Comparison of Concurrent and Asynchronous Running Kinematics and Kinetics From Marker-Based and Markerless Motion Capture Under Varying Clothing Conditions.

As markerless motion capture is increasingly used to measure 3-dimensional human pose, it is important to understand how markerless results can be interpreted alongside historical marker-based data and how they are impacted by clothing. We compared concurrent running kinematics and kinetics between marker-based and markerless motion capture, and between 2 markerless clothing conditions. Thirty adults ran on an instrumented treadmill wearing motion capture clothing while concurrent marker-based and markerless data were recorded, and ran a second time wearing athletic clothing (shorts and t-shirt) while markerless data were recorded. Differences calculated between the concurrent signals from both systems, and also between each participant's mean signals from both asynchronous clothing conditions were summarized across all participants using root mean square differences. Most kinematic and kinetic signals were visually consistent between systems and markerless clothing conditions. Between systems, joint center positions differed by 3 cm or less, sagittal plane joint angles differed by 5° or less, and frontal and transverse plane angles differed by 5° to 10°. Joint moments differed by 0.3 N·m/kg or less between systems. Differences were sensitive to segment coordinate system definitions, highlighting the effects of these definitions when comparing against historical data or other motion capture modalities.

Prediction of Model Generated Patellofemoral Joint Contact Forces Using Principal Component Prediction and Reconstruction.

It is not currently possible to directly and noninvasively measure in vivo patellofemoral joint contact force during dynamic movement; therefore, indirect methods are required. Simple models may be inaccurate because patellofemoral contact forces vary for the same knee flexion angle, and the patellofemoral joint has substantial out-of-plane motion. More sophisticated models use 3-dimensional kinematics and kinetics coupled to a subject-specific anatomical model to predict contact forces; however, these models are time consuming and expensive. We applied a principal component analysis prediction and regression method to predict patellofemoral joint contact forces derived from a robust musculoskeletal model using exclusively optical motion capture kinematics (external approach), and with both patellofemoral and optical motion capture kinematics (internal approach). We tested this on a heterogeneous population of asymptomatic subjects (n = 8) during ground-level walking (n = 12). We developed equations that successfully capture subject-specific gait characteristics with the internal approach outperforming the external. These approaches were compared with a knee-flexion based model in literature (Brechter model). Both outperformed the Brechter model in interquartile range, limits of agreement, and the coefficient of determination. The equations generated by these approaches are less computationally demanding than a musculoskeletal model and may act as an effective tool in future rapid gait analysis and biofeedback applications.

Principal component analysis of whole-body kinematics using markerless motion capture during static balance tasks.

Balance tests have clinical utility in identifying balance deficits and supporting recommendations for appropriate treatments. Motion capture technology can be used to measure whole-body kinematics during balance tasks, but to date the high technical and financial costs have limited uptake of traditional marker-based motion capture systems for clinical applications. Markerless motion capture technology using standard video cameras has the potential to provide whole-body kinematic assessments with clinically accessible technology. Our aim was to quantify poses and movement strategies during static balance tasks (tandem stance, single limb stance, standing hip abduction, and quiet standing on foam with eyes closed) using video-based markerless motion capture software (Theia3D) and principal component analysis to examine the associations with age, body mass index (BMI) and sex. In 30 healthy adults, the mean poses for all balance tasks had at least one principal component (PC) that differed significantly by sex. Age was significantly associated with the PC describing leg height for the hip abduction task and erect posture for the quiet standing task. BMI was significantly associated with the PC capturing knee flexion in the single leg stance task. The movement strategies used to maintain balance showed significant differences by sex for the tandem stance pose. BMI was correlated with PCs for movement strategies for hip abduction and quiet standing tasks. Results from this study demonstrate how markerless motion capture technology could be used to augment analyses of balance both in the clinic and in the field.

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.

Influence of Articular Geometry and Tibial Tubercle Location on Patellofemoral Kinematics and Contact Mechanics.

