Technological Solutions for Human Movement Analysis in Obese Subjects: A Systematic Review.

Obesity has a critical impact on musculoskeletal systems, and excessive weight directly affects the ability of subjects to realize movements. It is important to monitor the activities of obese subjects, their functional limitations, and the overall risks related to specific motor tasks. From this perspective, this systematic review identified and summarized the main technologies specifically used to acquire and quantify movements in scientific studies involving obese subjects. The search for articles was carried out on electronic databases, i.e., PubMed, Scopus, and Web of Science. We included observational studies performed on adult obese subjects whenever reporting quantitative information concerning their movement. The articles must have been written in English, published after 2010, and concerned subjects who were primarily diagnosed with obesity, thus excluding confounding diseases. Marker-based optoelectronic stereophotogrammetric systems resulted to be the most adopted solution for movement analysis focused on obesity; indeed, wearable technologies based on magneto-inertial measurement units (MIMUs) were recently adopted for analyzing obese subjects. Further, these systems are usually integrated with force platforms, so as to have information about the ground reaction forces. However, few studies specifically reported the reliability and limitations of these approaches due to soft tissue artifacts and crosstalk, which turned out to be the most relevant problems to deal with in this context. In this perspective, in spite of their inherent limitations, medical imaging techniques-such as Magnetic Resonance Imaging (MRI) and biplane radiography-should be used to improve the accuracy of biomechanical evaluations in obese people, and to systematically validate less-invasive approaches.

Body-Worn IMU-Based Human Hip and Knee Kinematics Estimation during Treadmill Walking.

Traditionally, inertial measurement unit (IMU)-based human joint angle estimation techniques are evaluated for general human motion where human joints explore all of their degrees of freedom. Pure human walking, in contrast, limits the motion of human joints and may lead to unobservability conditions that confound magnetometer-free IMU-based methods. This work explores the unobservability conditions emergent during human walking and expands upon a previous IMU-based method for the human knee to also estimate human hip angles relative to an assumed vertical datum. The proposed method is evaluated (N=12) in a human subject study and compared against an optical motion capture system. Accuracy of human knee flexion/extension angle (7.87∘ absolute root mean square error (RMSE)), hip flexion/extension angle (3.70∘ relative RMSE), and hip abduction/adduction angle (4.56∘ relative RMSE) during walking are similar to current state-of-the-art self-calibrating IMU methods that use magnetometers. Larger errors of hip internal/external rotation angle (6.27∘ relative RMSE) are driven by IMU heading drift characteristic of magnetometer-free approaches and non-hinge kinematics of the hip during gait, amongst other error sources. One of these sources of error, soft tissue perturbations during gait, is explored further in the context of knee angle estimation and it was observed that the IMU method may overestimate the angle during stance and underestimate the angle during swing. The presented method and results provide a novel combination of observability considerations, heuristic correction methods, and validation techniques to magnetic-blind, kinematic-only IMU-based skeletal pose estimation during human tasks with degenerate kinematics (e.g., straight line walking).

Wearable IMMU-Based Relative Position Estimation between Body Segments via Time-Varying Segment-to-Joint Vectors.

In biomechanics, estimating the relative position between two body segments using inertial and magnetic measurement units (IMMUs) is important in that it enables the capture of human motion in unconstrained environments. The relative position can be estimated using the segment orientation and segment-to-joint center (S2J) vectors where the S2J vectors are predetermined as constants under the assumption of rigid body segments. However, human body segments are not rigid bodies because they are easily affected by soft tissue artifacts (STAs). Therefore, the use of the constant S2J vectors is one of the most critical factors for the inaccurate estimation of relative position. To deal with this issue, this paper proposes a method of determining time-varying S2J vectors to reflect the deformation of the S2J vectors and thus to increase the estimation accuracy, in IMMU-based relative position estimation. For the proposed method, first, reference S2J vectors for learning needed to be collected. A regression method derived a function outputting S2J vectors based on specific physical quantities that were highly correlated with the deformation of S2J vectors. Subsequently, time-varying S2J vectors were determined from the derived function. The validation results showed that, in terms of the averaged root mean squared errors of four tests performed by three subjects, the proposed method (15.08 mm) provided a higher estimation accuracy than the conventional method using constant vectors (31.32 mm). This indicates the proposed method may effectively compensate for the effects of STAs and ultimately estimate more accurate relative positions. By providing STA-compensated relative positions between segments, the proposed method applied in a wearable motion tracking system can be useful in rehabilitation or sports sciences.

Body-Worn IMU Human Skeletal Pose Estimation Using a Factor Graph-Based Optimization Framework.

