Comparative assessment of knee joint models used in multi-body kinematics optimisation for soft tissue artefact compensation.

Estimating joint kinematics from skin-marker trajectories recorded using stereophotogrammetry is complicated by soft tissue artefact (STA), an inexorable source of error. One solution is to use a bone pose estimator based on multi-body kinematics optimisation (MKO) embedding joint constraints to compensate for STA. However, there is some debate over the effectiveness of this method. The present study aimed to quantitatively assess the degree of agreement between reference (i.e., artefact-free) knee joint kinematics and the same kinematics estimated using MKO embedding six different knee joint models. The following motor tasks were assessed: level walking, hopping, cutting, running, sit-to-stand, and step-up. Reference knee kinematics was taken from pin-marker or biplane fluoroscopic data acquired concurrently with skin-marker data, made available by the respective authors. For each motor task, Bland-Altman analysis revealed that the performance of MKO varied according to the joint model used, with a wide discrepancy in results across degrees of freedom (DoFs), models and motor tasks (with a bias between -10.2° and 13.2° and between -10.2mm and 7.2mm, and with a confidence interval up to ±14.8° and ±11.1mm, for rotation and displacement, respectively). It can be concluded that, while MKO might occasionally improve kinematics estimation, as implemented to date it does not represent a reliable solution to the STA issue.

Overcoming the limitations of the Harmonic Ratio for the reliable assessment of gait symmetry.

The Harmonic Ratio (HR) is an index based on the spectral analysis of lower trunk accelerations that is commonly used to assess the quality of gait. However, it presents several issues concerning reliability and interpretability. As a consequence, the literature provides very different values albeit corresponding to the same populations. In the present work, an improved harmonic ratio (iHR) was defined, relating the power of the intrinsic harmonics (i.e. associated with the symmetric component of gait) to the total power of the signal for each stride, leading to a normalised index ranging from 0 to 100%. The effect of the considered number of harmonics and strides on the estimate of both HR and iHR was assessed. The gait of three groups of volunteers was investigated: young healthy adults, elderly women and male trans-femoral amputees. Both HR and iHR were able to discriminate gait deviations from the gait of young healthy adults. Moreover, iHR proved to be more robust with respect to the number of considered harmonics and strides, and to exhibit a lower inter-stride variability. Additionally, using a normalised index as iHR led to a more straightforward interpretation and improved comparability. The importance of standardised conditions for the index evaluation was unveiled, and, in order to enhance the future comparability of the index, the following guidelines were presented: considering at least 20 harmonics and 20 strides; expressing the acceleration components in a repeatable, anatomical, local system of reference; and evaluating the iHR index, rather than the traditional HR.

To what extent is joint and muscle mechanics predicted by musculoskeletal models sensitive to soft tissue artefacts?

Musculoskeletal models are widely used to estimate joint kinematics, intersegmental loads, and muscle and joint contact forces during movement. These estimates can be heavily affected by the soft tissue artefact (STA) when input positional data are obtained using stereophotogrammetry, but this aspect has not yet been fully characterised for muscle and joint forces. This study aims to assess the sensitivity to the STA of three open-source musculoskeletal models, implemented in OpenSim. A baseline dataset of marker trajectories was created for each model from experimental data of one healthy volunteer. Five hundred STA realizations were then statistically generated using a marker-dependent model of the pelvis and lower limb artefact and added to the baseline data. The STA׳s impact on the musculoskeletal model estimates was finally quantified using a Monte Carlo analysis. The modelled STA distributions were in line with the literature. Observed output variations were comparable across the three models, and sensitivity to the STA was evident for most investigated quantities. Shape, magnitude and timing of the joint angle and moment time histories were not significantly affected throughout the entire gait cycle, whereas magnitude variations were observed for muscle and joint forces. Ranges of contact force variations differed between joints, with hip variations up to 1.8 times body weight observed. Variations of more than 30% were observed for some of the muscle forces. In conclusion, musculoskeletal simulations using stereophotogrammetry may be safely run when only interested in overall output patterns. Caution should be paid when more accurate estimated values are needed.

