The Conventional Gait Model’s sensitivity to lower-limb marker placement

Effect of uncertainties in musculoskeletal modeling inputs on sensitivity of knee joint finite element simulations

Musculoskeletal finite element modeling is used to estimate mechanical responses of knee joint tissues but involves uncertainties in muscle activations, marker locations, cartilage stiffness, maximum isometric forces, and gait parameter personalization. This study investigates how these uncertainties affect cartilage mechanical responses in knee joint finite element models during walking. We selected three subjects and constructed five musculoskeletal models for each, representing different variations of modeling assumptions, along with a reference model using conventional assumptions. We then ran finite element simulations of knee joints using both personalized gait inputs (motion and loading boundary conditions) and non-personalized gait inputs from literature. Our results demonstrated that varying modeling assumptions, such as optimization function for muscle activation patterns, knee marker position, knee cartilage stiffness, and maximum isometric force, produced highly subject-specific effects. Differences between the reference and altered models ranged from 3% to 30% in musculoskeletal modeling and from 1% to 61% in finite element modeling results. The largest effects occurred with non-personalized gait data, resulting in up to 6- and 2-fold changes in musculoskeletal and finite element modeling results, respectively. This study highlights the sensitivity of knee mechanics to different modeling assumptions and underscores the importance of applying personalized gait parameters for accurate finite element simulations.

Maintained gait in persons with arthrogryposis from childhood to adulthood

BACKGROUND

Individuals with arthrogryposis multiplex congenita (AMC) exhibit a range of modes of ambulation, from walking independently to requiring a wheelchair. Presence of joint contractures and muscle strength plays a crucial role, and, in some patients, orthoses are necessary to facilitate or enable walking.

METHODS

Gait was assessed with a three-dimensional (3D) gait analysis, calculated as a gait deviation index (GDI) of nine kinematic variables, and compared between childhood and adulthood.

RESULTS

A total of 12 persons, 8 with community and 4 with household ambulation, who had undergone a 3D gait analysis in childhood (CH) and as an adult (follow-up, FU) at the same gait laboratory were enrolled in the study. At the FU, three, five, and four participants respectively were categorized based on need of joint stabilization while walking as AMC1 using knee-ankle-orthoses (KAFOs) with locked knee joints, AMC2 using KAFOs with free-articulating knee joint or ankle-foot-orthoses (AFOs) and AMC3 using insoles or shoes. Two participants in AMC2 had changed from AFOs to insoles or shoes between CH and FU. There were no differences in joint contractures between the AMC groups at CH or FU. Two participants had orthopaedic surgery between CH and FU. The GDI of the leg with the lowest GDI score at CH vs FU was median [min, max] 55.67 [41.79, 65.14] vs 48.4 [42.67, 56.30] (p = 1.000) in AMC1, 81.25 [59.42, 84.12] vs 68.96 [47.68, 70.33] (p = 0.043) in AMC2, and 73.15 [43.94, 91.72] vs 73.46 [50.82, 75.24] (p = 1.000) in AMC3. Time and distance parameters of cadence, walking speed, step length, and step width did not differ between the CH and FU, nor were there differences in satisfaction with the device or the service at the FU.

CONCLUSION

A difference in the GDI was found in one of the AMC groups between childhood and adulthood that could not be explained by factors such as contractures or muscle strength. This study reflects that gait is maintained in ambulating persons with AMC who were offered an orthosis program that has been available from childhood into adulthood.

The effects of contralateral limb cross-education training on post-surgical rehabilitation outcomes in patients with anterior cruciate ligament reconstruction: a randomized controlled trial

OBJECTIVE

This study examines whether cross-education training of the healthy limb promotes cross-transfer through central nervous system stimulation, enhancing the function, kinematic parameters, dynamic balance, and plantar pressure of the affected knee joint in patients recovering from postoperative anterior cruciate ligament reconstruction (ACLR).

