pressure sensors, and IMUs attached to their hands and performed front crawl swimming for 25 m twice at each of nine different swimming speeds. The results show that the hand-mounted IMU affects the resultant force; however, the effect of the hand-mounted IMU varies with the flow direction. The mean values of FMocap and FIMU are similar (19.59 ± 7.66 N and 19.36 ± 7.86 N, respectively; intraclass correlation coefficient_(2,1) = 0.966), and their waveforms are similar (coefficient of multiple correlation = 0.99). These results indicate that the IMU can estimate the same level of propulsive force as an underwater motion-capture system.

Accuracy of a 3D temporal scanning system for gait analysis: Comparative with a marker-based photogrammetry system

BACKGROUND

Combining the accuracy of marker-based stereophotogrammetry and the usability and comfort of markerless human movement analysis is a difficult challenge. 3D temporal scanners are a promising solution, since they provide moving meshes with thousands of vertices that can be used to analyze human movements.

RESEARCH QUESTION

Can a 3D temporal scanner be used as a markerless system for gait analysis with the same accuracy as traditional, marker-based stereophotogrammetry systems?

METHODS

A comparative study was carried out using a 3D temporal scanner synchronized with a marker-based stereophotogrammetry system. Two gait cycles of twelve healthy adults were measured simultaneously, extracting the positions of key anatomical points from both systems, and using them to analyze the 3D kinematics of the pelvis, right hip and knee joints. Measurement differences of marker positions and joint angles were described by their root mean square. A t-test was performed to rule out instrumental errors, and an F-test to evaluate the amplifications of marker position errors in dynamic conditions.

RESULTS

The differences in 3D landmark positions were between 1.9 and 2.4 mm in the reference pose. Marker position errors were significantly increased during motion in the medial-lateral and vertical directions. The angle relative errors were between 3% and 43% of the range of motion, with the greatest difference being observed in hip axial rotation.

SIGNIFICANCE

The differences in the results obtained between the 3D temporal scanner and the marker-based system were smaller than the usual errors due to lack of accuracy in the manual positioning of markers on anatomical landmarks and to soft-tissue artefacts. That level of accuracy is greater than other markerless systems, and proves that such technology is a good alternative to traditional, marker-based motion capture.

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.

Lumbar segment-dependent soft tissue artifacts of skin markers during in vivo weight-bearing forward–Backward bending

Traditional optical motion capture (OMC) with retroreflective markers is commonly used to measure joint kinematics but was also reported with unavoidable soft tissue artifacts (STAs) when quantifying the motion of the spine. Additionally, the patterns of the STA on the lumbar spine remain unclear. This study aimed to 1) quantify the in vivo STAs of the human lower back in three-dimensional directions during weight-bearing forward–backward bending and 2) determine the effects of the STAs on the calculated flexion angles between the upper and lower lumbar spines and adjacent vertebrae by comparing the skin marker (SM)- and virtual bone marker (VM)-based measurements. Six healthy volunteers were imaged using a biplanar radiographic system, and thirteen skin markers were mounted on every volunteer’s lower back while performing weight-bearing forward–backward bending. The STAs in the anterior/posterior (AP), medial/lateral (ML), and proximal/distal (PD) directions were investigated. The flexion angles between the upper and lower lumbar segments and adjacent intervertebral segments (L2–L5) throughout the cycle were calculated. For all the participants, STAs continuously increased in the AP direction and exhibited a reciprocal trend in the PD direction. During flexion, the STA at the lower lumbar region (L4–L5: 13.5 ± 6.5 mm) was significantly higher than that at the upper lumbar (L1–L3: 4.0 ± 1.5 mm) in the PD direction (p < 0.01). During extension, the lower lumbar (L4–L5: 2.7 ± 0.7 mm) exhibited significantly less STAs than that exhibited by the upper lumbar region (L1–L3: 6.1 ± 3.3 mm) (p < 0.05). The STA at the spinous process was significantly lower than that on both sides in the AP direction (p < 0.05). The present results on STAs, based on dual fluoroscopic measurements in healthy adult subjects, presented an anatomical direction, marker location, and anatomic segment dependency, which might help describe and quantify STAs for the lumbar spine kinematics and thus help develop location- and direction-specific weighting factors for use in global optimization algorithms aimed at minimizing the effects of STAs on the calculation of lumbar joint kinematics in the future.

Automatic Swimming Activity Recognition and Lap Time Assessment Based on a Single IMU: A Deep Learning Approach

This study presents a deep learning model devoted to the analysis of swimming using a single Inertial Measurement Unit (IMU) attached to the sacrum. Gyroscope and accelerometer data were collected from 35 swimmers with various expertise levels during a protocol including the four swimming techniques. The proposed methodology took high inter- and intra-swimmer variability into account and was set up for the purpose of predicting eight swimming classes (the four swimming techniques, rest, wallpush, underwater, and turns) at four swimming velocities ranging from low to maximal. The overall F1-score of classification reached 0.96 with a temporal precision of 0.02 s. Lap times were directly computed from the classifier thanks to a high temporal precision and validated against a video gold standard. The mean absolute percentage error (MAPE) for this model against the video was 1.15%, 1%, and 4.07%, respectively, for starting lap times, middle lap times, and ending lap times. This model is a first step toward a powerful training assistant able to analyze swimmers with various levels of expertise in the context of in situ training monitoring.

