Effect of the soft tissue artifact on marker measurements and on the calculation of the helical axis of the knee during a gait cycle: A study on the CAMS-Knee data set

A Method to Track 3D Knee Kinematics by Multi-Channel 3D-Tracked A-Mode Ultrasound

This paper introduces a method for measuring 3D tibiofemoral kinematics using a multi-channel A-mode ultrasound system under dynamic conditions. The proposed system consists of a multi-channel A-mode ultrasound system integrated with a conventional motion capture system (i.e., optical tracking system). This approach allows for the non-invasive and non-radiative quantification of the tibiofemoral joint's six degrees of freedom (DOF). We demonstrated the feasibility and accuracy of this method in the cadaveric experiment. The knee joint's motions were mimicked by manually manipulating the leg through multiple motion cycles from flexion to extension. To measure it, six custom ultrasound holders, equipped with a total of 30 A-mode ultrasound transducers and 18 optical markers, were mounted on various anatomical regions of the lower extremity of the specimen. During experiments, 3D-tracked intra-cortical bone pins were inserted into the femur and tibia to measure the ground truth of tibiofemoral kinematics. The results were compared with the tibiofemoral kinematics derived from the proposed ultrasound system. The results showed an average rotational error of 1.51 ± 1.13° and a translational error of 3.14 ± 1.72 mm for the ultrasound-derived kinematics, compared to the ground truth. In conclusion, this multi-channel A-mode ultrasound system demonstrated a great potential of effectively measuring tibiofemoral kinematics during dynamic motions. Its improved accuracy, nature of non-invasiveness, and lack of radiation exposure make this method a promising alternative to incorporate into gait analysis and prosthetic kinematic measurements later.

Does IMU redundancy improve multi-body optimization results to obtain lower-body kinematics? A preliminary study says no

Inertial Measurement Units (IMUs) have been proposed as an ecological alternative to optoelectronic systems for obtaining human body joint kinematics. Tremendous work has been done to reduce differences between kinematics obtained with IMUs and optoelectronic systems, by improving sensor-to-segment calibration, fusion algorithms, and by using Multibody Kinematics Optimization (MKO). However, these improvements seem to reach a barrier, particularly on transverse and frontal planes. Inspired by marker-based MKO approach performed via OpenSim, this study proposes to test whether IMU redundancy with MKO could improve lower-limb kinematics obtained from IMUs. For this study, five subjects were equipped with 11 IMUs and 30 reflective markers tracked by 18 optoelectronic cameras. They then performed gait, cycling, and running actions. Four different lower-limb kinematics were computed: one kinematics based on markers after MKO, one kinematics based on IMUs without MKO, and two based on IMUs after MKO performed with OpenSense (one with, and one without, sensor redundancy). Kinematics were compared via Root Mean Square Difference and correlation coefficients to kinematics based on markers after MKO. Results showed that redundancy does not reduce differences with the kinematics based on markers after MKO on frontal and transverse planes comparatively to classic IMU MKO. Sensor redundancy does not seem to impact lower-limb kinematics on frontal and transverse planes, due to the likelihood of the "rigid component" of soft-tissue artefact impacting all sensors located on one segment.

A portable system to measure knee extensor spasticity after spinal cord injury

BACKGROUND

The pendulum test is a quantitative method used to assess knee extensor spasticity in humans with spinal cord injury (SCI). Yet, the clinical implementation of this method remains limited. The goal of our study was to develop an objective and portable system to assess knee extensor spasticity during the pendulum test using inertial measurement units (IMU).

METHODS

Spasticity was quantified by measuring the first swing angle (FSA) using a 3-dimensional optical tracking system (with external markers over the iliotibial band, lateral knee epicondyle, and lateral malleolus) and two wireless IMUs (positioned over the iliotibial band and mid-part of the lower leg) as well as a clinical exam (Modified Ashworth Scale, MAS).

RESULTS

Measurements were taken on separate days to assess test-retest reliability and device agreement in humans with and without SCI. We found no differences between FSA values obtained with the optical tracking system and the IMU-based system in control subjects and individuals with SCI. FSA values from the IMU-based system showed excellent agreement with the optical tracking system in individuals with SCI (ICC > 0.98) and good agreement in controls (ICC > 0.82), excellent test-retest reliability across days in SCI (ICC = 0.93) and good in controls (ICC = 0.87). Notably, FSA values measured by both systems showed a strong association with MAS scores ( ρ  ~ -0.8) being decreased in individuals with SCI with higher MAS scores, reflecting the presence of spasticity.