Estimating orientation using magnetic and inertial sensors and different sensor fusion approaches: accuracy assessment in manual and locomotion tasks.

Magnetic and inertial measurement units are an emerging technology to obtain 3D orientation of body segments in human movement analysis. In this respect, sensor fusion is used to limit the drift errors resulting from the gyroscope data integration by exploiting accelerometer and magnetic aiding sensors. The present study aims at investigating the effectiveness of sensor fusion methods under different experimental conditions. Manual and locomotion tasks, differing in time duration, measurement volume, presence/absence of static phases, and out-of-plane movements, were performed by six subjects, and recorded by one unit located on the forearm or the lower trunk, respectively. Two sensor fusion methods, representative of the stochastic (Extended Kalman Filter) and complementary (Non-linear observer) filtering, were selected, and their accuracy was assessed in terms of attitude (pitch and roll angles) and heading (yaw angle) errors using stereophotogrammetric data as a reference. The sensor fusion approaches provided significantly more accurate results than gyroscope data integration. Accuracy improved mostly for heading and when the movement exhibited stationary phases, evenly distributed 3D rotations, it occurred in a small volume, and its duration was greater than approximately 20 s. These results were independent from the specific sensor fusion method used. Practice guidelines for improving the outcome accuracy are provided.

Non-invasive assessment of superficial soft tissue local displacements during movement: a feasibility study.

In the movement analysts community, the assessment of the displacement of skin photogrammetric markers relative to the underlying bone (soft tissue displacement, STD) is considered to be a priority. The aim of this study is to present a non-invasive method that allows for the characterization of STD for any marker location, subject, and motor task. In particular, this method provides an estimate of the STD vector in a bone-embedded frame. The body segment under analysis is endowed with the largest possible number of skin markers located over all areas of interest. Any given STD vector is observed from all the marker cluster frames that can be built by suitably combining all the available markers. A subset of the latter frames is identified that is made of frames endowed with uncorrelated local movements. The estimate of a given STD vector is determined through the coherent average of the vectors reconstructed using the above-mentioned independent frames. This estimate is affected by a 180 degrees phase indeterminacy. The proposed method and the underlying hypotheses were validated using markers located on the thighs of two female subjects treated for a total knee replacement. The relevant STD estimates, STDm, were compared with those directly observed using photogrammetry combined with 2D fluoroscopic projections and the prosthesis CAD model (STDf). Recordings were made while the volunteers performed step up/down motor tasks. The root mean square value of STDm was found in the range 2.5-23.0 mm and was consistent with the RMS values of STDf and with other results reported in the literature and obtained in similarly unconstrained conditions. Moreover, STDm and STDf showed a pattern similarity measured by a correlation coefficient equal to 0.83 (+/-0.13) and by a normalised root mean square distance equal to 27% (+/-16%). The described estimate of the STD pattern and magnitude, even with the above-mentioned indeterminacies, constitutes valuable information when aiming at optimal marker placement and is an indispensable prerequisite for bone pose estimator design and assessment.

Assessment of level-walking aperiodicity.

BACKGROUND: In gait analysis, walking is assumed to be periodic for the sake of simplicity, despite the fact that, strictly speaking, it can only approximate periodicity and, as such, may be referred to as pseudo-periodic. This study aims at: 1) quantifying gait pseudo-periodicity using information concerning a single stride; 2) investigating the effects of walking pathway length on gait periodicity; 3) investigating separately the periodicity of the upper and lower body parts movement; 4) verifying the validity of foot-floor contact events as markers of the gait cycle period. METHODS: Ten young healthy subjects (6 males, 23 +/- 5 years) were asked to perform various gait trials, first along a 20-m pathway that allowed reaching a steady-state condition, and then along an 8-m pathway. A stereophotogrammetric system was used to reconstruct the 3D position of reflective markers distributed over the subjects' body. Foot contact was detected using an instrumented mat. Three marker clusters were used to represent the movement of the whole body, the upper body (without upper limbs), and the lower body, respectively. Linear and rotational kinetic, and gravitational and elastic potential "energy-like" quantities were used to calculate an index J(t) that described the instantaneous "mechanical state" of the analysed body portion. The variations of J(t) in time allowed for the determination of the walking pseudo-period and for the assessment of gait aperiodicity. RESULTS: The suitability of the proposed approach was demonstrated, and it was shown that, for young, healthy adults, a threshold of physiological pseudo-periodicity of walking at natural speed could be set. Higher pseudo-periodicity values were found for the shorter pathway only for the upper body. Irrespective of pathway length, the upper body had a larger divergency from periodicity than the lower body. The error that can be made in estimating the gait cycle duration for the upper body from the heel contacts was shown to be significant. CONCLUSION: The proposed method can be easily implemented in gait laboratories to verify the consistency of a recorded stride with the hypothesis of periodicity.

