Impact of Quadriceps Tendon Graft Thickness on Electromechanical Delay and Neuromuscular Performance After ACL Reconstruction.

Background: Both partial- and full-thickness quadriceps tendon (QT) graft harvests are used for anterior cruciate ligament reconstruction (ACLR). Purpose: To evaluate the impact of QT graft harvest depth (full or partial thickness) on electromechanical delay (EMD), peak torque (PT), and rate of torque development (RTD) after ACLR. Study Design: Controlled laboratory study. Methods: A total of 26 patients who underwent either partial-thickness (n = 14) or full-thickness (n = 12) autograft QT ACLR were recruited between June and November 2021 (>1 year before participation). Patients performed isokinetic knee extension testing with surface electromyography of the quadriceps muscles. Mixed repeated-measures analysis of variance with least significant difference post hoc testing was used to determine significant differences (mean difference [MD] ± SE) or interactions for all variables. Results: A significant speed×depth interaction was seen for the vastus medialis (P = .005). Pairwise analyses showed significantly longer EMD for the partial-thickness graft than the full-thickness graft (MD ± SE, 19.92 ± 6.33 ms; P = .006). In the partial-thickness graft, the EMD was significantly longer at 90 deg/s versus 180 deg/s (MD ± SE, 19.11 ± 3.95 ms; P < .001) and 300 deg/s (MD ± SE, 16.43 ± 5.30 ms; P = .006). For PT, the full-thickness graft had a significantly lower PT on the operated versus nonoperated side at all speeds (MD ± SE: 90 deg/s, -57.0 ± 10.5 N·m, P < .001; 180 deg/s, -26.0 ± 10.2 N·m, P = .020; 300 deg/s, -20.3 ± 8.9 N·m, P = .034). For RTD, the full-thickness graft showed significantly Slower RTD for the operated versus nonoperated side at all time points (MD ± SD: RTD0-25 (0-25% of the range of motion), -131.3 ± 50.9 N·m/s, P = .018; RTD25-50, -197.0 ± 72.5 N·m/s, P = .014; RTD50-75, -113.3 ± 39.8 N·m/s, P = .013; RTD75-100, -149.4 ± 35.9 N·m/s, P < .001). Conclusion: Compared with partial-thickness QT, full-thickness QT showed a shorter vastus medialis EMD at higher loading, and therefore greater stiffness, as well as slower RTD and lower PT across all testing speeds. Clinical Relevance: The impact of full-thickness QT autograft on EMD and neuromuscular performance should be considered for ACLR.

A comparison of three-dimensional kinematics between markerless and marker-based motion capture in overground gait.

Vision-based methods using RGB inputs for human pose estimation have grown in recent years but have undergone limited testing in clinical and biomechanics research areas like gait analysis. The purpose of the present study was to compare lower extremity kinematics during overground gait between a traditional marker-based approach and a commercial multi-view markerless system in a sample of subjects including young adults, older adults, and adults diagnosed with Parkinson's disease. A convenience sample of 35 adults between the age of 18-85 years were included in this study, yielding a total of 114 trials and 228 gait cycles that were compared between systems. A total of 30 time normalized waveforms, including three-dimensional joint centers, segment angles, and joint angles were compared between systems using root mean-squared error (RMSE), range of motion difference (ΔROM), Pearson correlation coefficients (r), and interclass correlation coefficients (ICC). RMSEs for joint center positions were less than 28 mm in all joints with correlations indicating good to excellent agreement. RMSEs for segment and joint angles were in range of previous results, with highest agreement between systems in the sagittal plane. ΔROM differences were within reference values that characterize clinical groups like Parkinson's disease, stroke, or knee osteoarthritis. Further improvements in pelvis tracking, markerless keypoint model definitions, and standardization of comparison study protocols are needed. Nevertheless, markerless solutions seem promising toward unrestricted motion analysis in biomechanics research and clinical settings.

Prediction of gait kinetics using Markerless-driven musculoskeletal modeling.

