Effects of hip joint centre mislocation on gait analysis results

Impact of model geometry and joint center locations on inverse kinematic/dynamic predictions: A comparative study of sexually dimorphic models

This work illustrates the sensitivity of demographically characteristic body segment inertial properties and subject-specific customization on model performance. One characteristic demographic, gender, and one subject-specific characteristic, hip joint center location, were represented with musculoskeletal modeling to evaluate how design decisions may alter model outputs. Generic sexually dimorphic musculoskeletal models were developed from the commonly used Rajagopal model using male and female data adapted by Dumas et al. Hip joint centers of these models were adjusted based on functional joint center testing. The kinematics and dynamics of 40 gait cycles from four subjects are predicted using these models. Two-way analysis of variance (ANOVA) was performed on the continuous time series data using statistical parametric mapping (SPM) to assess changes in kinematics/dynamics due to either choice in model (Rajagopal vs Dumas) or whether joint center adjustment was performed. The SPM based two-way ANOVA of the inverse dynamics found that differences in the Rajagopal and Dumas models resulted in significant differences in sagittal plane moments during swing (0.115 ± 0.032 Nm/kg difference in mean hip flexion moment during initial swing and a 0.077 ± 0.041 Nm/kg difference in mean hip extension moment during terminal swing), and differences between the models with and without hip joint center adjustment resulted in significant differences in hip flexion and abduction moments during stance (0.217 ± 0.055 Nm/kg increased mean hip abductive moment). By comparing the outputs of these differently constructed models with each other, the study finds that dynamic predictions of stance are sensitive to positioning of joint centers, and dynamic predictions of swing are more sensitive to segment mass/inertial properties.

Which method should we use to determine the hip joint center location in individuals with a high amount of soft tissue?

BACKGROUND

This study investigated the most accurate method for estimating the hip joint center position in clinical 3D gait analysis for young individuals with high amounts of soft tissue. We compared position estimates of five regression-based and two functional methods to the hip joint center position obtained through 3D free-hand ultrasound.

METHODS

For this purpose, the data of 14 overweight or obese individuals with a mean age of 13.6 (SD 2.1 yrs) and a BMI of 36.5 (SD 7.1 kg/m2, range 26-52 kg/m2) who underwent standard clinical 3D gait analysis were used. The data of each participant were processed with five regression-based and two functional methods and compared to the hip joint center identified via 3D free-hand ultrasound.

FINDINGS

The absolute location errors to 3D free-hand ultrasound for each anatomical plane and the Euclidean distances served as outcomes next to their effects on gait variables. The data suggest that regression-based methods are preferable to functional methods in this population, as the latter demonstrated the highest variability in accuracy with large errors for some individuals.

INTERPRETATION

Based on our findings we recommend using the regression method presented by Hara et al. due to its superior overall accuracy of <9 mm on average in all planes and the lowest impact on kinematic and kinetic output variables. We do not recommend using the Harrington equations (single and multiple) in populations with high amounts of soft tissue as they require pelvic depth as input, which can be massively biased when a lot of soft tissue is present around the pelvis.

Influence of Skin Marker Positioning and Their Combinations on Hip Joint Center Estimation Using the Functional Method

Accurate estimation of hip joint center (HJC) position is crucial during gait analysis. HJC is obtained with predictive or functional methods. But in the functional method, there is no consensus on where to place the skin markers and which combination to use. The objective of this study was to analyze how different combinations of skin markers affect the estimation of HJC position relative to predictive methods. Forty-one healthy volunteers were included in this study; thirteen markers were placed on the pelvis and hip of each subject's lower limbs. Various marker combinations were used to determine the HJC position based on ten calibration movement trials, captured by a motion capture system. The estimated HJC position for each combination was evaluated by focusing on the range and standard deviation of the mean norm values of HJC and the mean X, Y, Z coordinates of HJC for each limb. The combinations that produced the best estimates incorporated the markers on the pelvis and on proximal and easily identifiable muscles, with results close to predictive methods. The combination that excluded the markers on the pelvis was not robust in estimating the HJC position.

Comparison of kinematics and joint moments calculations for lower limbs during gait using markerless and marker-based motion capture

Objective: This study aimed at quantifying the difference in kinematic and joint moments calculation for lower limbs during gait utilizing a markerless motion system (TsingVA Technology, Beijing, China) in comparison to values estimated using a marker-based motion capture system (Nokov Motion Capture System, Beijing, China). Methods: Sixteen healthy participants were recruited for the study. The kinematic data of the lower limb during walking were acquired simultaneously based on the markerless motion capture system (120 Hz) and the marker-based motion capture system (120 Hz). The ground reaction force was recorded synchronously using a force platform (1,200 Hz). The kinematic and force data were input into Visual3D for inverse dynamics calculations. Results: The difference in the lower limb joint center position between the two systems was the least at the ankle joint in the posterior/anterior direction, with the mean absolute deviation (MAD) of 0.74 cm. The least difference in measuring lower limb angles between the two systems was found in flexion/extension movement, and the greatest difference was found in internal/external rotation movement. The coefficient of multiple correlations (CMC) of the lower limb three joint moments for both systems exceeded or equaled 0.75, except for the ad/abduction of the knee and ankle. All the Root Mean Squared Deviation (RMSD) of the lower limb joint moment are below 18 N·m. Conclusion: The markerless motion capture system and marker-based motion capture system showed a high similarity in kinematics and inverse dynamic calculation for lower limbs during gait in the sagittal plane. However, it should be noted that there is a notable deviation in ad/abduction moments at the knee and ankle.