CONCLUSIONS

These findings suggest that our new portable IMU-based system provides a robust and flexible alternative to a camera-based optical tracking system to quantify knee extensor spasticity following SCI.

Comparison of markerless and marker-based motion capture systems using 95% functional limits of agreement in a linear mixed-effects modelling framework

Biomechanics analysis of human movement has been proven useful for maintenance of health, injury prevention, and rehabilitation in both sports and clinical populations. A marker-based motion capture system is considered the gold standard method of measurement for three dimensional kinematics measurements. However, the application of markers to anatomical bony points is a time consuming process and constrained by inter-, intra-tester and session reliability issues. The emergence of novel markerless motion capture systems without the use of reflective markers is a rapidly growing field in motion analysis. However an assessment of the level of agreement of a markerless system with an established gold standard marker-based system is needed to ensure the applicability of a markerless system. An extra layer of complexity is involved as the kinematics measurements are functional responses. In this paper a new approach is proposed to generate 95% functional limits of agreement (fLoA) using the linear mixed-effects modelling framework for hierarchical study designs. This approach is attractive as it will allow practitioners to extend their use of linear mixed models to assess agreement in method comparison studies in all domains where functional responses are recorded.

Assessment of an IMU-Based Experimental Set-Up for Upper Limb Motion in Obese Subjects

In recent years, wearable systems based on inertial sensors opened new perspectives for functional motor assessment with respect to the gold standard motion capture systems. The aim of this study was to validate an experimental set-up based on 17 body-worn inertial sensors (Awinda, Xsens, The Netherlands), addressing specific body segments with respect to the state-of-the art system (VICON, Oxford Metrics Ltd., Oxford, UK) to assess upper limb kinematics in obese, with respect to healthy subjects. Twenty-three obese and thirty healthy weight individuals were simultaneously acquainted with the two systems across a set of three tasks for upper limbs (i.e., frontal arm rise, lateral arm rise, and reaching). Root Mean Square error (RMSE) was computed to quantify the differences between the measurements provided by the systems in terms of range of motion (ROM), whilst their agreement was assessed via Pearson's correlation coefficient (PCC) and Bland-Altman (BA) plots. In addition, the signal waveforms were compared via one-dimensional statistical parametrical mapping (SPM) based on a paired t-test and a two-way ANOVA was applied on ROMs. The overall results partially confirmed the correlation and the agreement between the two systems, reporting only a moderate correlation for shoulder principal rotation angle in each task (r~0.40) and for elbow/flexion extension in obese subjects (r = 0.66), whilst no correlation was found for most non-principal rotation angles (r < 0.40). Across the performed tasks, an average RMSE of 34° and 26° was reported in obese and healthy controls, respectively. At the current state, the presence of bias limits the applicability of the inertial-based system in clinics; further research is intended in this context.

A simulation study to investigate an extension to the point cluster technique

Joint kinematics are an important and widely utilized metric in quantitative human movement analysis. Typically, trajectory data for skin-mounted markers are collected using stereophotogrammetry, sometimes referred to as optical motion capture, and processed using various mathematical models to estimate joint kinematics (e.g., angles). Among the various sources of noise in optical motion capture data, soft tissue artifacts (STAs) remain a critical source of error. This study investigates the performance of the point cluster technique (PCT), an extension of the PCT using perturbation theory (PCT-PT), and singular value decomposition least squares (SVD-LS) method (as a reference) for 100 different marker configurations on the thigh and shank during treadmill walking. This study provides additional evidence that the PCT method is significantly limited by the underlying mathematical constraints governing its optimization process. Furthermore, the results suggest the PCT-PT method outperforms the PCT method across all performance metrics for both body segments during the entire gait cycle. For position-based metrics, the PCT-PT method provides better estimates than the SVD-LS method for the thigh during majority of the stance phase and provides comparable estimates for the shank during the entire gait cycle. For knee angle estimates, the PCT-PT method provides equivalent results as the SVD-LS method.