METHODS

Forty anterior cruciate ligament reconstruction (ACLR) patients, 5-6 weeks postoperatively, were included and randomly assigned to either an experimental group (n = 20) or a control group (n = 20). The experimental group participated in six weeks of cross-education (CE) training in addition to conventional rehabilitation, while the control group received only conventional rehabilitation. Assessment outcomes included knee function (Lysholm score, joint mobility, and surface electromyographic characteristics of the rectus femoris muscle), kinematic parameters (stride length, stride speed, and stride width), dynamic balance (gait line length, single-support line length, and medial-lateral displacements), and plantar pressure (forefoot, midfoot, and hindfoot pressures). The effect of CE training on postoperative ACLR rehabilitation was comprehensively assessed by comparing the pre- and post-intervention changes within each group and the differences between the groups.

RESULTS

Before the intervention, no statistically significant differences were observed between the two groups across all measured parameters (P > 0.05). Following the intervention, significant improvements in knee function, kinematic parameters, balance function, and plantar pressure were observed in both groups, with the experimental group showing significantly more significant improvements (P < 0.05). The Lysholm score, range of motion (ROM), and surface electromyographic activity of the rectus femoris muscle were significantly higher in the experimental group compared to the control group (P < 0.01). Among kinematic parameters, the experimental group demonstrated a significant increase in stride length and reduced stride width, whereas differences in stride speed were not statistically significant (P > 0.05). Regarding balance function, the experimental group exhibited significantly longer gait and single-support line lengths, significantly reducing medial-lateral displacement (P < 0.05). Analysis of plantar pressure revealed significant improvements in forefoot and hindfoot pressures in the experimental group, with a particularly notable increase in hindfoot pressure (P < 0.05). However, changes in midfoot pressure were not statistically significant (P > 0.05).

CONCLUSION

CE training markedly enhanced knee function, kinematic metrics, dynamic stability, and plantar pressure in postoperative ACLR patients providing initial evidence for the prospective utilization of CE theory in rehabilitation. Nonetheless, the fundamental mechanics of its effects remain ambiguous, and variables such as individual differences and neuromuscular adaptation processes may affect training results. Future studies should examine its long-term impacts and uncover potential neuromuscular pathways to establish a solid scientific basis for improving postoperative rehabilitation procedures.

Cumulative loading increases and loading asymmetries persist during walking for people with a transfemoral bone-anchored limb

BACKGROUND

A bone-anchored limb (BAL) is an alternative to a traditional socket-type prosthesis for people with transfemoral amputation. Early laboratory-based evidence suggests improvement in joint and limb loading mechanics during walking with a BAL compared to socket prosthesis use. However, changes in cumulative joint and limb loading measures, which may be predictive of degenerative joint disease progression, remain unknown.

RESEARCH QUESTION

Do cumulative total limb and hip joint loading during walking change using a BAL for people with unilateral transfemoral amputation, compared to prior socket prosthesis use?

METHODS

A case-series cohort of eight participants with prior unilateral transfemoral amputation who underwent BAL hardware implantation surgery were retrospectively analyzed (4 M/4 F; BMI: 27.7 ± 3.1 kg/m2; age: 50.4 ± 10.2 years). Daily step count and whole-body motion capture data were collected before (using socket prosthesis) and one-year after BAL hardware implantation. Cumulative total limb and hip joint loading and between-limb loading symmetry metrics were calculated during overground walking at both time points and compared using Cohen's d effect sizes.

RESULTS

One year after BAL hardware implantation, participants demonstrated bilateral increases in cumulative total limb loading (amputated: d = -0.65; intact: d = -0.72) and frontal-plane hip moment (amputated: d = -1.29; intact: d = -1.68). Total limb loading and hip joint loading in all planes remained asymmetric over time, with relative overloading of the intact limb in all variables of interest at the one-year point.

SIGNIFICANCE

Despite increases in cumulative total limb and hip joint loading, between-limb loading asymmetries persist. Habitual loading asymmetry has been implicated in contributing to negative long-term joint health and onset or progression of degenerative joint diseases. Improved understanding of methods to address habitual loading asymmetries is needed to optimize rehabilitation and long-term joint health as people with transfemoral amputation increase physical activity when using a BAL.