Differences between lower extremity joint running kinetics captured by marker-based and markerless systems were speed dependent

BACKGROUND

The development of computer vision technology has enabled the use of markerless movement tracking for biomechanical analysis. Recent research has reported the feasibility of markerless systems in motion analysis but has yet to fully explore their utility for capturing faster movements, such as running. Applied studies using markerless systems in clinical and sports settings are still lacking. Thus, the present study compared running biomechanics estimated by marker-based and markerless systems. Given running speed not only affects sports performance but is also associated with clinical injury prevention, diagnosis, and rehabilitation, we aimed to investigate the effects of speed on the comparison of estimated lower extremity joint moments and powers between markerless and marker-based technologies during treadmill running as a concurrent validating study.

METHODS

Kinematic data from marker-based/markerless technologies were collected, along with ground reaction force data, from 16 young adults running on an instrumented treadmill at 3 speeds: 2.24 m/s, 2.91 m/s, and 3.58 m/s (5.0 miles/h, 6.5 miles/h, and 8.0 miles/h). Sagittal plane moments and powers of the hip, knee, and ankle were calculated by inverse dynamic methods. Time series analysis and statistical parametric mapping were used to determine system differences.

RESULTS

Compared to the marker-based system, the markerless system estimated increased lower extremity joint kinetics with faster speed during the swing phase in most cases.

CONCLUSION

Despite the promising application of markerless technology in clinical settings, systematic markerless overestimation requires focused attention. Based on segment pose estimations, the centers of mass estimated by markerless technologies were farther away from the relevant distal joint centers, which led to greater joint moments and powers estimates by markerless vs. marker-based systems. The differences were amplified by running speed.

Hip and lumbosacral joint centre locations in asian population: Biases produced by existing regression equations and development of new equations

The hip and lumbosacral joint centre (HJC and LSJC) predictions are required to analyse the lumbo-pelvic-hip dynamics during various human motions. Some HJC and LSJC regression equations based on pelvic dimension have been developed; however, the pre-existing methods need to be re-evaluated, and methodological reconsideration may improve the regression methods. Here we show that pre-existing methods produce biased predictions of the LSJC and HJC in 23 male and 24 female Japanese adults, and that the biases in the LSJC differ between sexes, using magnetic resonance imaging (MRI) around the pelvis. Compared with directly measured locations on MRI, the pre-existing regression equations predict LSJC to be more posterior in males and more inferior and posterior in females, and HJC to be more medial in both sexes. The better pre-existing regression equation for LSJC height differs between sexes, with pelvic-width-base better in males and pelvic-depth-base better in females, respectively. We suggest the unsuitability of pre-existing methods to our dataset consisting of Japanese adults and the importance of considering sex differences in regression methods. We propose regression equations to predict HJC and LSJC, considering soft-tissue thickness, sex differences, and a height-directional measure, using least absolute shrinkage and selection operator regression. We validate them using leave-one-out cross-validation (LOOCV). LOOCV shows that our model produces negligible biases and smaller absolute errors than the pre-existing regressions; in particular, the anteroposterior absolute error for LSJC is less than half that of the pre-existing regression. Our regression equation can be a powerful solution for accurate motion analysis.

Development of a simulation system for femoroacetabular impingement detection based on 3D images

Image-based criteria have been adopted to diagnose femoroacetabular impingement (FAI). However, the overlapping property of the two-dimensional X-ray outlines and static and supine posture of taking computed tomography (CT) and magnetic resonance imaging images potentially affect the accuracy of the criteria. This study developed a CT image-based dynamic criterion to effectively simulate FAI, thereby providing a basis for physicians to perform pre-operative planning for arthroscopic surgery. Post-operative CT images of 20 patients with satisfactory surgical results were collected, and 10 sets of models were used to define the flexion rotation centre (FRC) of the three-dimensional FAI model. First, let these 10 groups of models simulate the FAI detection action and find the best centre offset, and then FRC is the result of averaging these 10 groups of best displacements. The model was validated in 10 additional patients. Finally, through the adjustment basis of FRC, the remaining 10 sets of models can find out the potential position of FAI during the dynamic simulation process. Rotational collisions detected using FRC indicate that the patient's post-operative flexion angle may reach 120° or greater, which is close to the actual result. The recommended surgical range of the diagnostic system (average length of 6.4 mm, width of 4.1 mm and depth of 3.2 mm) is smaller than the actual surgical results, which prevents the doctor from performing excessive resection operations, which may preserve more bones. The FRC diagnostic system detects the distribution of FAI in a simple manner. It can be used as a pre-operative diagnosis reference for clinicians, hoping to improve the effect and accuracy of debridement surgery.

Predictive estimation of ovine hip joint centers: A regression approach

Estimation of the hip joint center in ovine biomechanical analysis is often overlooked or estimated using a marker on the greater trochanter which can result in large errors that propagate through subsequent analyses. The purpose of this study was to develop a novel method of estimating the hip joint centers in sheep to facilitate more accurate analysis of ovine biomechanics. CT scans from 16 sheep of varying ages, weight, sex, and phenotypes were acquired and the data was used to calculate the known hip joint center by sphere fitting the femoral head. Anatomical measurements and additional subject information were used to create a variety of regression models to estimate the hip joint centers in absence of CT data. The best regression equation created utilized markers placed on the tuber coxae and tuber ischii of the pelvis and resulted in a mean 3D Euclidean distance error of 6.43 ± 2.22 mm (mean ± standard deviation) between the known and estimated hip joint center. The regression models produced allow for more detailed, accurate and robust analysis of sheep biomechanics.