Trochlear groove geometry and the location of the tibial tubercle, where the patellar tendon inserts, have both been associated with patellofemoral instability and can be modified surgically. Although their effects on patellofemoral biomechanics have been investigated individually, the interaction between the two is unclear. The authors' aim was to use statistical shape modeling and musculoskeletal simulation to examine the effect of patellofemoral geometry on the relationship between tibial tubercle location and patellofemoral function. A statistical shape model was used to generate new knee geometries with trochlear grooves ranging from shallow to deep. A Monte Carlo approach was used to create 750 knee models by randomly selecting a geometry and randomly translating the tibial tubercle medially/laterally and anteriorly. Each knee model was incorporated into a musculoskeletal model, and an overground walking trial was simulated. Knees with shallow trochlear geometry were more sensitive to tubercle medialization with greater changes in lateral patella position (-3.0 mm/cm medialization shallow vs -0.6 mm/cm deep) and cartilage contact pressure (-0.51 MPa/cm medialization shallow vs 0.04 MPa/cm deep). However, knees with deep trochlear geometry experienced greater increases in medial cartilage contact pressure with medialization. This modeling framework has the potential to aid in surgical decision making.

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.

Knee extension moment arm variations relate to mechanical function in walking and running.

The patellofemoral joint plays a crucial mechanical role during walking and running. It increases the knee extensor mechanism's moment arm and reduces the knee extension muscle forces required to generate the extension moment that supports body weight, prevents knee buckling and propels the centre of mass. However, the mechanical implications of moment arm variation caused by patellofemoral and tibiofemoral motion remain unclear. We used a data-driven musculoskeletal model with a 12-degree-of-freedom knee to simulate the knee extension moment arm during walking and running. Using a geometric method to calculate the moment arm, we found smaller moment arms during running than during walking in the swing phase. Overall, knee flexion causes differences between running and walking moment arms as increased flexion causes a posterior shift in the tibiofemoral rotation axis and patella articulation with the distal femur. Moment arms were also affected by knee motion direction and best predicted by separating by direction instead of across the entire gait cycle. Furthermore, we found high inter-subject variation in the moment arm that was largely explained by out-of-plane motion. Our results are consistent with the concept that shorter moment arms increase the effective mechanical advantage of the knee and may contribute to increased running velocity.

Inter-session repeatability of markerless motion capture gait kinematics.

The clinical uptake and influence of gait analysis has been hindered by inherent limitations of marker-based motion capture systems, which have long been the standard method for the collection of gait data including kinematics. Markerless motion capture offers an alternative method for the collection of gait kinematics that presents several practical benefits over marker-based systems. This work aimed to determine the reliability of lower limb gait kinematics from video based markerless motion capture using an established experimental protocol for testing reliability. Eight healthy adult participants performed three sessions of five over-ground walking trials in their own self-selected clothing, separated by an average of 8.5 days, while eight synchronized and calibrated cameras recorded video. Three-dimensional pose estimates from the video data were used to compute lower limb joint angles. Inter-session variability, inter-trial variability, and the variability ratio were used to assess the reliability of the gait kinematics. Compared to repeatability studies based on marker-based motion capture, inter-trial variability was slightly greater than previously reported for some angles, with an average across all joint angles of 2.5°. Inter-session variability was smaller on average than all previously reported values, with an average across all joint angles of 2.8°. Variability ratios were all smaller than those previously reported with an average of 1.1, indicating that the multi-session protocol increased the total variability of joint angles by 10% of the inter-trial variability. These results indicate that gait kinematics can be reliably measured using markerless motion capture.

Assessment of spatiotemporal gait parameters using a deep learning algorithm-based markerless motion capture system.

Spatiotemporal parameters can characterize the gait patterns of individuals, allowing assessment of their health status and detection of clinically meaningful changes in their gait. Video-based markerless motion capture is a user-friendly, inexpensive, and widely applicable technology that could reduce the barriers to measuring spatiotemporal gait parameters in clinical and more diverse settings. Two studies were performed to determine whether gait parameters measured using markerless motion capture demonstrate concurrent validity with those measured using marker-based motion capture and a pressure-sensitive gait mat. For the first study, thirty healthy young adults performed treadmill gait at self-selected speeds while marker-based motion capture and synchronized video data were recorded simultaneously. For the second study, twenty-five healthy young adults performed over-ground gait at self-selected speeds while footfalls were recorded using a gait mat and synchronized video data were recorded simultaneously. Kinematic heel-strike and toe-off gait events were used to identify the same gait cycles between systems. Nine spatiotemporal gait parameters were measured by each system and directly compared between systems. Measurements were compared using Bland-Altman methods, mean differences, Pearson correlation coefficients, and intraclass correlation coefficients. The results indicate that markerless measurements of spatiotemporal gait parameters have good to excellent agreement with marker-based motion capture and gait mat systems, except for stance time and double limb support time relative to both systems and stride width relative to the gait mat. These findings indicate that markerless motion capture can adequately measure spatiotemporal gait parameters of healthy young adults during treadmill and over-ground gait.