Reconstruction of proximal hamstring ruptures restores joint biomechanics during various walking conditions

PURPOSE

We aimed to examine the functional outcome in different walking conditions in elderly adults who underwent surgical repair after a non-contact hamstring injury. Our objective was to compare lower limb kinematics and kinetics over the entire gait cycle between the injured and contralateral leg in overground and level and uphill treadmill walking.

METHODS

12 patients (mean ± SD, age: 65 ± 9 years; body mass index: 30 ± 6 kg/m2) walked at self-selected speed in overground (0% slope) and treadmill conditions (0% and 10% slope). We measured spatiotemporal parameters, joint angles (normalised to gait cycle) and joint moments (normalised to stance phase) of the hip, knee and ankle. Data between sides were compared using paired sample t-tests (p < 0.05) and continuous 95% confidence intervals of the paired difference between trajectories.

RESULTS

Patients walked at an average speed of 1.31 ± 0.26 m/second overground and 0.92 ± 0.31 m/second on the treadmill. Spatiotemporal parameters were comparable between the injured and contralateral leg (p > 0.05). Joint kinematic and joint kinetic trajectories were comparable between sides for all walking conditions.

CONCLUSIONS

Refixation of the proximal hamstring tendons resulted in comparable ambulatory mechanics at least 1 year after surgery in the injured leg and the contralateral leg, which were all within the range of normative values reported in the literature. These results complement our previous findings on hamstring repair in terms of clinical outcomes and muscle strength and support that surgical repair achieves good functional outcomes in terms of ambulation in an elderly population.

TRIAL REGISTRATION

clinicaltrials.gov (NCT04867746).

On the reliability of single-camera markerless systems for overground gait monitoring

BACKGROUND AND OBJECTIVE

Motion analysis is crucial for effective and timely rehabilitative interventions on people with motor disorders. Conventional marker-based (MB) gait analysis is highly time-consuming and calls for expensive equipment, dedicated facilities and personnel. Markerless (ML) systems may pave the way to less demanding gait monitoring, also in unsupervised environments (i.e., in telemedicine). However,scepticism on clinical usability of relevant outcome measures has hampered its use. ML is normally used to analyse treadmill walking, which is significantly different from the more physiological overground walking. This study aims to provide end-users with instructions on using a single-camera markerless system to obtain reliable motion data from overground walking, while clinicians will be instructed on the reliability of obtained quantities.

METHODS

The study compares kinematics obtained from ML systems to those concurrently obtained from marker-based systems, considering different stride counts and subject positioning within the capture volume.

RESULTS

The findings suggest that five straight walking trials are sufficient for collecting reliable kinematics with ML systems. Precision on joint kinematics decreased at the boundary of the capture volume. Excellent correlation was found between ML and MB systems for hip and knee angles (0.92

CONCLUSION

Single-camera markerless motion capture systems have great potential in assessing human joint kinematics during overground walking. Clinicians can confidently rely on estimated joint kinematics while walking, enabling personalized interventions and improving accessibility to remote evaluation and rehabilitation services, as long as: (i) the camera is positioned to capture someone walking back and forth at least five times with good visibility of the entire body silhouette; (ii) the walking path is at least 2 m long; and (iii) images captured at the boundaries of the camera image plane should be discarded.