[Evaluation of a Bone Coordinate System Constructed Using MR Image Composing]

PURPOSE

To evaluate the accuracy of a bone coordinate system constructed using MR image composing.

METHOD

A femoral coordinate system constructed using image composing of MR images of a whole bovine femur was evaluated using CT images. The MR images were acquired by moving the table and were processed with 3D distortion correction and composing. To evaluate the reproducibility of the measurements, the same operator repeated the construction of the femoral coordinate system. In addition, distortions in the MR images were evaluated in comparison with those in the CT images.

RESULT

The center position of the femoral coordinate system constructed using the MR image composing was 1.6±0.9 mm on the X-axis, 1.5±0.8 mm on the Y-axis, and 0.2±0.3 mm on the Z-axis, and the rotation of each axis was 1° or less. The distortion of the composed MR image was about 0.3%.

CONCLUSION

The femoral coordinate system constructed using MR image composing had the same accuracy as a system constructed with CT images. The effect of MR image composing on the construction of the femoral coordinate system was small.

Clothing condition does not affect meaningful clinical interpretation in markerless motion capture

Markerless motion capture allows whole-body movements to be captured without the need for physical markers to be placed on the body. This enables motion capture analyses to be conducted in more ecologically valid environments. However, the influences of varied clothing on video-based markerless motion capture assessments remain largely unexplored. This study investigated two types of clothing conditions, "Sport" (gym shirt and shorts) and "Street" (unrestricted casual clothing), on gait parameters during overground walking by 29 participants at self-selected speeds using markerless motion capture. Segment lengths, gait spatiotemporal parameters, and lower-limb kinematics were compared between the two clothing conditions. Mean differences in segment length for the forearm, upper arm, thigh, and shank between clothing conditions ranged from 0.2 cm for the forearm to 0.9 cm for the thigh (p < 0.05 for thigh and shank) but below typical marker placement errors (1 - 2 cm). Seven out of 9 gait spatiotemporal parameters demonstrated statistically significant differences between clothing conditions (p < 0.05), however, these differences were approximately ten times smaller than minimal detectable changes in movement-related pathologies including multiple sclerosis and cerebral palsy. Hip, knee, and ankle joint angle root-mean-square deviation values averaged 2.6° and were comparable to previously reported average inter-session variability for this markerless system (2.8°). The results indicate that clothing, a potential limiting factor in markerless motion capture performance, would negligibly alter meaningful clinical interpretations under the conditions investigated.

Conclusion or Illusion: Quantifying Uncertainty in Inverse Analyses From Marker-Based Motion Capture due to Errors in Marker Registration and Model Scaling

Estimating kinematics from optical motion capture with skin-mounted markers, referred to as an inverse kinematic (IK) calculation, is the most common experimental technique in human motion analysis. Kinematics are often used to diagnose movement disorders and plan treatment strategies. In many such applications, small differences in joint angles can be clinically significant. Kinematics are also used to estimate joint powers, muscle forces, and other quantities of interest that cannot typically be measured directly. Thus, the accuracy and reproducibility of IK calculations are critical. In this work, we isolate and quantify the uncertainty in joint angles, moments, and powers due to two sources of error during IK analyses: errors in the placement of markers on the model (marker registration) and errors in the dimensions of the model’s body segments (model scaling). We demonstrate that IK solutions are best presented as a distribution of equally probable trajectories when these sources of modeling uncertainty are considered. Notably, a substantial amount of uncertainty exists in the computed kinematics and kinetics even if low marker tracking errors are achieved. For example, considering only 2 cm of marker registration uncertainty, peak ankle plantarflexion angle varied by 15.9°, peak ankle plantarflexion moment varied by 26.6 N⋅m, and peak ankle power at push off varied by 75.9 W during healthy gait. This uncertainty can directly impact the classification of patient movements and the evaluation of training or device effectiveness, such as calculations of push-off power. We provide scripts in OpenSim so that others can reproduce our results and quantify the effect of modeling uncertainty in their own studies.

The Use of Wearable Sensors for Preventing, Assessing, and Informing Recovery from Sport-Related Musculoskeletal Injuries: A Systematic Scoping Review

Wearable technologies are often indicated as tools that can enable the in-field collection of quantitative biomechanical data, unobtrusively, for extended periods of time, and with few spatial limitations. Despite many claims about their potential for impact in the area of injury prevention and management, there seems to be little attention to grounding this potential in biomechanical research linking quantities from wearables to musculoskeletal injuries, and to assessing the readiness of these biomechanical approaches for being implemented in real practice. We performed a systematic scoping review to characterise and critically analyse the state of the art of research using wearable technologies to study musculoskeletal injuries in sport from a biomechanical perspective. A total of 4952 articles were retrieved from the Web of Science, Scopus, and PubMed databases; 165 were included. Multiple study features-such as research design, scope, experimental settings, and applied context-were summarised and assessed. We also proposed an injury-research readiness classification tool to gauge the maturity of biomechanical approaches using wearables. Five main conclusions emerged from this review, which we used as a springboard to propose guidelines and good practices for future research and dissemination in the field.