Traditionally, inertial measurement units- (IMU) based human joint angle estimation requires a priori knowledge about sensor alignment or specific calibration motions. Furthermore, magnetometer measurements can become unreliable indoors. Without magnetometers, however, IMUs lack a heading reference, which leads to unobservability issues. This paper proposes a magnetometer-free estimation method, which provides desirable observability qualities under joint kinematics that sufficiently excite the lower body degrees of freedom. The proposed lower body model expands on the current self-calibrating human-IMU estimation literature and demonstrates a novel knee hinge model, the inclusion of segment length anthropometry, segment cross-leg length discrepancy, and the relationship between the knee axis and femur/tibia segment. The maximum a posteriori problem is formulated as a factor graph and inference is performed via post-hoc, on-manifold global optimization. The method is evaluated (N = 12) for a prescribed human motion profile task. Accuracy of derived knee flexion/extension angle (4.34∘ root mean square error (RMSE)) without magnetometers is similar to current state-of-the-art with magnetometer use. The developed framework can be expanded for modeling additional joints and constraints.

Quantification of three-dimensional soft tissue artifacts in the canine hindlimb during passive stifle motion.

BACKGROUND: Three-dimensional joint kinematics during canine locomotion are commonly measured using skin marker-based stereophotogrammetry technologies. However, marker-related errors caused by the displacement of the skin surface relative to the underlying bones (i.e., soft tissue artifacts, STA) may affect the accuracy of the measurements and obscure clinically relevant information. Few studies have assessed STA in canine limbs during kinematic analysis. The magnitudes and patterns of the STA and their influence on kinematic analysis remain unclear. Therefore, the current study aims to quantify the in vivo STA of skin markers on the canine thigh and crus during passive joint motion. The stifle joints of ten dogs were passively extended while the skin markers were measured using a motion capture system, and skeletal kinematics were determined using a CT-to-fluoroscopic image registration method. RESULTS: The skin markers exhibited considerable STA relative to the underlying bones, with a peak amplitude of 27.4 mm for thigh markers and 28.7 mm for crus markers; however, the amplitudes and displacement directions at different attachment sites were inconsistent. The markers on the cranial thigh and lateral crus closer to the stifle joint had greater STA amplitudes in comparison to those of other markers. Most markers had STA with linear and quadratic patterns against the stifle flexion angles. These STA resulted in underestimated flexion angles but overestimated adduction and internal rotation when the stifle was flexed to greater than 90°. CONCLUSIONS: Marker displacements relative to the underlying bones were prominent in the cranial aspect of the thigh and the proximal-lateral aspect of the crus. The calculated stifle kinematic variables were also affected by the STA. These findings can provide a reference for marker selection in canine motion analysis for similar motion tasks and clarify the relationship between STA patterns and stifle kinematics; the results may therefore contribute to the development of STA models and compensation techniques for canine motion analysis.

Quantification of soft tissue artifacts using CT registration and subject-specific multibody modeling.

The potential use of gait analysis for quantitative preoperative planning in total hip arthroplasty (THA) has previously been demonstrated. However, the joint kinematic data measured through this process tend to be unreliable for surgical planning due to distortions caused by soft tissue artifacts (STAs). In this study, we developed a novel motion capture framework by combining computed tomography (CT)-based postural calibration and subject-specific multibody dynamics modeling to prevent the effect of STAs in measuring hip kinematics. Three subjects with femoroacetabular impingement syndrome were recruited, and CT data for each patient were collected by attaching marker clusters near the hip. A subject-specific multibody hip joint model was developed based on reconstructed CT data. Spring-dashpot network calculations were performed to minimize the distance between the anatomical landmark and its corresponding infrared reflective marker. The STAs of the thigh was described as six degrees of freedom viscoelastic bushing elements, and their parameter values were identified via smooth orthogonal decomposition. Least squares optimization was used to modify the pelvic rotations to compensate for the rigid components of STAs. The results showed that CT-assisted motion tracking enabled the successful identification of STA influences in gait and squat positions. Furthermore, STA effects were found to alter maximal pelvis tilt and hip rotations during a squat. Compared to other techniques, such as dual fluoroscopic imaging, the adopted framework does not require additional medical imaging for patients undergoing robot-assisted THA surgery and is thus a practical way of evaluating hip joint kinematics for preoperative surgical planning.

[Research progress of optical motion capture technology in shoulder biomechanics].