Markerless motion capture estimates of lower extremity kinematics and kinetics are comparable to marker-based across 8 movements

Motion analysis is essential for assessing in-vivo human biomechanics. Marker-based motion capture is the standard to analyze human motion, but the inherent inaccuracy and practical challenges limit its utility in large-scale and real-world applications. Markerless motion capture has shown promise to overcome these practical barriers. However, its fidelity in quantifying joint kinematics and kinetics has not been verified across multiple common human movements. In this study, we concurrently captured marker-based and markerless motion data on 10 healthy study participants performing 8 daily living and exercise movements. We calculated the correlation (Rxy) and root-mean-square difference (RMSD) between markerless and marker-based estimates of ankle dorsi-plantarflexion, knee flexion, and three-dimensional hip kinematics (angles) and kinetics (moments) during each movement. Estimates from markerless motion capture matched closely with marker-based in ankle and knee joint angles (Rxy ≥ 0.877, RMSD ≤ 5.9°) and moments (Rxy ≥ 0.934, RMSD ≤ 2.66 % height × weight). High outcome comparability means the practical benefits of markerless motion capture can simplify experiments and facilitate large-scale analyses. Hip angles and moments demonstrated more differences between the two systems (RMSD: 6.7-15.9° and up to 7.15 % height × weight), especially during rapid movements such as running. Markerless motion capture appears to improve the accuracy of hip-related measures, yet more research is needed for validation. We encourage the biomechanics community to continue verifying, validating, and establishing best practices for markerless motion capture, which holds exciting potential to advance collaborative biomechanical research and expand real-world assessments needed for clinical translation.

Are we overestimating internal rotation gait by conventional modelling?

BACKGROUND

The determination of the knee joint axis (KJA) via specific calibration movements has become a promising alternative to the conventional approach to determine this axis based on regression equations or directly via marker placement on bony landmarks of the knee. Since the orientation of the KJA may differ between methods, it has direct influence on hip rotation and may therefore influence clinical decision making in context of transverse plane gait deviations.

RESEARCH QUESTION

Does a functional KJA calibration lead to clinically relevant differences in hip rotation estimates during gait compared to the conventional method?

METHODS

95 subjects (age: 19.9 years; BMI: 21.1 kg/m²), including 71 patients with potential rotation malalignment, were prospectively examined and underwent 3D gait analysis. For the conventional approach the KJA was determined by applying a knee alignment device, for the functional approach subjects were asked to perform two different calibration movements. Each procedure was performed twice. Mean hip rotation in stance (mHipRotSt) was determined following the conventional and the functional KJA calibration.

RESULTS

Deming regression analysis for the comparison of conventional and functionally measured hip rotation revealed a systematic and substantial difference between methods (slope: 0.63; intercept: 0.31°). Measurement repetition with the knee alignment device revealed typical errors around 5°, whereas the functional methods lead to profoundly smaller errors around 1-2° with slightly inferior results for SQUAT compared to FLEX. However, when compared to conventional frontal plane video-taping, the conventional method seemed to reflect the more consistent results.

SIGNIFICANCE

The systematic linear discrepancy in mHipRotSt obtained by a functional approach as compared to the conventional approach appears critical since patients with severe internal or external rotation gait may be misjudged in function when receiving corrective procedures such as femoral derotation osteotomy.

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.

Markerless motion capture estimates of lower extremity kinematics and kinetics are comparable to marker-based across 8 movements

Motion analysis is essential for assessing in-vivo human biomechanics. Marker-based motion capture is the standard to analyze human motion, but the inherent inaccuracy and practical challenges limit its utility in large-scale and real-world applications. Markerless motion capture has shown promise to overcome these practical barriers. However, its fidelity in quantifying joint kinematics and kinetics has not been verified across multiple common human movements. In this study, we concurrently captured marker-based and markerless motion data on 10 healthy subjects performing 8 daily living and exercise movements. We calculated the correlation (R xy ) and root-mean-square difference (RMSD) between markerless and marker-based estimates of ankle dorsi-plantarflexion, knee flexion, and three-dimensional hip kinematics (angles) and kinetics (moments) during each movement. Estimates from markerless motion capture matched closely with marker-based in ankle and knee joint angles (R xy ≥ 0.877, RMSD ≤ 5.9°) and moments (R xy ≥ 0.934, RMSD ≤ 2.66 % height × weight). High outcome comparability means the practical benefits of markerless motion capture can simplify experiments and facilitate large-scale analyses. Hip angles and moments demonstrated more differences between the two systems (RMSD: 6.7° - 15.9° and up to 7.15 % height × weight), especially during rapid movements such as running. Markerless motion capture appears to improve the accuracy of hip-related measures, yet more research is needed for validation. We encourage the biomechanics community to continue verifying, validating, and establishing best practices for markerless motion capture, which holds exciting potential to advance collaborative biomechanical research and expand real-world assessments needed for clinical translation.

Comparison of Lower Extremity Joint Moment and Power Estimated by Markerless and Marker-Based Systems during Treadmill Running

Background: Markerless (ML) motion capture systems have recently become available for biomechanics applications. Evidence has indicated the potential feasibility of using an ML system to analyze lower extremity kinematics. However, no research has examined ML systems’ estimation of the lower extremity joint moments and powers. This study aimed to compare lower extremity joint moments and powers estimated by marker-based (MB) and ML motion capture systems. Methods: Sixteen volunteers ran on a treadmill for 120 s at 3.58 m/s. The kinematic data were simultaneously recorded by 8 infrared cameras and 8 high-resolution video cameras. The force data were recorded via an instrumented treadmill. Results: Greater peak magnitudes for hip extension and flexion moments, knee flexion moment, and ankle plantarflexion moment, along with their joint powers, were observed in the ML system compared to an MB system (p < 0.0001). For example, greater hip extension (MB: 1.42 ± 0.29 vs. ML: 2.27 ± 0.45) and knee flexion (MB: −0.74 vs. ML: −1.17 nm/kg) moments were observed in the late swing phase. Additionally, the ML system’s estimations resulted in significantly smaller peak magnitudes for knee extension moment, along with the knee production power (p < 0.0001). Conclusions: These observations indicate that inconsistent estimates of joint center position and segment center of mass between the two systems may cause differences in the lower extremity joint moments and powers. However, with the progression of pose estimation in the markerless system, future applications can be promising.