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.

Assessment of Stability of MIMU Probes to Skin-Marker-Based Anatomical Reference Frames During Locomotion Tasks: Effect of Different Locations on the Lower Limb

Soft tissue artefacts (STAs) undermine the validity of skin-mounted approaches to measure skeletal kinematics. Magneto-inertial measurement units (MIMU) gained popularity due to their low cost and ease of use. Although the reliability of different protocols for marker-based joint kinematics estimation has been widely reported, there are still no indications on where to place MIMU to minimize STA. This study aims to find the most stable positions for MIMU placement, among four positions on the thigh, four on the shank, and three on the foot. Stability was investigated by measuring MIMU movements against an anatomical reference frame, defined according to a standard marker-based approach. To this aim, markers were attached both on the case of each MIMU (technical frame) and on bony landmarks (anatomical frame). For each MIMU, the nine angles between each versor of the technical frame with each versor of the corresponding anatomical frame were computed. The maximum standard deviation of these angles was assumed as the instability index of MIMU-body coupling. Six healthy subjects were asked to perform barefoot gait, step negotiation, and sit-to-stand. Results showed that (1) in the thigh, the frontal position was the most stable in all tasks, especially in gait; (2) in the shank, the proximal position is the least stable, (3) lateral or medial calcaneus and foot dorsum positions showed equivalent stability performances. Further studies should be done before generalizing these conclusions to different motor tasks and MIMU-body fixation methods. The above results are of interest for both MIMU-based gait analysis and rehabilitation approaches using wearable sensors-based biofeedback.

A method for measuring in vivo finger kinematics using electromagnetic tracking

Accurate in vivo measurement of finger joint kinematics is important for evaluation of treatment methods, implant designs, and for the development and validation of computer models of the hand. The main objective of this project was to develop a standardized finger kinematic measurement system employing electromagnetic (EM) tracking to measure in vivo finger motion pathways. A landmark digitization protocol was developed and used in vivo, in a biomechanical study using EM trackers secured to the finger segments. In vivo results for finger flexion/extension showed no significant differences between EM and goniometer results, 5°±3°; p = 0.735.

A review of musculoskeletal modelling of human locomotion

Locomotion through the environment is important because movement provides access to key resources, including food, shelter and mates. Central to many locomotion-focused questions is the need to understand internal forces, particularly muscle forces and joint reactions. Musculoskeletal modelling, which typically harnesses the power of inverse dynamics, unites experimental data that are collected on living subjects with virtual models of their morphology. The inputs required for producing good musculoskeletal models include body geometry, muscle parameters, motion variables and ground reaction forces. This methodological approach is critically informed by both biological anthropology, with its focus on variation in human form and function, and mechanical engineering, with a focus on the application of Newtonian mechanics to current problems. Here, we demonstrate the application of a musculoskeletal modelling approach to human walking using the data of a single male subject. Furthermore, we discuss the decisions required to build the model, including how to customize the musculoskeletal model, and suggest cautions that both biological anthropologists and engineers who are interested in this topic should consider.

Estimating soft tissue artifact of the thigh in high knee flexion tasks using optical motion Capture: Implications for marker cluster placement

Soft tissue artifact in motion capture is widely accepted as a significant source of error in kinematic and kinetic measurements. Non-invasive methods of estimating soft tissue artifact, those requiring only motion capture, provide a feasible method to evaluate marker placement on a segment and enable recommendations for marker configurations which can minimize soft tissue artifact. The purpose of this study was to investigate the effect of thigh marker cluster location on soft tissue artifact during high knee flexion (>120 deg) as unique deformation of soft tissue occurs in this range (e.g. thigh-calf contact). Motion of the pelvis and lower limbs were recorded during squatting and kneeling in fifty participants. Six rigid marker clusters were affixed to the skin on the anterior, lateral, and anterolateral aspect, at the distal and middle third of the thighs. To estimate soft tissue artifact, the functional hip joint center was reconstructed relative to the pelvis cluster and each of the six thigh clusters throughout motion. The difference in the position of these two points was input into Bland-Altman analyses and compared between the thigh clusters. Across the tasks, the total mean difference ranged from 2.81 to 8.95 cm while the lower and upper limits of agreement ranged from -0.79 to 2.54 cm and 5.04 to 17.65 cm, respectively. Using this non-invasive method, the mid-anterolateral cluster was least susceptible to soft tissue artifact and thus would be recommended, while the lateral clusters were most susceptible and should avoided in high knee flexion and similar tasks.

Efficacy of quantifying marker-cluster rigidity in a multi-segment foot model: a Monte-Carlo based global sensitivity analysis and regression model

Marker-based clinical gait analysis and multi-segment foot models (MSFM) have been successfully used for the diagnosis and clinical management of various lower limb disorders. The accuracy and validity of the kinematics measured depend on the design of the model, as well as on the adherence to its inherent rigid body assumption. This study applies a Monte-Carlo based global sensitivity analysis to evaluate the efficacy of using 'rigid body error (σRBE)' in quantifying the rigidity of a MSFM marker-cluster. A regression model is proposed. It is concluded that σRBE is effective in quantifying rigidity.