Whole body mass estimates and error propagation in countermovement jump: a simulated error study

High-velocity actions are central to clinical and athletic performance, with jumping used to assess outcomes in sports medicine. Ground reaction force (GRF)-based methods are the standard for computing jump characteristics, but require mass estimation and GRF integration, potentially resulting in mass errors which influence outcomes. This study investigated how simulated mass errors influenced the centre of mass (CoM) trajectory during a countermovement jump. The mass was estimated from the static GRF, and simulated errors were added or subtracted to the mass. The CoM trajectory with simulated mass errors was computed using the GRF-based method to investigate mass mis-estimation's influence on jump height. A regression model indicated that, for a 1 kg mass change, there was a 7.7 cm jump height change, and the jump height differed by 11.5 ± 0.4 cm from the maximum to minimum error. A 2-way ANOVA identified significant height differences between the starting position, and landing, or final position with mass errors of ± 0.2 or ± 0.4 kg. These results reveal that small mass errors may produce inaccurate conclusions regarding performance changes, and that errors may propagate throughout the jump trajectory. Caution may be necessary when using GRF-based methods to compute jump height as a power proxy.

Eight weeks of a lower limb resistance training protocol and gait performance in patients with symptomatic mild to moderate knee osteoarthritis

BACKGROUND

The role of strengthening the lower limbs to optimize the biomechanics of the hip, knee and ankle during walking in patients with knee osteoarthritis, is still unclear. This study aimed to analyse the walking biomechanics of individuals with symptomatic mild to moderate knee osteoarthritis before and after a simplified lower limb resistance training protocol, focused on knee joint exercises with individualized load.

METHODS

Forty-one patients with symptomatic and radiographic mild to moderate knee osteoarthritis underwent 3D gait analysis pre-post 8 weeks lower limb resistance training protocol performed 3 times a week. Parameters investigated were spatiotemporal, sagittal range of motion, flexion and extension minimum and maximum values, power and moment of hip, knee and ankle, as well as self-reported pain and physical function by the Western Ontario MacMaster University Osteoarthritis Index. Paired t test, Wilcoxon, Spearman's correlation and a logistic model were used for statistical analysis, with p < 0.05. Pain improvement more than 2 points was considered clinically relevant. The effect size (ES) was calculated using Cohen's d.

RESULTS

Post protocol walking speed increased 6.7% (ES: 0.711), cadence 3.7% (ES: 0.655), stride length 2.6% (ES: 0.542), and double support time reduced 6.9% (ES:0.459). It was also observed a significant increase in one maximum repetition test for legpress 46%, knee extension 23% and knee flexion chair 27% (p < 0.001). Patients reported a 62.5% reduction in pain (ES:1.518) and 64.9% improvement in physical function (ES:1.376). 82% of the patients presented more than 2 points improvement in pain. No evidence of strong correlations between pain, strength gains and gait parameters were found.

CONCLUSIONS

There was a significant and clinical improvement of spatiotemporal gait parameters, pain, physical function, and strength after 8-week lower limb resistance training protocol. Patients who had a clinically relevant pain improvement presented better gait performance.

Inter-Device Reliability of a Three-Dimensional Markerless Motion Capture System Quantifying Elementary Movement Patterns in Humans

With advancements in technology able to quantify wide-ranging features of human movement, the aim of the present study was to investigate the inter-device technological reliability of a three-dimensional markerless motion capture system (3D-MCS), quantifying different movement tasks. A total of 20 healthy individuals performed a test battery consisting of 29 different movements, from which 214 different metrics were derived. Two 3D-MCS located in close proximity were utilized to quantify movement characteristics. Independent sample t-tests with selected reliability statistics (i.e., intraclass correlation coefficient (ICC), effect sizes, and mean absolute differences) were used to evaluate the agreement between the two systems. The study results suggested that 95.7% of all metrics analyzed revealed negligible or small between-device effect sizes. Further, 91.6% of all metrics analyzed showed moderate or better agreement when looking at the ICC values, while 32.2% of all metrics showed excellent agreement. For metrics measuring joint angles (198 metrics), the mean difference between systems was 2.9 degrees, while for metrics investigating distance measures (16 metrics; e.g., center of mass depth), the mean difference between systems was 0.62 cm. Caution is advised when trying to generalize the study findings beyond the specific technology and software used in this investigation. Given the technological reliability reported in this study, as well as the logistical and time-related limitations associated with marker-based motion capture systems, it may be suggested that 3D-MCS present practitioners with an opportunity to reliably and efficiently measure the movement characteristics of patients and athletes. This has implications for monitoring the health/performance of a broad range of populations.