Predicting the hip joint centre in children: New regression equations, linear scaling, and statistical shape modelling

Determination of the hip joint centre (HJC) is important to accurately estimate hip joint motion, moments and muscle forces. The most accurate method for HJC estimation without medical imaging is an area of interest in the biomechanics community, especially in a paediatric population, which has not been widely evaluated. HJC locations were calculated by sphere-fitting to the acetabulum of three-dimensional pelvises segmented from 333 CT scans of children aged 4 to 18 years old. Three methods for determining the HJC were compared: regression equations, linear scaling, and shape model prediction. The new regression equations developed in this study produced Euclidean distance errors of 6.23 mm ± 2.90 mm. Linear scaling of paediatric bone produced errors of 3.90 mm ± 2.52 mm and adult bone scaling of 5.45 mm ± 3.26 mm. Prediction of the HJC using a paediatric statistical shape model produced mean Euclidian distance errors of 2.95 mm ± 1.65 mm. Overall, shape model prediction of the HJC produced the lowest errors, with linear scaling of a mean paediatric pelvis providing better estimates than regression equations.

Rotation sequence and marker tracking method affects the humerothoracic kinematics of manual wheelchair propulsion

The literature on shoulder (humerothoracic) kinematics in manual wheelchair propulsion is growing. Inconsistencies in the reporting of which rotation sequence is used to compute three-dimensional (3D) angles complicates the interpretation and comparison between studies. The purpose of this study was to compare the effects of three often used and recommended rotation sequences (ZXY, XZY, and YXY) and two tracking methods (anatomical and cluster only) on the humerothoracic kinematics of manual wheelchair propulsion. Fourteen able-bodied participants performed manual wheelchair propulsion on a treadmill, while a motion capture system recorded the movements at 120 Hz. Humeral and thoracic segment coordinate systems were constructed according to ISB recommendations. Humerothoracic angles were calculated using each of the three rotation sequences. The ZXY and XZY sequences yielded similar angles in terms of both shape and amplitude, but, perhaps unsurprisingly, these differed substantially from the YXY sequence. Anatomical tracking showed neither gimbal locks nor phase angle discontinuities for any rotation sequence, while cluster tracking yielded phase angle discontinuities for the ZXY and YXY rotation sequences. The two tracking methods yielded similar joint angles for all sequences except for internal/external rotation, and the cluster-only method had larger variability than the anatomical method. These results highlight the importance of reporting which rotation sequence and tracking method are used when calculating humerothoracic angles in order to allow for straightforward interpretation of results and comparison across studies.

A regularized functional method to determine the hip joint center of rotation in subjects with limited range of motion

The symmetrical center of rotation estimation (SCoRE) is probably one of the most used functional method for estimating the hip join center (HJC). However, it requires of complex multi-plane movements to find accurate estimations of HJC. Thus, using SCoRE for people with limited hip range of motion will lead to poor HJC estimation. In this work, we propose an anisotropic regularized version of the SCoRE formulation (RSCoRE), which is able to estimate the HJC location by using only standard gait trials, avoiding the need of recording complex multi-plane movements. RSCoRE is evaluated in both accuracy and repeatability of the estimation as compared to functional and predictive methods on a self-recorded cohort of fifteen young healthy adults with no hip joint pathologies or other disorders that could affect their gait. Given that, no medical images were available for this study, to quantify the global error of HJC the SCoRE residual was used. RSCoRE presents a global error of about 12 mm, similarly to the best performance of SCoRE. The comparison of the coordinate's errors at each coordinate indicates that HJC estimations from SCoRE with complex multi-plane movements and RSCoRE are not statistical significantly different. Finally, we show that the repeatability of RSCoRE is similar to the rest of the tested methods, yielding to repeatability values between 0.72 and 0.79. In conclusion, not only the RSCoRE yields similar estimation performance than SCoRE, but it also avoids the need of complex multi-plane movements to be performed by the subject of analysis. For this reason, RSCoRE has the potential to be a valuable approach for estimating the HJC location in people with limited hip ROM.

Functional hip joint centre determination in children with cerebral palsy

BACKGROUND

Although functional methods determining the hip joint center (HJC) are becoming increasingly popular, no systematic investigation has been conducted yet to assess the reliability of functional hip joint calibration in patients with cerebral palsy (CP).

RESEARCH QUESTION

What is the most reliable way to conduct functional calibration motions for estimating HJC location in children with CP and movement disorders?

METHODS

Twenty-two patients with CP were included in the study. A marker set for Plug-in Gait with additional cluster markers was used. Two functional calibration movements, including a new movement, were proposed and tested with one and three repetitions each. Functional HJCs were determined using the SCoRE approach and compared to results obtained by applying the conventional regression method for assessing face validity.

RESULTS

The choice of calibration movement had significant impact on SCoRE residuals and HJC location. Increasingly repeating calibration movements did not improve results. A modified star movement by allowing the toes to tip the ground provided the most reliable data and is feasible for children with GMFCS level I-III. The feasibility of the method is further improved by analyzing hip motion in the contralateral stance limb and, among the calibration movements, gave the most precise HJC estimation.

SIGNIFICANCE

Type and performance of the functional calibration movement is one key factor for determining a robust HJC. Analyzing the data in the stance leg via the modified star motion yielded robust and reasonable results for the HJC location, which should be validated in further studies that include imaging methods. Using one repetition instead of three seems promising in terms of feasibility for patients with movement disorder.