Muscle forces and the demands of human walking

Reconstructing the locomotor behavior of extinct animals depends on elucidating the principles that link behavior, function, and morphology, which can only be done using extant animals. Within the human lineage, the evolution of bipedalism represents a critical transition, and evaluating fossil hominins depends on understanding the relationship between lower limb forces and skeletal morphology in living humans. As a step toward that goal, here we use a musculoskeletal model to estimate forces in the lower limb muscles of ten individuals during walking. The purpose is to quantify the consistency, timing, and magnitude of these muscle forces during the stance phase of walking. We find that muscles which act to support or propel the body during walking demonstrate the greatest force magnitudes as well as the highest consistency in the shape of force curves among individuals. Muscles that generate moments in the same direction as, or orthogonal to, the ground reaction force show lower forces of greater variability. These data can be used to define the envelope of load cases that need to be examined in order to understand human lower limb skeletal load bearing.

Summary: A musculoskeletal model of human walking reveals the consistency, timing, and magnitude of lower limb muscle forces across the stance phase.

Quantification of the errors associated with marker occlusion in stereophotogrammetric systems and implications on gait analysis

Optoelectronic stereophotogrammetric systems (OSSs) represent the standard for gait analysis. Despite widespread, their reported accuracy in nominal working conditions shows a variability of several orders of magnitude, ranging from few microns to several millimetres. No clear explanation for this variability has been provided yet. We hypothesized that this reflects an error affecting OSS outcomes when some of the tracked markers are totally or partially occluded. The aim of this paper is to quantify this error in static and dynamic conditions, also distinguishing between total and partial marker occlusion. A Vicon system featuring 8 cameras is employed in this study. Two camera distributions, one designed to maximize OSS accuracy and another one representative of a typical gait setup, are investigated. For both the setups, static and dynamic tests are performed, evaluating the different impact of partial and total marker occlusions. Marker occlusions significantly affected the system performances. The maximum measure variation reached 1.86 mm and 7.20 mm in static and dynamic conditions, respectively, both obtained in the case of partial occlusion. This systematic source of error is likely to affect gait measures: markers placed on the patient body are often visible only by half of the cameras, with swinging arms and legs providing moving occlusions. The maximum error observed in this study can potentially affect the kinematics outcomes of conventional gait models, particularly on frontal and coronal plane, and consequently the peak muscle forces estimated with musculoskeletal models.

A joint kinematics driven model of the pelvic soft tissue artefact

When skin-markers trajectories are used in human movement analysis, compensating for their relative movement with respect to the underlying bone (soft tissue artefact, STA) is essential for accurate bone-pose estimation; information about the artefact is required in the form of a mathematical model. Such model, not available for pelvic artefacts, could allow pelvic STA compensation in routine gait analysis by embedding it in skeletal kinematics estimators and developing ad-hoc optimization problems for the estimate of subject-specific model parameters. It was developed as driven by adjacent body segment kinematics. Model architecture feasibility was tested; its compensation effectiveness was assessed evaluating the error in pelvic orientation after removing the modelled artefact from the measured one. Five volunteers with a wide body mass range (BMI: 22-37) underwent MRI scans to reconstruct subject-specific pelvic digital bone models. Multiple anatomical calibrations performed in different static postures, as occurring during walking and star-arc movements, registering the bone-models with points digitized through stereophotogrammetry over pelvic bony prominences, allowed to define the relevant poses of a pelvis-embedded anatomical coordinate system. Such approach allowed to measure STAs over several pelvic anatomical landmarks, for each posture and subject. Model parameters were estimated by minimizing the least squares difference between measured and modelled STAs. The measured STAs were appropriately modelled with subject-specific calibrations, both in terms of shape (correlation coefficient: median [inter-quartile-range]: 0.72 [0.36]) and amplitude (root mean square residual: 3.0 [3.2] mm). Consequently, the overall error in pelvic orientation vector (5.1 [4.4] deg) was reduced after removing the modelled artefacts (2.5 [1.9] deg).

Knee Kinematics of Healthy Adults Measured Using Biplane Radiography

A dataset of knee kinematics in healthy, uninjured adults is needed to serve as a reference for comparison when evaluating the effects of injury, surgery, rehabilitation, and age. Most currently available datasets that characterize healthy knee kinematics were developed using conventional motion analysis, known to suffer from skin motion artifact. More accurate kinematics, obtained from bone pins or biplane radiography, have been reported for datasets ranging in size from 5 to 15 knees. The aim of this study was to characterize tibiofemoral kinematics and its variability in a larger sample of healthy adults. Thirty-nine knees were imaged using biplane radiography at 100 images/s during multiple trials of treadmill walking. Multiple gait trials were captured to measure stance and swing-phase knee kinematics. Six degrees-of-freedom kinematics were determined using a validated volumetric model-based tracking process. A bootstrapping technique was used to define average and 90% prediction bands for the kinematics. The average ROM during gait was 7.0 mm, 3.2 mm, and 2.9 mm in anterior/posterior (AP), medial/lateral (ML), and proximal/distal (PD) directions, and 67.3 deg, 11.5 deg, and 3.7 deg in flexion/extension (FE), internal/external (IE), and abduction/adduction (AbAd). Continuous kinematics demonstrated large interknee variability, with 90% prediction bands spanning approximately ±4 mm, ±10 mm, and ±5 mm for ML, AP, and PD translations and ±15 deg, ±10 deg, and ±6 deg in FE, IE, and AbAd. This dataset suggests substantial variability exists in healthy knee kinematics. This study provides a normative database for evaluating knee kinematics in patients who receive conservative or surgical treatment.