The shoulder joint is the most flexible joint in the body with the largest range of motion, and the movement pattern is more complex. Accurate capture of three-dimensional motion data of the shoulder joint is crucial for biomechanical evaluation. Optical motion capture systems offer a non-invasive and radiation-free method to capture shoulder joint motion data during complex movements, enabling further biomechanical analysis of the shoulder joint. This review provides a comprehensive overview of optical motion capture technology in the context of shoulder joint movement, including measurement principles, data processing methods to reduce artifacts from skin and soft tissues, factors influencing measurement results, and applications in shoulder joint disorders.

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.

The Amsterdam Foot Model: a clinically informed multi-segment foot model developed to minimize measurement errors in foot kinematics.

BACKGROUND: Foot and ankle joint kinematics are measured during clinical gait analyses with marker-based multi-segment foot models. To improve on existing models, measurement errors due to soft tissue artifacts (STAs) and marker misplacements should be reduced. Therefore, the aim of this study is to define a clinically informed, universally applicable multi-segment foot model, which is developed to minimize these measurement errors. METHODS: The Amsterdam foot model (AFM) is a follow-up of existing multi-segment foot models. It was developed by consulting a clinical expert panel and optimizing marker locations and segment definitions to minimize measurement errors. Evaluation of the model was performed in three steps. First, kinematic errors due to STAs were evaluated and compared to two frequently used foot models, i.e. the Oxford and Rizzoli foot models (OFM, RFM). Previously collected computed tomography data was used of 15 asymptomatic feet with markers attached, to determine the joint angles with and without STAs taken into account. Second, the sensitivity to marker misplacements was determined for AFM and compared to OFM and RFM using static standing trials of 19 asymptomatic subjects in which each marker was virtually replaced in multiple directions. Third, a preliminary inter- and intra-tester repeatability analysis was performed by acquiring 3D gait analysis data of 15 healthy subjects, who were equipped by two testers for two sessions. Repeatability of all kinematic parameters was assessed through analysis of the standard deviation (σ) and standard error of measurement (SEM). RESULTS: The AFM was defined and all calculation methods were provided. Errors in joint angles due to STAs were in general similar or smaller in AFM (≤2.9°) compared to OFM (≤4.0°) and RFM (≤6.7°). AFM was also more robust to marker misplacement than OFM and RFM, as a large sensitivity of kinematic parameters to marker misplacement (i.e. > 1.0°/mm) was found only two times for AFM as opposed to six times for OFM and five times for RFM. The average intra-tester repeatability of AFM angles was σ:2.2[0.9°], SEM:3.3 ± 0.9° and the inter-tester repeatability was σ:3.1[2.1°], SEM:5.2 ± 2.3°. CONCLUSIONS: Measurement errors of AFM are smaller compared to two widely-used multi-segment foot models. This qualifies AFM as a follow-up to existing foot models, which should be evaluated further in a range of clinical application areas.

Lumbar segment-dependent soft tissue artifacts of skin markers during in vivo weight-bearing forward-Backward bending.

Traditional optical motion capture (OMC) with retroreflective markers is commonly used to measure joint kinematics but was also reported with unavoidable soft tissue artifacts (STAs) when quantifying the motion of the spine. Additionally, the patterns of the STA on the lumbar spine remain unclear. This study aimed to 1) quantify the in vivo STAs of the human lower back in three-dimensional directions during weight-bearing forward-backward bending and 2) determine the effects of the STAs on the calculated flexion angles between the upper and lower lumbar spines and adjacent vertebrae by comparing the skin marker (SM)- and virtual bone marker (VM)-based measurements. Six healthy volunteers were imaged using a biplanar radiographic system, and thirteen skin markers were mounted on every volunteer's lower back while performing weight-bearing forward-backward bending. The STAs in the anterior/posterior (AP), medial/lateral (ML), and proximal/distal (PD) directions were investigated. The flexion angles between the upper and lower lumbar segments and adjacent intervertebral segments (L2-L5) throughout the cycle were calculated. For all the participants, STAs continuously increased in the AP direction and exhibited a reciprocal trend in the PD direction. During flexion, the STA at the lower lumbar region (L4-L5: 13.5 ± 6.5 mm) was significantly higher than that at the upper lumbar (L1-L3: 4.0 ± 1.5 mm) in the PD direction (p < 0.01). During extension, the lower lumbar (L4-L5: 2.7 ± 0.7 mm) exhibited significantly less STAs than that exhibited by the upper lumbar region (L1-L3: 6.1 ± 3.3 mm) (p < 0.05). The STA at the spinous process was significantly lower than that on both sides in the AP direction (p < 0.05). The present results on STAs, based on dual fluoroscopic measurements in healthy adult subjects, presented an anatomical direction, marker location, and anatomic segment dependency, which might help describe and quantify STAs for the lumbar spine kinematics and thus help develop location- and direction-specific weighting factors for use in global optimization algorithms aimed at minimizing the effects of STAs on the calculation of lumbar joint kinematics in the future.