Kinematics Adaptation and Inter-Limb Symmetry during Gait in Obese Adults

The main purpose of this study is to characterize lower limb joint kinematics during gait in obese individuals by analyzing inter-limb symmetry and angular trends of lower limb joints during walking. To this purpose, 26 obese individuals (mean age 28.5 years) and 26 normal-weight age- and sex-matched were tested using 3D gait analysis. Raw kinematic data were processed to derive joint-specific angle trends and angle-angle diagrams (synchronized cyclograms) which were characterized in terms of area, orientation and trend symmetry parameters. The results show that obese individuals exhibit a kinematic pattern which significantly differs from those of normal weight especially in the stance phase. In terms of inter-limb symmetry, higher values were found in obese individuals for all the considered parameters, even though the statistical significance was detected only in the case of trend symmetry index at ankle joint. The described alterations of gait kinematics in the obese individuals and especially the results on gait asymmetry are important, because the cyclic uneven movement repeated for hours daily can involve asymmetrical spine loading and cause lumbar pain and could be dangerous for overweight individuals.

Concurrent assessment of gait kinematics using marker-based and markerless motion capture

Kinematic analysis is a useful and widespread tool used in research and clinical biomechanics for the quantification of human movement. Common marker-based optical motion capture systems are time intensive and require highly trained operators to obtain kinematic data. Markerless motion capture systems offer an alternative method for the measurement of kinematic data with several practical benefits. This work compared the kinematics of human gait measured using a deep learning algorithm-based markerless motion capture system to those from a standard marker-based motion capture system. Thirty healthy adult participants walked on a treadmill while data were simultaneously recorded using eight video cameras and seven infrared optical motion capture cameras, providing synchronized markerless and marker-based data for comparison. The average root mean square distance (RMSD) between corresponding joint centers was less than 2.5 cm for all joints except the hip, which was 3.6 cm. Lower limb segment angles relative to the global coordinate system indicated the global segment pose estimates from both systems were very similar, with RMSD of less than 5.5° for all segment angles except those that represent rotations about the long axis of the segment. Lower limb joint angles captured similar patterns for flexion/extension at all joints, ab/adduction at the knee and hip, and toe-in/toe-out at the ankle. These findings indicate that the markerless system would be a suitable alternative technology in cases where the practical benefits of markerless data collection are preferred.

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.

Positional difference of malleoli-midpoint from three-dimensional geometric centre of rotation of ankle and its effect on ankle joint kinetics

BACKGROUNDS

Joint kinetic calculations are sensitive to joint centre locations. Although geometric hip and knee joint centre/axis are generally developed, the ankle joint centre (AJC) is conventionally defined as the midpoint between the malleolus lateralis and medialis (AJC_MID) in most gait analyses.

RESEARCH QUESTION

We examined the positional difference of the AJC_MID from the geometric centre of rotation (AJC_FUN) and its effect on the ankle joint kinetics in representative human gaits.

METHODS

In the first experiment, we calculated the AJC_FUN and indicated its location on the ankle MRI in 14 (seven male and seven female) participants. In the second experiment, we compared ankle kinematics/kinetics based on AJC_FUN and AJC_MID during walking and hopping at 2.6 Hz in 17 (nine male and eight female) participants.

RESULTS

In both experiments, AJC_FUN was located at positions significantly medial (-9.2 ± 5.4 mm and -10.1 ± 4.4 mm) and anterior (17.0 ± 7.4 mm and 15.3 ± 5.2 mm) from the AJC_MID. Furthermore, the AJC_MID underestimated peak dorsiflexion (AJC_MID/AJC_FUN: 52.6 ± 17.1%) and inversion (AJC_MID/AJC_FUN: 62.2 ± 11.5%) torques and their durations in walking. Additionally, AJC_MID overestimated the plantar flexion torque in both gait modes [AJC_MID/AJC_FUN: 111.3 ± 4.8% (walking) and 112.7 ± 6.3% (hopping)].

SIGNIFICANCE

We therefore concluded that the positional difference between the geometric and landmark-based AJC definitions significantly affected ankle kinetics, thereby indicating that the functional method should be used for defining AJC for gait analysis.

The effect of simulated marker misplacement on the interpretation of inter-limb differences during a change of direction task

The objective assessment of biomechanical asymmetries during movement tasks is used to monitor rehabilitation following anterior cruciate ligament reconstruction (ACLR). Marker placement is an important source of methodological variability within human motion analysis. It is currently unclear how marker placement error effects the interpretation of biomechanical asymmetries throughout post ACLR rehabilitation. The aim of this investigation was to determine the effect of random marker placement variation on the interpretation of inter-limb differences during a change of direction (CoD) task. Forty-seven participants 9 months post-ACLR and fifty uninjured controls completed a 90° CoD task on both limbs. Inter-limb differences in kinematic and kinetic metrics during the CoD stance phase were calculated for both groups using the Vicon Plug-in Gait model, and ACLR subjects were classified as having 'normal' or 'abnormal' inter-limb differences relative to the control group. Simulated random marker displacements based on published marker placement error ranges were then repeatedly applied to the lateral thigh, femoral epicondyle and tibia markers. ACLR inter-limb differences were recalculated each time, allowing the estimation of 95% confidence intervals and minimal identifiable between-session changes. ACLR subjects were also reclassified relative to the control group after each simulation and the percentage of participants to change classification was calculated. Marker displacements caused large deviations in inter-limb difference measures in several variables including hip rotation angle, knee abduction angle and knee abduction moment, thus limiting the ability to identify participants with large inter-limb differences relative to a control group. These findings highlight the challenges in using marker-based biomechanical models to conduct objective assessments of inter-limb differences during CoD tasks.