Video-based motion analysis systems are emerging in the biomechanics research community, yet there is limited exploration of kinetics prediction using RGB-markerless kinematics and musculoskeletal modeling. This project aimed to provide ground reaction force (GRF) and ground reaction moment (GRM) predictions during over-ground gait by introducing RGB-markerless kinematics into a musculoskeletal modeling framework. Full-body markerless kinematic inputs and musculoskeletal modeling were used to obtain GRF and GRM predictions which were compared to measured force plate values. The markerless-driven predictions yielded average root mean-squared error (RMSE) in the stance phase of 0.035 ± 0.009 N∙BW-1, 0.070 ± 0.014 N∙BW-1, and 0.155 ± 0.041 N∙BW-1 in the mediolateral (ML), anteroposterior (AP), and vertical (V) GRFs. This was accompanied by moderate to high correlations and interclass correlation coefficients (ICC) indicating moderate to good agreement between measured and predicted values (95% Confidence Inervals: ML = [0.479, 0.717], AP = [0.714, 0.856], V = [0.803, 0.905]). For ground reaction moments (GRM), average RMSE was 0.029 ± 0.013 Nm∙BWH-1, 0.014 ± 0.005 Nm∙BWH-1, and 0.005 ± 0.002 Nm∙BWH-1 in the sagittal, frontal, and transverse planes. Pearson correlations and ICCs indicated poor agreement between systems for GRMs (95% Confidence Intervals: Sagittal = [0.314, 0.608], Frontal = [0.006, 0.373], Transverse = [0.269, 0.570]). Currently, RMSE is larger than target thresholds set from studies using Kinect, inertial, or marker-based kinematic drivers; but methodological considerations highlighted in this work may help guide follow-up iterations. At this point, further use in research or clinical practice is cautioned until methodological considerations are addressed, although results are promising at this point.

Validity of artificial intelligence-based markerless motion capture system for clinical gait analysis: Spatiotemporal results in healthy adults and adults with Parkinson's disease.

Markerless motion capture methods are continuously in development to target limitations encountered in marker-, sensor-, or depth-based systems. Previous evaluation of the KinaTrax markerless system was limited by differences in model definitions, gait event methods, and a homogenous subject sample. The purpose of this work was to evaluate the accuracy of spatiotemporal parameters in the markerless system with an updated markerless model, coordinate- and velocity-based gait events, and subjects representing young adult, older adult, and Parkinson's disease groups. Fifty-seven subjects and 216 trials were included in this analysis. Interclass correlation coefficients showed excellent agreement between the markerless system and a marker-based reference system for all spatial parameters. Temporal variables were similar, except swing time which showed good agreement. Concordance correlation coefficients were similar with all but swing time showing moderate to almost perfect concordance. Bland-Altman bias and limits of agreement (LOA) were small and improved from previous evaluations. Parameters showed similar agreement across coordinate- and velocity-based gait methods with the latter showing generally smaller LOAs. Improvements in spatiotemporal parameters in the present evaluation was due to inclusion of keypoints at the calcanei in the markerless model. Consistency in the calcanei keypoints relative to heel marker placements may improve results further. Similar to previous work, LOAs are within boundaries to detect differences in clinical groups. Results support the use of the markerless system for estimation of spatiotemporal parameters across age and clinical groups, but caution should be taken when generalizing findings due to remaining error in kinematic gait event methods.

The Associations Between Quadriceps Tendon Graft Thickness and Isokinetic Performance.