A comparison of centre of pressure behaviour and ground reaction force magnitudes when individuals walk overground and on an instrumented treadmill.

BACKGROUND: Instrumented treadmills facilitate analysis of consecutive strides in ways that typical overground gait data collections cannot. Researchers have quantified differences between joint kinetic measures whilst walking on an instrumented treadmill compared to those walking overground. The reason for such differences has not yet been established. RESEARCH QUESTION: Can we identify the source or sources of these errors by comparing centre of pressure and ground reaction force measurements recorded on a treadmill to those collected overground? METHODS: Kinematic and kinetic data were recorded while nineteen individuals walked continuously at their self-selected walking speed overground and on a treadmill. Comparisons of the centre of pressure and ground reaction forces were made between the two conditions using 2-tailed paired t-tests and Cohen's d effect size. RESULTS: The results indicated that participants had significantly faster backwards, lateral and medial centre of pressure velocities when walking on a treadmill compared to when they were walking overground. Additionally, participants also had significantly reduced peak propulsive ground reaction forces when walking on a treadmill than walking overground. SIGNIFICANCE: These results suggest that shear forces caused by the belts sliding over the treadmill force platforms affect the centre of pressure during early stance, and the minimal acceleration of a participant's centre of mass during treadmill walking results in reduced propulsive force during late stance. Therefore, care should be taken during studies when comparing kinetic gait variables between overground and treadmill walking.

Relationship Between Lateral Patellar Stability and Tibial Tubercle Location for Varying Patellofemoral Geometries.

The geometry of the patellofemoral joint affects function and pathology. However, the impact of trochlear groove depth on treatments for patellar instability and pain is not clear. Tibial tubercle osteotomy is a common surgical intervention for patellar instability where the tibial insertion of the patellar tendon (PT) is translated to align the extensor mechanism and stabilize the joint. The aim of this work was to investigate the interaction between trochlear groove depth and PT insertion and their effect on patellar stability. Patellofemoral geometry was modified based on a statistical shape model to create knees with a range of trochlear groove depths. A Monte Carlo approach was used and 750 instances of a musculoskeletal model were generated with varying geometry and anterior and medial transfer of the PT. Stability was assessed by applying a lateral perturbation force to the patella during simulation of overground walking. In knees with deep trochlear grooves, a medialized PT increased stability. However, in knees with shallow trochlear grooves, stability was maximized for tendon insertion ∼1 mm medial to its neutral location. This PT insertion also corresponded to the best alignment of the patella in the trochlear groove in these knees, indicating that good alignment may be important to maximizing stability. Anterior PT transfer had minimal effect on stability for all geometries. A better understanding of the effects of articular geometry and tubercle location on stability may aid clinicians in patient-specific surgical planning.

Contributions of muscles and external forces to medial knee load reduction due to osteoarthritis braces.

BACKGROUND: Braces for medial knee osteoarthritis can reduce medial joint loads through a combination of three mechanisms: application of an external brace abduction moment, alteration of gait dynamics, and reduced activation of antagonistic muscles. Although the effect of knee bracing has been reported independently for each of these parameters, no previous study has quantified their relative contributions to reducing medial knee loads. METHODS: In this study, we used a detailed musculoskeletal model to investigate immediate changes in medial and lateral loads caused by two different knee braces: OA Assist and OA Adjuster 3 (DJO Global). Seventeen osteoarthritis subjects and eighteen healthy controls performed overground gait trials in unbraced and braced conditions. RESULTS: Across all subjects, bracing reduced medial loads by 0.1 to 0.3 times bodyweight (BW), or roughly 10%, and increased lateral loads by 0.03 to 0.2 BW. Changes in gait kinematics due to bracing were subtle, and had little effect on medial and lateral joint loads. The knee adduction moment was unaltered unless the brace moment was included in its computation. Only one muscle, biceps femoris, showed a significant change in EMG with bracing, but this did not contribute to altered peak medial contact loads. CONCLUSIONS: Knee braces reduced medial tibiofemoral loads primarily by applying a direct, and substantial, abduction moment to each subject's knee. To further enhance brace effectiveness, future brace designs should seek to enhance the magnitude of this unloader moment, and possibly exploit additional kinematic or neuromuscular gait modifications.