Biomechanic modeling of sit-to-stand to upright posture for mobility assessment of persons with chronic stroke.

OBJECTIVE: To test the suitability of using biomechanic measures associated with a minimum measured input model (MMIM) approach to assess mobility of people with chronic stroke during the execution of a sit-to-stand (STS) to upright posture motor task. DESIGN: Single group, observational. SETTING: Institutional settings in the United States and Italy. PARTICIPANTS: Twenty-nine subjects with chronic unilateral lower-limb impairments and resultant mobility limitations secondary to stroke. INTERVENTIONS: Not applicable. MAIN OUTCOME MEASURES: Manual measurement of lower-limb strength; performance-based tests including repeated chair standing, walking speed, and standing balance; and ground reactions measured with a force platform during STS and upright posture. The ground reactions were fed to a telescopic inverted pendulum model of the musculoskeletal system. Parameters representing the model outputs were compared with performance-based and strength measures to assess, respectively, motor ability and impairment-related changes in subjects' motor strategies. RESULTS: The parameters derived from the model effectively differentiated between motor strategies associated with different performance-based scores, and allowed the identification of relevant difficulties encountered in STS execution. These difficulties could be associated with different strength scores. This was also true for subjects scoring the maximum in both performance-based and strength tests. CONCLUSIONS: The MMIM is a relatively inexpensive and noninvasive approach that enhances mobility assessment of hemiparetic subjects with different motor ability levels. It provides information that correlates well with performance-based and strength scores and, in addition, it allows for subject-specific motor strategy identification.

Reconstruction of skeletal movement using skin markers: comparative assessment of bone pose estimators.

BACKGROUND: The assessment of the accuracy of the pose estimation of human bones and consequent joint kinematics is of primary relevance in human movement analysis. This study evaluated the performance of selected pose estimators in reducing the effects of instrumental errors, soft tissue artifacts and anatomical landmark mislocations occurring at the thigh on the determination of the knee kinematics. METHODS: The pattern of a typical knee flexion-extension during a gait cycle was fed into a knee model which generated a six-components knee kinematics and relevant marker trajectories. The marker trajectories were corrupted with both instrumental noise and soft tissue artifacts. Two different cluster configurations (4 and 12-marker cluster) were investigated. Four selected pose estimators, a Geometrical method, a SVD-based method, and the Pointer Cluster Technique in the optimized and non optimized version, were analyzed. The estimated knee kinematics were compared to the nominal kinematics in order to evaluate the accuracy of the selected pose estimators. RESULTS: Results have shown that optimal pose estimators perform better than traditional geometric pose estimators when soft tissue artifacts are present. The use of redundant markers improved in some cases the estimation of the dynamics of the kinematics patterns, while it does not reduce the offsets from the nominal kinematics curves. Overall, the best performance was obtained by the SVD-based pose estimator, while the performance of the PCT pose estimator in its optimal version was not satisfactory. However, the knee kinematics errors reached 5 deg for rotations and 10 mm for translations). CONCLUSION: Given the favorable experimental conditions of this study (soft tissue artifacts determined from a young, healthy and non overweight subject), the errors found in estimating the knee kinematics have to be considered unsatisfactory even if the best performing pose estimator is used. Therefore, it is the authors' opinion that the movement analysis research community should make additional efforts in the search of more subject specific error models to increase the accuracy of joint kinematics estimations.

Human movement analysis using stereophotogrammetry. Part 3. Soft tissue artifact assessment and compensation.