BACKGROUND: Anterior cruciate ligament reconstruction (ACLR) using the quadriceps tendon is an increasingly popular technique. Both partial-thickness quadriceps tendon (PT-Q) and full-thickness quadriceps tendon (FT-Q) graft depths are employed. HYPOTHESIS/PURPOSE: This study was designed to assess isokinetic peak torque, average power, and total work during knee extension in patients with FT-Q or PT-Q grafts for ACLR. We hypothesized that both groups would show lower isokinetic values for the operated side, with greater deficits in the FT-Q group than in the PT-Q group. STUDY DESIGN: Cohort study; Level of evidence, 3. METHODS: A total of 26 patients who underwent ACLR with either an FT-Q or PT-Q graft were recruited between June 2021 and November 2021. Patients underwent isokinetic knee extension testing at > 1 year after surgery. Mixed repeated-measures analysis of covariance with least square difference post hoc testing was used to determine significant differences or interactions for all variables. RESULTS: Peak torque was significantly lower for the operated limb than the nonoperated limb in the FT-Q group (mean difference [MD] ± standard error [SE], -38.6 ± 8.3 Ncm [95% CI, -55.7 to -21.5 Ncm]; P < .001; d = 0.90) but not in the PT-Q group (MD ± SE, -7.3 ± 7.7 Ncm [95% CI, -23.2 to 8.5 Ncm]; P = .348; d = 0.20). Similarly, average power for the operated limb was lower than that for the nonoperated limb in the FT-Q group (MD ± SE, -53.6 ± 13.4 W [95% CI, -81.3 to -26.9 W]; P < .001; d = 0.88) but not in the PT-Q group (MD ± SE, -4.1 ± 12.4 W [95% CI, -29.8 to 21.5 W]; P = .742; d = 0.07), and total work was lower for the operated limb compared with the nonoperated limb in the FT-Q group (MD ± SE, -118.2 ± 27.1 J [95% CI, -174.3 to -62.2 J]; P < .001; d = 0.96) but not in the PT-Q group (MD ± SE, -18.3 ± 25.1 J [95% CI, -70.2 to 33.6 J]; P = .472; d = 0.15). CONCLUSION: The FT-Q group showed significant deficits in the operated limb compared with the nonoperated limb for all isokinetic variables. In contrast, no significant differences were found between the nonoperated and operated limbs for the PT-Q group.

Concurrent validity of artificial intelligence-based markerless motion capture for over-ground gait analysis: A study of spatiotemporal parameters.

Gait analysis is used in research and clinical environments; yet several limitations exist in current methodologies. Markerless systems, utilizing high-speed video and artificial intelligence, eliminate most limitations encountered in marker-, depth-, or inertial sensor-based systems; however, further development is needed to improve their utility and accessibility in practice. Spatiotemporal parameters from 22 young adults were estimated during over-ground gait. Nine parameters were calculated using events determined from force plate information combined with foot segment tracking and from motion of the foot relative to the sacrum using marker-based and markerless tracking. Two-way mixed effects, single measurement, absolute agreement and relative consistency interclass correlation coefficients, Bland-Altman bias and limits of agreement, and Lin's concordance correlations were used to examine the validity of parameters from markerless tracking compared to parameters calculated from gait event methods using force plates and marker-based tracking. Gait speed, stride length, step length, cycle time, and step time from the markerless system all showed strong agreement with the force plate method. Other markerless-determined parameters were not as accurate. Differences in stride width are attributable to inconsistencies in foot segment definitions between models; while differences in stance time, swing time, and double limb support time were influenced by gait event methods. Mean differences in gait parameters were smaller than meaningful clinical differences in Parkinson's disease patients and within ranges of reference values for elderly subjects. Further studies are needed to determine the validity across other patient groups, but results support the continued development of markerless systems for over-ground gait analysis.

Monitoring joint mechanics in anterior cruciate ligament reconstruction using depth sensor-driven musculoskeletal modeling and statistical parametric mapping.

The incidence of anterior cruciate ligament injury and reconstruction (ACLR) may set the stage for the development of early onset osteoarthritis in these patients. Development of accessible quantitative motion capture methodologies for recurrent monitoring of knee joint loading during daily activities following ACLR is necessary. This study aimed to compare lower extremity kinetics between ACLR affected limbs, ACLR unaffected limbs, and dominant limbs of healthy control subjects during over-ground gait and stair ascent using a single depth sensor-driven musculoskeletal modeling approach. No meaningful differences were found between groups during over-ground gait in any kinetic variables. When subjected to a stair ascent task, both ACLR limbs showed greater hip extension and internal rotation moments compared to control subjects at approximately 72-79% stance. This was coincident with greater knee flexion moments in both ALCR limbs compared to control. The absence of differences during over-ground gait but presence of compensatory strategies during stair ascent, suggests task dependent recovery in this cohort who were tested at least 1-year following surgery. Importantly, this was determined using a portable low-cost motion capture method which may be attractive to professionals in sports medicine for recurrent monitoring following ACLR.