Peak Tibiofemoral Contact Forces Estimated Using IMU-Based Approaches Are Not Significantly Different from Motion Capture-Based Estimations in Patients with Knee Osteoarthritis

Altered tibiofemoral contact forces represent a risk factor for osteoarthritis onset and progression, making optimization of the knee force distribution a target of treatment strategies. Musculoskeletal model-based simulations are a state-of-the-art method to estimate joint contact forces, but they typically require laboratory-based input and skilled operators. To overcome these limitations, ambulatory methods, relying on inertial measurement units, have been proposed to estimated ground reaction forces and, consequently, knee contact forces out-of-the-lab. This study proposes the use of a full inertial-capture-based musculoskeletal modelling workflow with an underlying probabilistic principal component analysis model trained on 1787 gait cycles in patients with knee osteoarthritis. As validation, five patients with knee osteoarthritis were instrumented with 17 inertial measurement units and 76 opto-reflective markers. Participants performed multiple overground walking trials while motion and inertial capture methods were synchronously recorded. Moderate to strong correlations were found for the inertial capture-based knee contact forces compared to motion capture with root mean square error between 0.15 and 0.40 of body weight. The results show that our workflow can inform and potentially assist clinical practitioners to monitor knee joint loading in physical therapy sessions and eventually assess long-term therapeutic effects in a clinical context.

Differences in angular kinematics when using thigh, implant, or medial knee markers in osseointegrated transfemoral prosthetic gait

BACKGROUND

The Helen Hayes anatomical model is commonly used in clinical gait analysis with standard medial/lateral knee and thigh markers.

METHODS

To quantify soft-tissue artifacts associated with the thigh marker following osseointegration surgery, we added an "implant marker" on the implant extending from the femur, with the objective of identifying the differences in the angular kinematics when using the standard versus implant marker. One female adult with an osseointegrated transfemoral prosthesis walked overground for three trials, and common kinematic measures were calculated from motion capture data.

FINDINGS

The results indicated that, when using the thigh marker, a peak of knee varus occurred during the swing phase on the prosthetic side, which is unusual during gait and not feasible for hinge joint prostheses. When using the implant marker, knee varus/valgus was closer to normative. Using the thigh marker, the results showed an internal hip rotation at the start of stance and during the mid and terminal swing phases. In contrast, external hip rotation occurred in both stance and swing phases using the implant marker. Moreover, when selecting the medial knee marker instead of the thigh marker, the angular kinematics and range of motion of knee varus/valgus and hip rotation were comparable to those for the implant marker.

INTERPRETATION

This finding suggests that when studying osseointegration gait, using an implant marker will result in more accurate femoral and knee joint motion than using the thigh marker. Changing the selection of markers can reduce the errors of knee varus/valgus and hip kinematics in osseointegrated transfemoral prosthetic gait.

A novel method for in vivo measurement of dynamic ischiofemoral space based on MRI and motion capture

Purpose: To use a novel in vivo method to simulate a moving hip model. Then, measure the dynamic bone-to-bone distance, and analyze the ischiofemoral space (IFS) of patients diagnosed with ischiofemoral impingement syndrome (IFI) during dynamic activities. Methods: Nine healthy subjects and 9 patients with IFI were recruited to collect MRI images and motion capture data. The motion trail of the hip during motion capture was matched to a personalized 3D hip model reconstructed from MRI images to get a dynamic bone model. This personalized dynamic in vivo method was then used to simulate the bone motion in dynamic activities. Validation was conducted on a 3D-printed sphere by comparing the calculated data using this novel method with the actual measured moving data using motion capture. Moreover, the novel method was used to analyze the in vivo dynamic IFS between healthy subjects and IFI patients during normal and long stride walking. Results: The validation results show that the root mean square error (RMSE) of slide and rotation was 1.42 mm/1.84° and 1.58 mm/2.19°, respectively. During normal walking, the in vivo dynamic IFS was significantly larger in healthy hips (ranged between 15.09 and 50.24 mm) compared with affected hips (between 10.16 and 39.74 mm) in 40.27%-83.81% of the gait cycle (p = 0.027). During long stride walking, the in vivo dynamic IFS was also significantly larger in healthy hips (ranged between 13.02 and 51.99 mm) than affected hips (between 9.63 and 44.22 mm) in 0%-5.85% of the gait cycle (p = 0.049). Additionally, the IFS of normal walking was significantly smaller than long stride walking during 0%-14.05% and 85.07%-100% of the gait cycle (p = 0.033, 0.033) in healthy hips. However, there was no difference between the two methods of walking among the patients. Conclusions: This study established a novel in vivo method to measure the dynamic bone-to-bone distance and was well validated. This method was used to measure the IFS of patients diagnosed with IFI, and the results showed that the IFS of patients is smaller compared with healthy subjects, whether in normal or long stride walking. Meanwhile, IFI eliminated the difference between normal and long stride walking.