The Biomechanics of the Track and Field Sprint Start: A Narrative Review

The start from blocks is a fundamental component of all track and field sprint events (≤ 400 m). This narrative review focusses on biomechanical aspects of the block phase and the subsequent first flight and stance phases. We discuss specific features of technique and how they may be important for a high level of performance during the start. The need to appropriately quantify performance is discussed first; external power has recently become more frequently adopted because it provides a single measure that appropriately accounts for the requirement to increase horizontal velocity as much as possible in as little time as possible. In the “set” position, a relatively wide range of body configurations are adopted by sprinters irrespective of their ability level, and between-sprinter differences in these general positions do not appear to be directly associated with block phase performance. Greater average force production during the push against the blocks, especially from the rear leg and particularly the hip, appears to be important for performance. Immediately after exiting the blocks, shorter first flight durations and longer first stance durations (allowing more time to generate propulsive force) are found in sprinters of a higher performance level. During the first stance phase, the ankle and knee both appear to play an important role in energy generation, and higher levels of performance may be associated with a stiffer ankle joint and the ability to extend the knee throughout stance. However, the role of the sprinter’s body configuration at touchdown remains unclear, and the roles of strength and anatomy in these associations between technique and performance also remain largely unexplored. Other aspects such as the sex, age and performance level of the studied sprinters, as well as issues with measurement and comparisons with athletes with amputations, are also briefly considered.

A Normative Database of Hip and Knee Joint Biomechanics During Dynamic Tasks Using Four Functional Methods With Three Functional Calibration Tasks

Although predicted hip joint center (HJC) locations are known to vary widely between functional methods, no previous investigation has detailed functional method-dependent hip and knee biomechanics. The purpose of this study was to define a normative database of hip joint biomechanics during dynamic movements based upon functional HJC methods and calibration tasks. Thirty healthy young adults performed arc, star arc, and two-sided calibration tasks. Motion capture and ground reaction forces were collected during walking, running, and single-leg landings (SLLs). Two sphere-fit (geometric and algebraic) and two coordinate transformation techniques were implemented using each calibration (12 total method-calibration combinations). Surprisingly, the geometric fit-two-sided model placed the HJC at the midline of the pelvis and above the iliac spines, and thus was removed from analyses. A database of triplanar hip and knee kinematics and hip moments and powers was constructed using the mean of all subjects for the eleven method-calibration combinations. A nested analysis of variance approach compared calibration [method] peak hip kinematics and kinetics. Most method differences existed between geometric fit and coordinate transformations (58 of 84 total). No arc-star arc differences were found. Thirty-two differences were found between the two-sided and arc/star arc calibrations. This database of functional method based hip and knee biomechanics serves as an important reference point for interstudy comparisons. Overall, this study illustrates that functional HJC method can dramatically impact hip biomechanics and should be explicitly detailed in future work.

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.

Agreement between An Inertia and Optical Based Motion Capture during the VU-Return-to-Play- Field-Test

The validity of an inertial sensor-based motion capture system (IMC) has not been examined within the demands of a sports-specific field movement test. This study examined the validity of an IMC during a field test (VU®) by comparing it to an optical marker-based motion capture system (MMC). Expected accuracy and precision benchmarks were computed by comparing the outcomes of a linear and functional joint fitting model within the MMC. The kinematics from the IMC in sagittal plane demonstrated correlations (r²) between 0.76 and 0.98 with root mean square differences (RMSD) < 5°, only the knee bias was within the benchmark. In the frontal plane, r² ranged between 0.13 and 0.80 with RMSD < 10°, while the knee and hip bias was within the benchmark. For the transversal plane, r² ranged 0.11 to 0.93 with RMSD < 7°, while the ankle, knee and hip bias remained within the benchmark. The findings indicate that ankle kinematics are not interchangeable with MMC, that hip flexion and pelvis tilt higher in IMC than MMC, while other measures are comparable to MMC. Higher pelvis tilt/hip flexion in the IMC can be explained by a one sensor tilt estimation, while ankle kinematics demonstrated a considerable level of disagreement, which is likely due to four reasons: A one sensor estimation, sensor/marker attachment, movement artefacts of shoe sole and the ankle model used.

The sensitivity of joint kinematics and kinetics to marker placement during a change of direction task

The conventional gait model (CGM) refers to several closely related biomechanical models used in the objective analysis of human motion. Their use has become popular in the analysis of change of direction tasks to inform best practice in the prevention and rehabilitation of anterior cruciate ligament injury. As externally-placed markers define segment axes origins and orientations, kinematic and kinetic outputs from the CGM are sensitive to marker placement. The aim of this investigation was to quantify the sensitivity of lower extremity kinematics and knee moments to systematic differences in marker placement across the stance phase of a change of direction task. Systematic anterior/posterior displacements were applied to the lateral thigh, femoral epicondyle and tibia markers in software. One-dimensional statistical parametric mapping was used to determine the effect of marker placement across the entire stance phase of a 90° change of direction task. Marker placement error within previously reported inter-tester variability ranges caused significant differences in knee abduction moment, hip rotation angle, knee rotation angle, ankle abduction and rotation angle across various periods of stance. Discrete measures of these variables have been associated with increased frontal plane knee loading during change of direction, considered a key mechanism of anterior cruciate ligament injury. Systematic differences in marker placement may lead to incorrect group statistical inferences in such discrete measures.

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.

Effect of Two Different Pose Estimation Approaches on Lower Extremity Biomechanics in Professional Dancers

Different algorithms can be used to estimate the pose of musculoskeletal models in biomechanical studies. Visual 3D uses segment optimization whereas OpenSim uses global optimization. Thus, our purpose was to study whether the two approaches would influence the estimation of lower extremity biomechanical parameters. Marker trajectories and ground reaction forces of 6 professional dancers were collected during a single-leg forward jump-landing. The same data set was processed using both approaches. Our findings suggested that the sagittal knee and ankle angles and moments were highly comparable between the two approaches. The ankle sagittal angle and moment showed the lowest offset. On the other hand, the choice of a kinematic model was likely to affect the hip, more evident in the frontal and transverse planes. This may be due to different factors such as the pelvis and femur positions or larger amount of soft tissue in the thigh.