Soft tissue artifact causes underestimation of hip joint kinematics and kinetics in a rigid-body musculoskeletal model

Rigid body musculoskeletal models have been applied to study kinematics, moments, muscle forces, and joint reaction forces in the hip. Most often, models are driven with segment motions calculated through optical tracking of markers adhered to the skin. One limitation of optical tracking is soft tissue artifact (STA), which occurs due to motion of the skin surface relative to the underlying skeleton. The purpose of this study was to quantify differences in musculoskeletal model outputs when tracking body segment positions with skin markers as compared to bony landmarks measured by direct imaging of bone motion with dual fluoroscopy (DF). Eleven asymptomatic participants with normally developed hip anatomy were imaged with DF during level treadmill walking at a self-selected speed. Hip joint kinematics and kinetics were generated using inverse kinematics, inverse dynamics, static optimization and joint reaction force analysis. The effect of STA was assessed by comparing the difference in estimates from simulations based on skin marker positions (SM) versus virtual markers on bony landmarks from DF. While patterns were similar, STA caused underestimation of kinematics, range of motion (ROM), moments, and reaction forces at the hip, including flexion-extension ROM, maximum internal rotation joint moment and peak joint reaction force magnitude. Still, kinetic differences were relatively small, and thus they may not be relevant nor clinically meaningful.

Description of soft tissue artifacts and related consequences on hindlimb kinematics during canine gait

Background

Soft tissue artifacts (STAs) are a source of error in marker-based gait analysis in dogs. While some studies have revealed the existence of STAs in the canine hindlimb, STAs and their influence on kinematic gait analysis remain unclear.

Methods

Thirteen healthy Taiwan dogs affixed with twenty skin markers on the thigh and crus were recruited. Soft tissue artifacts and their influence on the determination of segment poses and stifle angles were assessed by simultaneously measuring marker trajectories and kinematics of the underlying bones via a model-based fluoroscopic analysis method.

Results

Markers on the thigh showed higher STAs than those on the crus, with root-mean-square amplitudes up to 15.5 mm. None of the tested marker clusters were able to accurately reproduce the skeletal poses, in which the maximum root-mean-square deviations ranged from 3.4° to 8.1°. The use of markers resulted in overestimated stifle flexion during 40–60% of the gait cycle and underestimated stifle flexion during 80–90% of the gait cycle.

Conclusions

Considerable magnitudes and effects of STAs on the marker-based 3D gait analysis of dogs were demonstrated. The results indicate that the development of error-compensation techniques based on knowledge regarding STAs is warranted for more accurate gait analysis.

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

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

The effect of intracortical bone pin on shoulder kinematics during dynamic activities

Intracortical bone pins are introduced as gold standard for analysing skeletal motion because of eliminating soft tissue artefact. However, excluding this methodological error might be in cost of intervening movement pattern by local anaesthesia and pain of external tool within body. The purpose of this study was to examine whether intracortical bone pins alter shoulder joint kinematics or coordination. Three subjects were analysed during arm elevation/depression in frontal and sagittal planes. Retroreflective skin markers captured the motion in two sessions, before and after inserting bone pins (SKIN and PIN sessions), respectively. Thoracohumeral and scapulothoracic kinematics and scapulohumeral rhythm (SHR) were compared between two sessions. Thoracohumeral exhibited lower elevation and internal rotation in PIN session especially close to maximum arm elevation. The highest differences were observed for scapulothoracic kinematics, with higher retraction during abduction as well as higher posterior tilt, lateral rotation and retraction during flexion in PIN session. In addition, no systematic changes in SHR between subjects was found. Statistically significant lower SHR in PIN session was observed over 87-100% of thoracohumeral elevation/depression cycle in frontal plane and over 25-61% in sagittal plane. Further studies should treat carefully toward the clinical validity of shoulder joint kinematics after inserting bone pins.

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.

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.