A Framework for Analytical Validation of Inertial-Sensor-Based Knee Kinematics Using a Six-Degrees-of-Freedom Joint Simulator

The success of kinematic analysis that relies on inertial measurement units (IMUs) heavily depends on the performance of the underlying algorithms. Quantifying the level of uncertainty associated with the models and approximations implemented within these algorithms, without the complication of soft-tissue artefact, is therefore critical. To this end, this study aimed to assess the rotational errors associated with controlled movements. Here, data of six total knee arthroplasty patients from a previously published fluoroscopy study were used to simulate realistic kinematics of daily activities using IMUs mounted to a six-degrees-of-freedom joint simulator. A model-based method involving extended Kalman filtering to derive rotational kinematics from inertial measurements was tested and compared against the ground truth simulator values. The algorithm demonstrated excellent accuracy (root-mean-square error ≤0.9°, maximum absolute error ≤3.2°) in estimating three-dimensional rotational knee kinematics during level walking. Although maximum absolute errors linked to stair descent and sit-to-stand-to-sit rose to 5.2° and 10.8°, respectively, root-mean-square errors peaked at 1.9° and 7.5°. This study hereby describes an accurate framework for evaluating the suitability of the underlying kinematic models and assumptions of an IMU-based motion analysis system, facilitating the future validation of analogous tools.

A Novel Procedure for Knee Flexion Angle Estimation Based on Functionally Defined Coordinate Systems and Independent of the Marker Landmarks

Knee angles are kinematic quantities that are commonly presented in gait analysis reports. They are typically calculated as the relative angles between the anatomical coordinate systems rigidly attached to the femur and the tibia. To give these angles a biomechanical meaning, the coordinate systems must be defined with respect to some anatomical landmarks. For example, if one axis of the joint coordinate systems is directed along the knee flexion/extension axis, then the relative angle assumes the meaning of flexion/extension angle. Defining accurate anatomical coordinate systems is not an easy task, because it requires skills in marker placement, landmark identification and definition of a biomechanical model. In this paper, we present a novel method to (i) functionally define two coordinate systems attached to femur and tibia and (ii) functionally calculate the knee angle based on the relative differential kinematics between the previously defined coordinate systems. As the main limitation, this method is unable to provide an absolute measurement of the knee flexion/extension angle; however, it is able to accurately capture and display the relative angular motion of the knee. We show that our method produced consistent results even when the measured coordinate systems were randomly modified, removing any anatomical referencing. The proposed method has the advantage of being independent/invariant of the choice of the original coordinate systems of the femur and tibia, removing the need for accurate marker placement. Some major consequences are that (i) the markers may be placed on optimal landmarks, for example, minimizing the soft tissue artifacts or improving the subject's comfort, and (ii) there is no need for anatomical calibration when technical marker clusters/triads are used.

Effect of the soft tissue artifact on marker measurements and on the calculation of the helical axis of the knee during a squat movement: A study on the CAMS-Knee dataset

BACKGROUND

Marker-based motion capture recordings of human body segments are often affected by soft tissue artifact (STA). The undesired and uncontrolled motion of the skin may introduce errors in the estimation of motion and position of body segments and, consequently, in the calculation of the relative functional quantities.