Anatomically-based skeletal coordinate systems for use with impact biomechanics data intended for anthropomorphic test device development

Post-mortem human subjects (PMHS) are frequently used to characterize biomechanical response and injury tolerance of humans to various types of loading by means of instrumentation installed directly on the skeleton. Data extracted from such tests are often used to develop and validate anthropomorphic test devices (ATDs), which function as human surrogates in tests for injury assessment. Given that the location and orientation of installed instrumentation differs between subjects, nominally similar measurements made on different PMHS must be transformed to standardized, skeletal-based local coordinate systems (LCS) before appropriate data comparisons can be made. Standardized PMHS LCS that correspond to ATD instrumentation locations and orientations have not previously been published. This paper introduces anatomically-defined PMHS LCS for body regions in which kinematic measurements are made using ATDs. These LCS include the head, sternum, single vertebrae, pelvis, femurs (distal and proximal), and tibiae (distal and proximal) based upon skeletal landmarks extracted from whole body CT scans. The proposed LCS provide a means to standardize the reporting of PMHS data, and facilitate both the comparison of PMHS impact data across institutions and the application of PMHS data to the development and validation of ATDs.

Lower back pain and healthy subjects exhibit distinct lower limb perturbation response strategies: A preliminary study

BACKGROUND

It is hypothesized that inherent differences in movement strategies exist between control subjects and those with a history of lower back pain (LBP). Previous motion analysis studies focus primarily on tracking spinal movements, neglecting the connection between the lower limbs and spinal function. Lack of knowledge surrounding the functional implications of LBP may explain the diversity in success from general treatments currently offered to LBP patients.

OBJECTIVE

This pilot study evaluated the response of healthy controls and individuals with a history of LBP (hLBP) to a postural disturbance.

METHODS

Volunteers (n= 26) were asked to maintain standing balance in response to repeated balance disturbances delivered via a perturbation platform while both kinematic and electromyographic data were recorded from the trunk, pelvis, and lower limb.

RESULTS

The healthy cohort utilized an upper body-focused strategy for balance control, with substantial activation of the external oblique muscles. The hLBP cohort implemented a lower limb-focused strategy, relying on activation of the semitendinosus and soleus muscles. No significant differences in joint range of motion were identified.

CONCLUSIONS

These findings suggest that particular reactive movement patterns may indicate muscular deficits in subjects with hLBP. Identification of these deficits may aid in developing specific rehabilitation programs to prevent future LBP recurrence.

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.

Influence of biomechanical models on joint kinematics and kinetics in baseball pitching

In baseball pitching, biomechanical parameters have been linked to ball velocity and potential injury risk. However, although the features of a biomechanical model have a significant influence on the kinematics and kinetics of a motion, this influence have not been assessed for pitching. The aim of this study was to evaluate the choice of the trunk and shoulder features, by comparing two models using the same input. The models differed in thoraco-humeral joint definition (moving or fixed with the thorax), joint centre estimation, values of the inertial parameters and computational framework. One professional pitcher participated in the study. We found that the different features of the biomechanical models have a substantial influence on the kinematics and kinetics of the pitchers. With a fixed thoraco-humeral joint the peak average thorax angular velocity was delayed and underestimated by 17% and the shoulder internal rotation velocity was overestimated by 7%. The use of a thoraco-humeral joint fixed to the thorax will lead to an overestimation of the rotational power at the shoulder and will neglect the power produced by the forward and upward translation of the shoulder girdle. These findings have direct implications for the interpretation of shoulder muscle contributions to the pitch.

Refining muscle geometry and wrapping in the TLEM 2 model for improved hip contact force prediction

Musculoskeletal models represent a powerful tool to gain knowledge on the internal forces acting at the joint level in a non-invasive way. However, these models can present some errors associated with the level of detail in their geometrical representation. For this reason, a thorough validation is necessary to prove the reliability of their predictions. This study documents the development of a generic musculoskeletal model and proposes a working logic and simulation techniques for identifying specific model features in need of refinement; as well as providing a quantitative validation for the prediction of hip contact forces (HCF). The model, implemented in the AnyBody Modeling System and based on the cadaveric dataset TLEM 2.0, was scaled to match the anthropometry of a patient fitted with an instrumented hip implant and to reproduce gait kinematics based on motion capture data. The relative contribution of individual muscle elements to the HCF and joint moments was analyzed to identify critical geometries, which were then compared to muscle magnetic resonance imaging (MRI) scans and, in case of inconsistencies, were modified to better match the volumetric scans. The predicted HCF showed good agreement with the overall trend and timing of the measured HCF from the instrumented prosthesis. The average root mean square error (RMSE), calculated for the total HCF was found to be 0.298*BW. Refining the geometries of the muscles thus identified reduced RMSE on HCF magnitudes by 17% (from 0.359*BW to 0.298*BW) over the whole gait cycle. The detailed study of individual muscle contributions to the HCF succeeded in identifying muscles with incorrect anatomy, which would have been difficult to intuitively identify otherwise. Despite a certain residual over-prediction of the final hip contact forces in the stance phase, a satisfactory level of geometrical accuracy of muscle paths has been achieved with the refinement of this model.

Is the reliability of 3D kinematics of young obese participants dependent on the hip joint center localization method used?

The aim of this study was to investigate if the test-retest reliability for three-dimensional (3D) gait kinematics in a young obese population is affected by using either a predictive (Davis) or a functional (SCoRE) hip joint center (HJC) localization approach. A secondary goal was to analyze how consistent both methods perform in estimating the HJC position. A convenience sample of ten participants, two females and eight males with an age-based body mass index (BMI) above the 97th percentile (mean±SD: 34.2±3.9kg/m²) was recruited. Participants underwent two 3D gait analysis sessions separated by a minimum of one day and a maximum of seven days. The standard error of measurement (SEM) and the root mean square error (RMSE) of key kinematic parameters along with the root mean square deviation (RMSD) of the entire waveforms were used to analyze the test-retest reliability. To get an estimate of the consistency of both HJC localization methods, the HJC positions determined by both methods were compared to each other. SEM, RMSE, and RMSD results indicate that the HJC position estimations between both methods are not different and demonstrate moderate to good reliability to estimate joint kinematics. With respect to the localization of the HJC, notable inconsistencies ranging from 0 to 5.4cm were observed. In conclusion, both approaches appear equally reliable. However, the inconsistent HJC estimation points out, that accuracy seems to be a big issue in these methods. Future research should attend to this matter.