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Key Words

• Clinical evaluation
• Human joint kinematics
• Human pose estimation
• Motion analysis
• Reference data
• Telemedicine

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MESH Headings

• Humans
• Gait Analysis
• Reproducibility of Results
• Gait/physiology
• Walking/physiology
• Knee Joint/physiology
• Biomechanical Phenomena

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Affiliation(s)

Michele Boldo Department of Computer Science, University of Verona, Strada Le Grazie, 15, Verona, 37134, Italy.
Roberto Di Marco Department of Engineering for Innovation Medicine, University of Verona, Strada Le Grazie, 15, Verona, 37134, Italy.
Enrico Martini Department of Computer Science, University of Verona, Strada Le Grazie, 15, Verona, 37134, Italy.
Mauro Nardon Department of Neurosciences, Biomedicine and Movement Sciences, University of Verona, Via Casorati, 43, Verona, 37131, Italy.
Matteo Bertucco Department of Neurosciences, Biomedicine and Movement Sciences, University of Verona, Via Casorati, 43, Verona, 37131, Italy.
Nicola Bombieri Department of Engineering for Innovation Medicine, University of Verona, Strada Le Grazie, 15, Verona, 37134, Italy.

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Gait kinematics based on inertial measurement units with the sensor-to-segment calibration and multibody optimization adapted to the patient's motor capacities, a pilot study

INTRODUCTION

Inertial Measurement Units (IMUs) offer a promising alternative to optoelectronic systems to obtain joint lower-limb kinematics during gait. However, the associated methodologies, such as sensor-to-segment (S2S) calibration and multibody optimization, have been developed mainly for, and tested on, asymptomatic subjects.

RESEARCH QUESTION

This study proposes to evaluate two personalizations of the methodology used to obtain lower-body kinematics from IMUs with pathological subjects: S2S calibration and multibody optimization.

METHODS

Based on previous studies, two decision trees were developed to select the best (in terms of accuracy and repeatability) S2S methods to be performed by the patient given his/her abilities. The multibody optimization was personalized by limiting the kinematic chain range of motion to the results of the subject's clinical examination. These two propositions were tested on 12 patients with various gait deficits. The patients were equipped with IMUs and reflective markers tracked by an optoelectronic system. They had to perform the postures and movements selected by the decision trees then walk back and forth along a walkway. Gait kinematics obtained from the IMUs directly (referred to as Direct kinematics), and after multibody optimization performed via the OpenSim software using the generic range of motion (referred to as Generic Optimized kinematics), and using the personalized range of motion (referred to as Personalized Optimized kinematics) were compared to those obtained with the Conventional Gait Model through Root Mean Square Errors (RMSE), Correlation Coefficients (CC) and Range of Motion differences (ΔROM).

RESULTS

The RMSEs were smaller than 8.1° in the sagittal plane but greater than 7.4° in the transverse plane. The CCs, between 0.71 and 0.99 in the sagittal plane, deteriorate sharply in the frontal and transverse planes where they only measured between 0.15 and 0.68. The ΔROMs were mostly below 8.3°. Optimized kinematics did not improve compared to Direct kinematics.

SIGNIFICANCE

The personalization of the proposed S2S calibration method showed encouraging results, whereas multibody optimization did not impact the resulting joint kinematics.

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

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

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

BACKGROUND

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

RESEARCH QUESTION

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

METHODS

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

RESULTS

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

SIGNIFICANCE

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

Towards Single Camera Human 3D-Kinematics

Markerless estimation of 3D Kinematics has the great potential to clinically diagnose and monitor movement disorders without referrals to expensive motion capture labs; however, current approaches are limited by performing multiple de-coupled steps to estimate the kinematics of a person from videos. Most current techniques work in a multi-step approach by first detecting the pose of the body and then fitting a musculoskeletal model to the data for accurate kinematic estimation. Errors in training data of the pose detection algorithms, model scaling, as well the requirement of multiple cameras limit the use of these techniques in a clinical setting. Our goal is to pave the way toward fast, easily applicable and accurate 3D kinematic estimation. To this end, we propose a novel approach for direct 3D human kinematic estimation D3KE from videos using deep neural networks. Our experiments demonstrate that the proposed end-to-end training is robust and outperforms 2D and 3D markerless motion capture based kinematic estimation pipelines in terms of joint angles error by a large margin (35% from 5.44 to 3.54 degrees). We show that D3KE is superior to the multi-step approach and can run at video framerate speeds. This technology shows the potential for clinical analysis from mobile devices in the future.