Ground reaction force and joint moment estimation during gait using an Azure Kinect-driven musculoskeletal modeling approach.

BACKGROUND: Gait analysis is burdened by time and equipment costs, interpretation, and accessibility of three-dimensional motion analysis systems. Evidence suggests growing adoption of gait testing in the shift toward evidence-based medicine. Further developments addressing these barriers will aid its efficacy in clinical practice. Previous research aiming to develop gait analysis systems for kinetics estimation using the Kinect V2 have provided promising results yet modified approaches using the latest hardware may further aid kinetics estimation accuracy RESEARCH QUESTION: Can a single Azure Kinect sensor combined with a musculoskeletal modeling approach provide kinetics estimations during gait similar to those obtained from marker-based systems with embedded force platforms? METHODS: Ten subjects were recruited to perform three walking trials at their normal speed. Trials were recorded using an eight-camera optoelectronic system with two embedded force plates and a single Azure Kinect sensor. Marker and depth data were both used to drive a musculoskeletal model using the AnyBody Modeling System. Predicted kinetics from the Azure Kinect-driven model, including ground reaction force (GRF) and joint moments, were compared to measured values using root meansquared error (RMSE), normalized RMSE, Pearson correlation, concordance correlation, and statistical parametric mapping RESULTS: High to very high correlations were observed for anteroposterior GRF (ρ = 0.889), vertical GRF (ρ = 0.940), and sagittal hip (ρ = 0.805) and ankle (ρ = 0.876) moments. RMSEs were 1.2 ± 2.2 (%BW), 3.2 ± 5.7 (%BW), 0.7 ± 0.1.3 (%BWH), and 0.6 ± 1.0 (%BWH) SIGNIFICANCE: The proposed approach using the Azure Kinect provided higher accuracy compared to previous studies using the Kinect V2 potentially due to improved foot tracking by the Azure Kinect. Future studies should seek to optimize ground contact parameters and focus on regions of error between predicted and measured kinetics highlighted currently for further improvements in kinetic estimations.

Estimation of ground reaction forces during stair climbing in patients with ACL reconstruction using a depth sensor-driven musculoskeletal model.

BACKGROUND: Although stair ambulation should be included in the rehabilitation of the long-term effects of ACL injury on knee function, the assessment of kinetic parameter in the situation where stair gait can only be established using costly and cumbersome force platforms via conventional inverse dynamic analysis. Therefore, there is a need to develop a practical laboratory setup as an assessment tool of the stair gait abnormalities in lower extremity that arise from an ACL deficiency. RESEARCH QUESTION: Can the use of a single depth sensor-driven full-body musculoskeletal gait model be considered an accurate assessment tool of the ground reaction forces (GRFs) during stair climbing for patients following ACL reconstruction (ACLR) surgery? METHODS: A total of 15 patients who underwent ACLR participated in this study. GRFs data during stair climbing was collected using a custom-built 3-step staircase with two embedded force platforms. A single depth sensor, commercially available and cost effective, was used to obtain participants' depth map information to extract the full-body skeleton information. The AnyBody TM GaitFullBody model was utilized to estimate GRFs attained by 25 artificial muscle-like actuators placed under each foot. Mean differences between the measured and estimated GRFs were compared using paired samples t-tests. The ensemble curves of the GRFs were compared between both approaches during stance phase of the gait cycle. RESULTS: The findings of this study showed that the estimation of the GRFs produced during staircase gait using a depth sensor-driven musculoskeletal model can produce acceptable results when compared to the traditional inverse dynamics modelling approach as an alternative tool in clinical settings for individuals who had undergone ACLR. SIGNIFICANCE: The introduced approach of full-body musculoskeletal modelling driven by a single depth sensor has the potential to be a cost-effective stair gait analysis tool for patients with ACL injury.