The effect of articular geometry features identified using statistical shape modelling on knee biomechanics.

Articular geometry in the knee varies widely among people which has implications for risk of injury and pathology. The goals of this work were to develop a framework to systematically vary geometry in a multibody knee model and to use this framework to investigate the effect of morphological features on dynamic knee kinematics and contact mechanics. A statistical shape model of the tibiofemoral and patellofemoral joints was created from magnetic resonance images of 14 asymptomatic knees. The shape model was then used to generate 37 unique multibody knee models based on -3 to +3 standard deviations of the scores for the first six principal components identified. Each multibody model was then incorporated into a lower extremity musculoskeletal model and the Concurrent Optimization of Muscle Activations and Kinematics (COMAK) routine was used to simulate knee mechanics for overground walking. Changes in articular geometry affected knee function, resulting in differences up to 17° in orientation, 8 mm in translation, 0.7 BW in contact force, and 2.0 MPa in mean cartilage contact pressure. Understanding the relationship between shape and function in a joint could provide insight into the mechanisms behind injury and pathology and the variability in response to treatment.

Self-Selected walking speed increases when individuals are aware of being recorded.

BACKGROUND: Typical gait data collections consist of discrete walking trials where participants are aware when data are being recorded. Anecdotally, some investigators have reported that participants often walk differently between trials or before or after data collection compared to when they know they are being recorded. In addition, walking speed, which affects a number of gait variables, is known to be different when individuals complete discrete and continuous walking trials. RESEARCH QUESTION: The purpose of this study was to determine whether changes in walking speed occurred as a result of participants being aware, versus unaware that data were being recorded, during both discrete and continuous walking trials. METHODS: Kinematic data were collected for twenty two individuals walking continuous trials or discrete trials, while they were both aware and unaware of being recorded. Comparisons of walking speeds were made between groups (continuous walking; discrete trials) and awareness of being recorded (aware; unaware) using a two way ANOVA. RESULTS: The results indicated that participants walked significantly faster during discrete trials when they were aware that data were being recorded compared to when they were unaware. However, when they walked continuously their walking speed was not affected by their awareness. SIGNIFICANCE: The results suggest that awareness of data collection, and the type of protocol used during data collection, affect an individual's walking speed during gait analysis. Therefore, care should be taken when determining gait analysis protocols where variables are sensitive to walking speeds.

Validation of method for analysing mechanics of unloader brace for medial knee osteoarthritis.

Unloader braces are one non-invasive treatment of knee osteoarthritis, which primarily function by applying an external abduction moment to the joint to reduce loads in the medial compartment of the knee. We developed a novel method using brace deflection to estimate the mechanical effect of valgus braces and validated this model using strain gauge instrumentation. Three subjects performed static and walking trials, in which the moment applied by an instrumented brace was calculated using the deflection and strain methods. The deflection method predicted average brace moments of 8.7 Nm across static trials; mean error between the deflection model predictions and the gold-standard strain gauge measurements was 0.32 Nm. Mean brace moment predictions throughout gait ranged from 7.1 to 8.7 Nm using the deflection model. Maximum differences (MAE) over the gait cycle in mean and peak brace moments between methods were 1.50 Nm (0.96) and 0.60 Nm (0.42). Our proposed method enables quantification of brace abduction moments without the use of custom instrumentation. While the deflection-based method is similar to that implemented by Schmalz et al. (2010), the proposed method isolates abduction deflection from the 3 DOF angular changes that occur within the brace. Though the model should be viewed with more caution during swing (MAE = 1.16 Nm), it was shown that the accuracy is influenced by the uncertainty in angle measurement due to cluster spacing. In conclusion, the results demonstrate that the deflection-based method developed can predict comparable brace moments to those of the previously established strain method.