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

Multibody kinematics optimization (MKO) aims to reduce soft tissue artefact (STA) and is a key step in musculoskeletal modeling. The objective of this review was to identify the numerical methods, their validation and performance for the estimation of the human joint kinematics using MKO. Seventy-four papers were extracted from a systematized search in five databases and cross-referencing. Model-derived kinematics were obtained using either constrained optimization or Kalman filtering to minimize the difference between measured (i.e., by skin markers, electromagnetic or inertial sensors) and model-derived positions and/or orientations. While hinge, universal, and spherical joints prevail, advanced models (e.g., parallel and four-bar mechanisms, elastic joint) have been introduced, mainly for the knee and shoulder joints. Models and methods were evaluated using: (i) simulated data based, however, on oversimplified STA and joint models; (ii) reconstruction residual errors, ranging from 4 mm to 40 mm; (iii) sensitivity analyses which highlighted the effect (up to 36 deg and 12 mm) of model geometrical parameters, joint models, and computational methods; (iv) comparison with other approaches (i.e., single body kinematics optimization and nonoptimized kinematics); (v) repeatability studies that showed low intra- and inter-observer variability; and (vi) validation against ground-truth bone kinematics (with errors between 1 deg and 22 deg for tibiofemoral rotations and between 3 deg and 10 deg for glenohumeral rotations). Moreover, MKO was applied to various movements (e.g., walking, running, arm elevation). Additional validations, especially for the upper limb, should be undertaken and we recommend a more systematic approach for the evaluation of MKO. In addition, further model development, scaling, and personalization methods are required to better estimate the secondary degrees-of-freedom (DoF).

Prediction of thigh-calf contact parameters from anthropometric regression

High knee flexion postures are common in industry and cultural practices, but the mechanical effect of intersegmental force, particularly thigh-calf contact force, on knee joint compressive force is poorly understood. Although some studies have measured thigh-calf contact parameters occurring in a number of high flexion postures, joint contact modeling would benefit from efforts to predict thigh-calf contact force for use in computational models. Therefore, this study assessed the strength of correlations and linear multiple regression models on the following five high flexion thigh-calf contact parameters in a young, healthy population: the onset angle of thigh-calf contact, maximum flexion angle, total thigh-calf contact force, center of force, and contact area at maximum flexion. Regressions used anthropometric values (and in some cases, maximum flexion angle). Overall, maximum flexion angle and center of force location had the most significant correlates and strong linear fits with regressive models. Thigh-calf contact onset, total force magnitude, and contact area had only moderate to weak relationships. An exploratory attempt at regression using grouped movements into gross patterns (e.g. two types of squatting were grouped into a general squatting category) using maximum flexion angle and center of force location as dependent variables resulted in similar model fitting. These findings suggest that a causal relationship between select anthropometrics and lower limb range of motion may exist, but further exploration is necessary to determine clinically reliable predictive models.

Evaluation of functional methods of joint centre determination for quasi-planar movement

Functional methods identify joint centres as the centre of rotation (CoR) of two adjacent movements during an ad-hoc movement. The methods have been used for functionally determining hip joint centre in gait analysis and have revealed advantages compared to predictive regression techniques. However, the current implementation of functional methods hinders its application in clinical use when subjects have difficulties performing multi-plane movements over the required range. In this study, we systematically investigated whether functional methods can be used to localise the CoR during a quasi-planar movement. The effects of the following factors were analysed: the algorithms, the range and speed of the movement, marker cluster location, marker cluster size and distance to the joint centre. A mechanical linkage was used in our study to isolate the factors of interest and give insight to variation in implementation of functional methods. Our results showed the algorithms and cluster locations significantly affected the estimate results. For all algorithms, a significantly positive relationship between CoR errors and the distance of proximal cluster coordinate location to the joint centre along the medial-lateral direction was observed while the distal marker clusters were best located as close as possible to the joint centre. By optimising the analytical and experimental factors, the transformation algorithms achieved a root mean square error (RMSE) of 5.3 mm while the sphere fitting methods yielded the best estimation with an RMSE of 2.6 mm. The transformation algorithms performed better in presence of random noise and simulated soft tissue artefacts.

Quantification of three-dimensional soft tissue artifacts in the canine hindlimb during passive stifle motion

Background

Three-dimensional joint kinematics during canine locomotion are commonly measured using skin marker-based stereophotogrammetry technologies. However, marker-related errors caused by the displacement of the skin surface relative to the underlying bones (i.e., soft tissue artifacts, STA) may affect the accuracy of the measurements and obscure clinically relevant information. Few studies have assessed STA in canine limbs during kinematic analysis. The magnitudes and patterns of the STA and their influence on kinematic analysis remain unclear. Therefore, the current study aims to quantify the in vivo STA of skin markers on the canine thigh and crus during passive joint motion. The stifle joints of ten dogs were passively extended while the skin markers were measured using a motion capture system, and skeletal kinematics were determined using a CT-to-fluoroscopic image registration method.

Results

The skin markers exhibited considerable STA relative to the underlying bones, with a peak amplitude of 27.4 mm for thigh markers and 28.7 mm for crus markers; however, the amplitudes and displacement directions at different attachment sites were inconsistent. The markers on the cranial thigh and lateral crus closer to the stifle joint had greater STA amplitudes in comparison to those of other markers. Most markers had STA with linear and quadratic patterns against the stifle flexion angles. These STA resulted in underestimated flexion angles but overestimated adduction and internal rotation when the stifle was flexed to greater than 90°.