METHODS

This study exploited a recently published dataset consisting of six adult subjects that underwent a total knee arthroplasty. The subject performed squat tasks while the motion was concurrently recorded by passive markers attached to the skin of the lower limbs, an optoelectronic system, and a fluoroscope. The STA of shank and thigh was decomposed in local deformation and rigid motion. Additionally, we studied how the instantaneous helical axis (IHA) calculation is affected by STA.

FINDINGS

The cluster most affected by STA rigid motion was the thigh. The largest estimated effects were about 7 deg. and about 20 mm. The largest effect of local deformation was about 25 mm, and it was observed on the thigh cluster.

INTERPRETATION

The STA made the estimation of the IHA unreliable for both position and direction. The choice of the reference configuration influenced the results of the STA analysis.

Validity of the Baiobit Inertial Measurements Unit for the Assessment of Vertical Double- and Single-Leg Countermovement Jumps in Athletes

Jump tests are simple, quick to execute, and considered the most reliable tool to measure lower extremities power and explosiveness in athletes. Wearable inertial sensors allow the assessment of jumping performance on any surface. The validity of inertial sensors measurements is a pivotal prerequisite to reliably implement their utilization in the clinical practice. Twenty-seven athletes (20 M/7 F, age: 27 ± 7 years old) performed five double-leg countermovement jumps (CMJs) and three single-leg CMJs per side with their hands on their hips. Jump height was measured/computed simultaneously with the optoelectronic system, force platforms, and the Baiobit inertial sensor system. The athletes completed the international physical activity questionnaire (IPAQ). When comparing the methods (Baiobit vs. force platforms), a non-statistically significant bias of 1.8 cm was found for two-leg CMJs and -0.6 cm for single-leg CMJs. The intraclass correlation coefficients (ICCs) was "excellent" for double-leg CMJs (ICC = 0.92, 95% CI = 0.89-0.94) and "good" for single-leg CMJs (ICC = 0.89, 95% CI = 0.85-0.91). When comparing the methods (Baiobit vs. force platforms + optoelectronic system), a non-statistically significant bias of -0.9 cm was found for two-leg CMJs and -1.2 cm for single-leg CMJs. The intraclass correlation coefficient (ICC) was "good" for both double-leg CMJs (ICC = 0.80, 95% CI = 0.73-0.85) and for single-leg CMJs (ICC = 0.86, 95% CI = 0.80-0.89). Baiobit tends to overestimate double- and single-leg CMJ height measurements; however, it can be recommended in the world of rehabilitation and sport analysis.

Analysis of Running Gait in Children with Cerebral Palsy: Barefoot vs. a New Ankle Foot Orthosis

Running is an essential activity for children with cerebral palsy (CP). This study aims to characterize the locomotor pattern of running in hemiplegic children with new generation ankle foot orthosis (AFOs) conceived to foster intense motor activities such as running. A group of 18 children with spastic hemiplegia was recruited. A biomechanical multivariable comparison was made between barefoot and with AFO running trials. The focus was devoted to bilateral sagittal plane hip, knee, ankle kinematics and kinetics, and three-dimensional ground reaction forces. Wearing the orthoses, the children were found to reduce cadence and the duration of the stance phase as well as increase the step and stride length. The new AFO resulted in significant changes in kinematics of affected ankle both at initial contact 0-3% GC (p < 0.017) and during the entire swing phase 31-100%GC (p < 0.001) being the ankle more dorsiflexed with AFO compared to barefoot condition. Ankle power was found to differ significantly both in absorption and generation 5-10%GC (p < 0.001); 21-27%GC (p < 0.001) with a reduction in both cases when the AFO was worn. No statistical differences were recorded in the GRF components, in the affected ankle torque and hip and knee kinematics and kinetics.

An optimal method for calculating an average screw axis for a joint, with improved sensitivity to noise and providing an analysis of the dispersion of the instantaneous axes