Effects of hip joint centre mislocation on gait kinematics of children with cerebral palsy calculated using patient-specific direct and inverse kinematic models

Joint kinematics can be calculated by Direct Kinematics (DK), which is used in most clinical gait laboratories, or Inverse Kinematics (IK), which is mainly used for musculoskeletal research. In both approaches, joint centre locations are required to compute joint angles. The hip joint centre (HJC) in DK models can be estimated using predictive or functional methods, while in IK models can be obtained by scaling generic models. The aim of the current study was to systematically investigate the impact of HJC location errors on lower limb joint kinematics of a clinical population using DK and IK approaches. Subject-specific kinematic models of eight children with cerebral palsy were built from magnetic resonance images and used as reference models. HJC was then perturbed in 6mm steps within a 60mm cubic grid, and kinematic waveforms were calculated for the reference and perturbed models. HJC perturbations affected only hip and knee joint kinematics in a DK framework, but all joint angles were affected when using IK. In the DK model, joint constraints increased the sensitivity of joint range-of-motion to HJC location errors. Mean joint angle offsets larger than 5° were observed for both approaches (DK and IK), which were larger than previously reported for healthy adults. In the absence of medical images to identify the HJC, predictive or functional methods with small errors in anterior-posterior and medial-lateral directions and scaling procedures minimizing HJC location errors in the anterior-posterior direction should be chosen to minimize the impact on joint kinematics.

Methodological factors affecting joint moments estimation in clinical gait analysis: a systematic review

Quantitative gait analysis can provide a description of joint kinematics and dynamics, and it is recognized as a clinically useful tool for functional assessment, diagnosis and intervention planning. Clinically interpretable parameters are estimated from quantitative measures (i.e. ground reaction forces, skin marker trajectories, etc.) through biomechanical modelling. In particular, the estimation of joint moments during motion is grounded on several modelling assumptions: (1) body segmental and joint kinematics is derived from the trajectories of markers and by modelling the human body as a kinematic chain; (2) joint resultant (net) loads are, usually, derived from force plate measurements through a model of segmental dynamics. Therefore, both measurement errors and modelling assumptions can affect the results, to an extent that also depends on the characteristics of the motor task analysed (i.e. gait speed). Errors affecting the trajectories of joint centres, the orientation of joint functional axes, the joint angular velocities, the accuracy of inertial parameters and force measurements (concurring to the definition of the dynamic model), can weigh differently in the estimation of clinically interpretable joint moments. Numerous studies addressed all these methodological aspects separately, but a critical analysis of how these aspects may affect the clinical interpretation of joint dynamics is still missing. This article aims at filling this gap through a systematic review of the literature, conducted on Web of Science, Scopus and PubMed. The final objective is hence to provide clear take-home messages to guide laboratories in the estimation of joint moments for the clinical practice.

Predicting the location of the hip joint centres, impact of age group and sex

Clinical gait analysis incorporating three-dimensional motion analysis plays a key role in planning surgical treatments in people with gait disability. The position of the Hip Joint Centre (HJC) within the pelvis is thus critical to ensure accurate data interpretation. The position of the HJC is determined from regression equations based on anthropometric measurements derived from relatively small datasets. Current equations do not take sex or age into account, even though pelvis shape is known to differ between sex, and gait analysis is performed in populations with wide range of age. Three dimensional images of 157 deceased individuals (37 children, 120 skeletally matured) were collected with computed tomography. The location of the HJC within the pelvis was determined and regression equations to locate the HJC were developed using various anthropometrics predictors. We determined if accuracy improved when age and sex were introduced as variables. Statistical analysis did not support differentiating the equations according to sex. We found that age only modestly improved accuracy. We propose a range of new regression equations, derived from the largest dataset collected for this purpose to date.

In-vivo quantification of dynamic hip joint center errors and soft tissue artifact

Hip joint center (HJC) measurement error can adversely affect predictions from biomechanical models. Soft tissue artifact (STA) may exacerbate HJC errors during dynamic motions. We quantified HJC error and the effect of STA in 11 young, asymptomatic adults during six activities. Subjects were imaged simultaneously with reflective skin markers (SM) and dual fluoroscopy (DF), an x-ray based technique with submillimeter accuracy that does not suffer from STA. Five HJCs were defined from locations of SM using three predictive (i.e., based on regression) and two functional methods; these calculations were repeated using the DF solutions. Hip joint center motion was analyzed during six degrees-of-freedom (default) and three degrees-of-freedom hip joint kinematics. The position of the DF-measured femoral head center (FHC), served as the reference to calculate HJC error. The effect of STA was quantified with mean absolute deviation. HJC errors were (mean±SD) 16.6±8.4mm and 11.7±11.0mm using SM and DF solutions, respectively. HJC errors from SM measurements were all significantly different from the FHC in at least one anatomical direction during multiple activities. The mean absolute deviation of SM-based HJCs was 2.8±0.7mm, which was greater than that for the FHC (0.6±0.1mm), suggesting that STA caused approximately 2.2mm of spurious HJC motion. Constraining the hip joint to three degrees-of-freedom led to approximately 3.1mm of spurious HJC motion. Our results indicate that STA-induced motion of the HJC contributes to the overall error, but inaccuracies inherent with predictive and functional methods appear to be a larger source of error.