Conclusions

Marker displacements relative to the underlying bones were prominent in the cranial aspect of the thigh and the proximal-lateral aspect of the crus. The calculated stifle kinematic variables were also affected by the STA. These findings can provide a reference for marker selection in canine motion analysis for similar motion tasks and clarify the relationship between STA patterns and stifle kinematics; the results may therefore contribute to the development of STA models and compensation techniques for canine motion analysis.

Electronic supplementary material

The online version of this article (10.1186/s12917-018-1714-7) contains supplementary material, which is available to authorized users.

A Simple Algorithm for Assimilating Marker-Based Motion Capture Data During Periodic Human Movement Into Models of Multi-Rigid-Body Systems

Human movement analysis is often performed with a model of multi-rigid-body system, whereby reflective-marker-based motion capture data are assimilated into the model for characterizing kinematics and kinetics of the movements quantitatively. Accuracy of such analysis is limited, due to motions of the markers on the skin relative to the underlying skeletal system, referred to as the soft tissue artifact (STA). Here we propose a simple algorithm for assimilating motion capture data during periodic human movements, such as bipedal walking, into models of multi-rigid-body systems in a way that the assimilated motions are not affected by STA. The proposed algorithm assumes that STA time-profiles during periodic movements are also periodic. We then express unknown STA profiles using Fourier series, and show that the Fourier coefficients can be determined optimally based solely on the periodicity assumption for the STA and kinematic constraints requiring that any two adjacent rigid-links are connected by a rotary joint, leading to the STA-free assimilated motion that is consistent with the multi-rigid-link model. To assess the efficiency of the algorithm, we performed a numerical experiment using a dynamic model of human gait composed of seven rigid links, on which we placed STA-affected markers, and showed that the algorithm can estimate the STA accurately and retrieve the non-STA-affected true motion of the model. We also confirmed that our STA-removal processing improves accuracy of the inverse dynamics analysis, suggesting the usability of the proposed algorithm for gait analysis.

Functional estimation of bony segment lengths using magneto-inertial sensing: Application to the humerus

Inertial sensor technology has assumed an increasingly important role in the field of human motion analysis. However, the reliability of the kinematic estimates could still be critical for specific applications in the field of functional evaluation and motor rehabilitation. Within this context, the definition of subject-specific multi-body kinematic models is crucial since it affects the accuracy and repeatability of movement reconstruction. A key step for kinematic model calibration is the determination of bony segment lengths. This study proposes a functional approach for the in vivo estimation of the humerus length using a single magneto-inertial measurement unit (MIMU) positioned on the right distal posterior forearm. The humerus length was estimated as the distance between the shoulder elevation axis and the elbow flexion-extension axis. The calibration exercise involved five shoulder elevations in the sagittal plane with the elbow completely extended and five elbow flexion-extensions with the upper arm rigidly aligned to the trunk. Validation of the method was conducted on five healthy subjects using the humerus length computed from magnetic resonance imaging as the gold standard. The method showed mean absolute errors of 12 ± 9 mm, which were in the estimate of the humerus length. When using magneto-inertial technology, the proposed functional method represents a promising alternative to the regressive methods or manual measurements for performing kinematic model calibrations. Although the proposed methodology was validated for the estimation of the humerus length, the same approach can be potentially extended to other body segments.

Elbow joint kinematics during cricket bowling using magneto-inertial sensors: A feasibility study

Magnetic and inertial measurement units (MIMUs) may provide an accessible, three-dimensional, in-field alternative to laboratory-restricted marker-based motion capture. Existing upper limb MIMU models have predominantly been validated with low-velocity motion and their suitability for use with sport-based movements remains relatively untested. We propose a MIMU system approach to enable the estimation of anatomically meaningful and participant-specific elbow kinematics with considerations for use with cricket bowling. A novel standardised elbow reference posture of 90 degrees flexion and 0 deg pronation, and functional definition of elbow joint axes of rotation calibrated the MIMU method model before it was validated across three experiments: (1) simple elbow rotations with a mechanical linkage; (2) low-velocity elbow rotations in human participants; and (3) low-medium velocity sport-based movements in human participants. The proposed MIMU method demonstrated high elbow kinematic measurement agreement when compared with a criterion measure across all three conditions. However, during experiment 3, sensor components neared their measurement capacity and the MIMU method elbow flexion measurement variability increased. We conclude that the proposed MIMU method can estimate anatomically referenced, participant-specific joint angles, however, the hardware specifications of currently available systems may limit application in high-velocity/acceleration situations, preventing the measurement of cricket bowling in-field for now.