The instantaneous (ISA) and average (ASA) screw axes are techniques commonly adopted in motion analysis to functionally locate the rotation axis and center of rotation of a joint. Several approaches for calculating such axes were proposed in literature and the main limitations were identified as the need for using a threshold on angular displacements or velocities for handling the cases where the ISA is ill-defined and the need for a method for reliably estimating the center or rotation in limit cases, such as a purely rotational motion in the three-dimensional space. Furthermore, in many applications, such as in biomechanics, it is useful to statistically estimate the dispersion or variation of the ISA with respect to the ASA. In this paper we propose a novel method for estimating an ASA. Our method represents an improvement over previous methods as it: (i) exploits an optimization procedure based on the instantaneous differential kinematics (screw twist); (ii) removes the need for a threshold by introducing a weighting based on the norm of angular velocity; (iii) handles the singular cases where the position of the ASA is ill-defined by proposing a regularization term in the optimization. In addition, we proposed a method for estimating the uncertainty in the ASA calculation. The same quantities serve as a measure of the dispersion of the ISAs with respect to the ASA. The method was tested on real data and surrogate data: (i) a human gait analysis trial representing the motion of a knee, (ii) the experimental recording of the free swing motion of a mechanical hinge and (iii) synthetically generated motion data of a purely rotational (cylindrical) motion. The results showed that the new method had a lower sensitivity to noise, was able to reasonably handle the singular cases and provide a detailed analysis of ISA dispersion.

Accuracy of a 3D temporal scanning system for gait analysis: Comparative with a marker-based photogrammetry system

BACKGROUND

Combining the accuracy of marker-based stereophotogrammetry and the usability and comfort of markerless human movement analysis is a difficult challenge. 3D temporal scanners are a promising solution, since they provide moving meshes with thousands of vertices that can be used to analyze human movements.

RESEARCH QUESTION

Can a 3D temporal scanner be used as a markerless system for gait analysis with the same accuracy as traditional, marker-based stereophotogrammetry systems?

METHODS

A comparative study was carried out using a 3D temporal scanner synchronized with a marker-based stereophotogrammetry system. Two gait cycles of twelve healthy adults were measured simultaneously, extracting the positions of key anatomical points from both systems, and using them to analyze the 3D kinematics of the pelvis, right hip and knee joints. Measurement differences of marker positions and joint angles were described by their root mean square. A t-test was performed to rule out instrumental errors, and an F-test to evaluate the amplifications of marker position errors in dynamic conditions.

RESULTS

The differences in 3D landmark positions were between 1.9 and 2.4 mm in the reference pose. Marker position errors were significantly increased during motion in the medial-lateral and vertical directions. The angle relative errors were between 3% and 43% of the range of motion, with the greatest difference being observed in hip axial rotation.

SIGNIFICANCE

The differences in the results obtained between the 3D temporal scanner and the marker-based system were smaller than the usual errors due to lack of accuracy in the manual positioning of markers on anatomical landmarks and to soft-tissue artefacts. That level of accuracy is greater than other markerless systems, and proves that such technology is a good alternative to traditional, marker-based motion capture.

Smart Brace for Static and Dynamic Knee Laxity Measurement

Every year in Europe more than 500 thousand injuries that involve the anterior cruciate ligament (ACL) are diagnosed. The ACL is one of the main restraints within the human knee, focused on stabilizing the joint and controlling the relative movement between the tibia and femur under mechanical stress (i.e., laxity). Ligament laxity measurement is clinically valuable for diagnosing ACL injury and comparing possible outcomes of surgical procedures. In general, knee laxity assessment is manually performed and provides information to clinicians which is mainly subjective. Only recently quantitative assessment of knee laxity through instrumental approaches has been introduced and become a fundamental asset in clinical practice. However, the current solutions provide only partial information about either static or dynamic laxity. To support a multiparametric approach using a single device, an innovative smart knee brace for knee laxity evaluation was developed. Equipped with stretchable strain sensors and inertial measurement units (IMUs), the wearable system was designed to provide quantitative information concerning the drawer, Lachman, and pivot shift tests. We specifically characterized IMUs by using a reference sensor. Applying the Bland–Altman method, the limit of agreement was found to be less than 0.06 m/s² for the accelerometer, 0.06 rad/s for the gyroscope and 0.08 μT for the magnetometer. By using an appropriate characterizing setup, the average gauge factor of the three strain sensors was 2.169. Finally, we realized a pilot study to compare the outcomes with a marker-based optoelectronic stereophotogrammetric system to verify the validity of the designed system. The preliminary findings for the capability of the system to discriminate possible ACL lesions are encouraging; in fact, the smart brace could be an effective support for an objective and quantitative diagnosis of ACL tear by supporting the simultaneous assessment of both rotational and translational laxity. To obtain reliable information about the real effectiveness of the system, further clinical validation is necessary.