When using optoelectronic stereophotogrammetry, skin deformation and displacement causes marker movement with respect to the underlying bone. This movement represents an artifact, which affects the estimation of the skeletal system kinematics, and is regarded as the most critical source of error in human movement analysis. A comprehensive review of the state-of-the-art for assessment, minimization and compensation of the soft tissue artifact (STA) is provided. It has been shown that STA is greater than the instrumental error associated with stereophotogrammetry, has a frequency content similar to the actual bone movement, is task dependent and not reproducible among subjects and, of lower limb segments, is greatest at the thigh. It has been shown that in in vivo experiments only motion about the flexion/extension axis of the hip, knees and ankles can be determined reliably. Motion about other axes at those joints should be regarded with much more caution as this artifact produces spurious effects with magnitudes comparable to the amount of motion actually occurring in those joints. Techniques designed to minimize the contribution of and compensate for the effects of this artifact can be divided up into those which model the skin surface and those which include joint motion constraints. Despite the numerous solutions proposed, the objective of reliable estimation of 3D skeletal system kinematics using skin markers has not yet been satisfactorily achieved and greatly limits the contribution of human movement analysis to clinical practice and biomechanical research. For STA to be compensated for effectively, it is here suggested that either its subject-specific pattern is assessed by ad hoc exercises or it is characterized from a large series of measurements on different subject populations. Alternatively, inclusion of joint constraints into a more general STA minimization approach may provide an acceptable solution.

Human movement analysis using stereophotogrammetry. Part 4: assessment of anatomical landmark misplacement and its effects on joint kinematics.

Estimating the effects of different sources of error on joint kinematics is crucial for assessing the reliability of human movement analysis. The goal of the present paper is to review the different approaches dealing with joint kinematics sensitivity to rotation axes and the precision of anatomical landmark determination. Consistent with the previous papers in this series, the review is limited to studies performed with video-based stereophotogrammetric systems. Initially, studies dealing with estimates of precision in determining the location of both palpable and internal anatomical landmarks are reviewed. Next, the effects of anatomical landmark position uncertainty on anatomical frames are shown. Then, methods reported in the literature for estimating error propagation from anatomical axes location to joint kinematics are described. Interestingly, studies carried out using different approaches reported a common conclusion: when joint rotations occur mainly in a single plane, minor rotations out of this plane are strongly affected by errors introduced at the anatomical landmark identification level and are prone to misinterpretation. Finally, attempts at reducing joint kinematics errors due to anatomical landmark position uncertainty are reported. Given the relevance of this source of errors in the determination of joint kinematics, it is the authors' opinion that further efforts should be made in improving the reliability of the joint axes determination.

Minimum measured-input models for the assessment of motor ability.

The problem of assessing the physical functional limitation of a given individual and establishing the relationship between impairment/s and disability using a biomechanical approach is addressed. This endeavour was pursued with reference to the locomotor system and in order to address the following specific clinical issues: prognosis, eligibility for health services, measure of the outcome of a therapy, and therapeutic programming. A thorough biomechanical analysis of selected motor tasks would be effective but awkward to apply for subject-specific evaluation in clinical practice by reason of the complexity of both instrumentation and experimental protocols. In addition, as illustrated in the paper, the adequacy of the accuracy with which this type of analysis provides relevant information may be argued. Therefore, different methods were devised in the attempt to join objectivity with field applicability. These entailed the measurement of a minimum number of biomechanical variables during the execution of the selected motor task and these quantities were acquired using a low cost experimental apparatus least perceivable to the test subject, that is a dynamometric plate. However, since data thus obtained do not necessarily lend themselves to straightforward interpretation in terms of function assessment, models of the musculo-skeletal system that embodied the invariant aspects of both the modelled system and the specific motor task were devised. Using such "minimum measured-input models", physiology-related, and thus easier to interpret, information was obtained. Two different sets of mathematical models are presented: one deals with the lowest level of detail and normally aims at assessing a global physical performance score, the other discloses joint function and segmental mechanics and therefore contributes to establishing a relationship between impairment and disability. The validation of these models, carried out in the laboratory, has shown that they possess a potential for application in clinical practice.