Comparison of Marker-Based and Stereo Radiography Knee Kinematics in Activities of Daily Living

Movement of the marker positions relative to the body segments obscures in vivo joint level motion. Alternatively, tracking bones from radiography images can provide precise motion of the bones at the knee but is impracticable for measurement of body segment motion. Consequently, researchers have combined marker-based knee flexion with kinematic splines to approximate the translations and rotations of the tibia relative to the femur. Yet, the accuracy of predicting six degree-of-freedom joint kinematics using kinematic splines has not been evaluated. The objectives of this study were to (1) compare knee kinematics measured with a marker-based motion capture system to kinematics acquired with high speed stereo radiography (HSSR) and describe the accuracy of marker-based motion to improve interpretation of results from these methods, and (2) use HSSR to define and evaluate a new set of knee joint kinematic splines based on the in vivo kinematics of a knee extension activity. Simultaneous measurements were recorded from eight healthy subjects using HSSR and marker-based motion capture. The marker positions were applied to three models of the lower extremity to calculate tibiofemoral kinematics and compared to kinematics acquired with HSSR. As demonstrated by normalized RMSE above 1.0, varus-valgus rotation (1.26), medial-lateral (1.26), anterior-posterior (2.03), and superior-inferior translations (4.39) were not accurately measured. Using kinematic splines improved predictions in varus-valgus (0.81) rotation, and medial-lateral (0.73), anterior-posterior (0.69), and superior-inferior (0.49) translations. Using splines to predict tibiofemoral kinematics as a function knee flexion can lead to improved accuracy over marker-based motion capture alone, however this technique was limited in reproducing subject-specific kinematics.

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

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

Trends Supporting the In-Field Use of Wearable Inertial Sensors for Sport Performance Evaluation: A Systematic Review

Recent technological developments have led to the production of inexpensive, non-invasive, miniature magneto-inertial sensors, ideal for obtaining sport performance measures during training or competition. This systematic review evaluates current evidence and the future potential of their use in sport performance evaluation. Articles published in English (April 2017) were searched in Web-of-Science, Scopus, Pubmed, and Sport-Discus databases. A keyword search of titles, abstracts and keywords which included studies using accelerometers, gyroscopes and/or magnetometers to analyse sport motor-tasks performed by athletes (excluding risk of injury, physical activity, and energy expenditure) resulted in 2040 papers. Papers and reference list screening led to the selection of 286 studies and 23 reviews. Information on sport, motor-tasks, participants, device characteristics, sensor position and fixing, experimental setting and performance indicators was extracted. The selected papers dealt with motor capacity assessment (51 papers), technique analysis (163), activity classification (19), and physical demands assessment (61). Focus was placed mainly on elite and sub-elite athletes (59%) performing their sport in-field during training (62%) and competition (7%). Measuring movement outdoors created opportunities in winter sports (8%), water sports (16%), team sports (25%), and other outdoor activities (27%). Indications on the reliability of sensor-based performance indicators are provided, together with critical considerations and future trends.

Comparison of soft tissue artifact and its effects on knee kinematics between non-obese and obese subjects performing a squatting activity recorded using an exoskeleton

BACKGROUND

Rigid attachment systems are one of the methods used to compensate for soft tissue artifact (STA) inherent in joint motion analyses.

RESEARCH QUESTION

The goal of this study was to quantify STA of an exoskeleton design to reduce STA at the knee, and to assess the accuracy of 3D knee kinematics recorded with the exoskeleton in non-obese and obese subjects during quasi-static weight-bearing squatting activity using biplane radiography.

METHODS

Nine non-obese and eight obese subjects were recruited. The exoskeleton was calibrated on each subject before they performed a quasistatic squatting activity in the EOS^® imaging system. 3D models of exoskeleton markers and knee bones were reconstructed from EOS^® radiographs; they served to quantify STA and to evaluate differences between the markers and bones knee kinematics during the squatting activity.

RESULTS

The results showed that STA observed at the femur was larger in non-obese subjects than in obese subjects in frontal rotation (p = 0.004), axial rotation (p = 0.000), medio-lateral displacement (p = 0.000) and antero-posterior displacement (p = 0.019), while STA observed at the tibia was lower in non-obese subjects than in obese subjects for the three rotations (p < 0.05) and medio-lateral displacement (p = 0.015). Differences between the markers and bones knee kinematics increased with knee flexion and were similar in both groups, except for abduction-adduction: 4.9° for non-obese subjects against 2.3° for obese subjects (p = 0.011).

SIGNIFICANCE

This study demonstrated that STA at the femur and its impact on knee abduction-adduction using a specific exoskeleton were greater among non-obese subjects than obese subjects, which is encouraging for future biomechanical studies on pathologies such as osteoarthritis.

A Novel Ultrasound-Based Lower Extremity Motion Tracking System

Tracking joint motion of the lower extremity is important for human motion analysis. In this study, we present a novel ultrasound-based motion tracking system for measuring three-dimensional (3D) position and orientation of the femur and tibia in 3D space and quantifying tibiofemoral kinematics under dynamic conditions. As ultrasound is capable of detecting underlying bone surface noninvasively through multiple layers of soft tissues, an integration of multiple A-mode ultrasound transducers with a conventional motion tracking system provides a new approach to track the motion of bone segments during dynamic conditions. To demonstrate the technical and clinical feasibilities of this concept, an in vivo experiment was conducted. For this purpose the kinematics of healthy individuals were determined in treadmill walking conditions and stair descending tasks. The results clearly demonstrated the potential of tracking skeletal motion of the lower extremity and measuring six-degrees-of-freedom (6-DOF) tibiofemoral kinematics and related kinematic alterations caused by a variety of gait parameters. It was concluded that this prototyping system has great potential to measure human kinematics in an ambulant, non-radiative, and noninvasive manner.