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

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).

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.

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.

Collapse

Key Words

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

Collapse

MESH Headings

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

Collapse

Grants Collapse

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.

Collapse

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.