Prediction of Knee Joint Contact Forces From External Measures Using Principal Component Prediction and Reconstruction.

Abnormal loading of the knee joint contributes to the pathogenesis of knee osteoarthritis. Gait retraining is a noninvasive intervention that aims to reduce knee loads by providing audible, visual, or haptic feedback of gait parameters. The computational expense of joint contact force prediction has limited real-time feedback to surrogate measures of the contact force, such as the knee adduction moment. We developed a method to predict knee joint contact forces using motion analysis and a statistical regression model that can be implemented in near real-time. Gait waveform variables were deconstructed using principal component analysis, and a linear regression was used to predict the principal component scores of the contact force waveforms. Knee joint contact force waveforms were reconstructed using the predicted scores. We tested our method using a heterogenous population of asymptomatic controls and subjects with knee osteoarthritis. The reconstructed contact force waveforms had mean (SD) root mean square differences of 0.17 (0.05) bodyweight compared with the contact forces predicted by a musculoskeletal model. Our method successfully predicted subject-specific shape features of contact force waveforms and is a potentially powerful tool in biofeedback and clinical gait analysis.

Identification of good candidates for valgus bracing as a treatment for medial knee osteoarthritis.

Valgus unloader braces are a conservative treatment option for medial compartment knee osteoarthritis that aim to unload the damaged medial compartment through application of an external abduction moment. Patient response to bracing is highly variable, however. While some experience improvements in pain, function, and joint loading, others receive little to no benefit. The objective of this work was to analyze clinical measures and biomechanical characteristics of unbraced walking to identify variables that are associated with the mechanical effectiveness of valgus unloader bracing. Seventeen patients with medial knee osteoarthritis walked overground with and without a valgus unloader brace. A musculoskeletal model was used to estimate the contact forces in the medial compartment of the tibiofemoral joint and brace effectiveness was defined as the decrease in peak medial contact force between unbraced and braced conditions. Stepwise linear regression was used to identify clinical and biomechanical measures that predicted brace effectiveness. The final regression model explained 77% of the variance in brace effectiveness using two variables. Bracing was more effective for those with greater peak external hip adduction moments and for those with higher Kellgren-Lawrence grades, indicating more severe radiographic osteoarthritis. The hip adduction moment was the best predictor of brace effectiveness and was well correlated with several other measures indicating that it may be functioning as a "biomarker" for good bracing candidates. CLINICAL SIGNIFICANCE: The ability to predict good candidates for valgus bracing may improve issues of patient compliance and could enable the ability to train patients to respond better to bracing. © 2017 Orthopaedic Research Society. Published by Wiley Periodicals, Inc. J Orthop Res 36:351-356, 2018.

Operator Bias Errors Are Reduced Using Standing Marker Alignment Device for Repeated Visit Studies.

When optical motion capture is used for motion analysis, reflective markers or a digitizer are typically used to record the location of anatomical landmarks identified through palpation. The landmarks are then used to construct anatomical coordinate systems. Failure to consistently identify landmarks through palpation over repeat tests creates artifacts in the kinematic waveforms. The purpose of this work was to improve intra- and inter-rater reliability in determining lower limb anatomical landmarks and the associated anatomical coordinate systems using a marker alignment device (MAD). The device aids the subject in recreating the same standing posture over multiple tests, and recreates the anatomical landmarks from previous static calibration trials. We tested three different raters who identified landmarks on eleven subjects. The subjects performed walking trials and their gait kinematics were analyzed with and without the device. Ankle kinematics were not improved by the device suggesting manual palpation over repeat visits is just as effective as the MAD. Intra-class correlation coefficients between gait kinematics registered to the reference static trial and registered to follow-up static trials with and without the device were improved between 1% and 33% when the device was used. Importantly, out-of-plane hip and knee kinematics showed the greatest improvements in repeatability. These results suggest that the device is well suited to reducing palpation artifact during repeat visits to the gait lab.