Description of soft tissue artifacts and related consequences on hindlimb kinematics during canine gait.

BACKGROUND: Soft tissue artifacts (STAs) are a source of error in marker-based gait analysis in dogs. While some studies have revealed the existence of STAs in the canine hindlimb, STAs and their influence on kinematic gait analysis remain unclear. METHODS: Thirteen healthy Taiwan dogs affixed with twenty skin markers on the thigh and crus were recruited. Soft tissue artifacts and their influence on the determination of segment poses and stifle angles were assessed by simultaneously measuring marker trajectories and kinematics of the underlying bones via a model-based fluoroscopic analysis method. RESULTS: Markers on the thigh showed higher STAs than those on the crus, with root-mean-square amplitudes up to 15.5 mm. None of the tested marker clusters were able to accurately reproduce the skeletal poses, in which the maximum root-mean-square deviations ranged from 3.4° to 8.1°. The use of markers resulted in overestimated stifle flexion during 40-60% of the gait cycle and underestimated stifle flexion during 80-90% of the gait cycle. CONCLUSIONS: Considerable magnitudes and effects of STAs on the marker-based 3D gait analysis of dogs were demonstrated. The results indicate that the development of error-compensation techniques based on knowledge regarding STAs is warranted for more accurate gait analysis.

In situ comparison of A-mode ultrasound tracking system and skin-mounted markers for measuring kinematics of the lower extremity.

Skin-mounted marker based motion capture systems are widely used in measuring the movement of human joints. Kinematic measurements associated with skin-mounted markers are subject to soft tissue artifacts (STA), since the markers follow skin movement, thus generating errors when used to represent motions of underlying bone segments. We present a novel ultrasound tracking system that is capable of directly measuring tibial and femoral bone surfaces during dynamic motions, and subsequently measuring six-degree-of-freedom (6-DOF) tibiofemoral kinematics. The aim of this study is to quantitatively compare the accuracy of tibiofemoral kinematics estimated by the ultrasound tracking system and by a conventional skin-mounted marker based motion capture system in a cadaveric experimental scenario. Two typical tibiofemoral joint models (spherical and hinge models) were used to derive relevant kinematic outcomes. Intra-cortical bone pins equipped with optical markers were inserted in the tibial and femoral bones to serve as a reference to provide ground truth kinematics. The ultrasound tracking system resulted in lower kinematic errors than the skin-mounted markers (the ultrasound tracking system: maximum root-mean-square (RMS) error 3.44° for rotations and 4.88 mm for translations, skin-mounted markers with the spherical joint model: 6.32° and 6.26 mm, the hinge model: 6.38° and 6.52 mm). Our proposed ultrasound tracking system has the potential of measuring direct bone kinematics, thereby mitigating the influence and propagation of STA. Consequently, this technique could be considered as an alternative method for measuring 6-DOF tibiofemoral kinematics, which may be adopted in gait analysis and clinical practice.

Research progress of optical motion capture technology in shoulder biomechanics / 中国骨伤

The shoulder joint is the most flexible joint in the body with the largest range of motion, and the movement pattern is more complex. Accurate capture of three-dimensional motion data of the shoulder joint is crucial for biomechanical evaluation. Optical motion capture systems offer a non-invasive and radiation-free method to capture shoulder joint motion data during complex movements, enabling further biomechanical analysis of the shoulder joint. This review provides a comprehensive overview of optical motion capture technology in the context of shoulder joint movement, including measurement principles, data processing methods to reduce artifacts from skin and soft tissues, factors influencing measurement results, and applications in shoulder joint disorders.

Human-Robot Collaboration Dynamic Impact Testing and Calibration Instrument for Disposable Robot Safety Artifacts.

The Dynamic Impact Testing and Calibration Instrument (DITCI) is a simple instrument with a significant data collection and analysis capability that is used for the testing and calibration of biosimulant human tissue artifacts. These artifacts may be used to measure the severity of injuries caused in the case of a robot impact with a human. In this paper we describe the DITCI adjustable impact and flexible foundation mechanism, which allows the selection of a variety of impact force levels and foundation stiffness. The instrument can accommodate arrays of a variety of sensors and impact tools, simulating both real manufacturing tools and the testing requirements of standards setting organizations. A computer data acquisition system may collect a variety of impact motion, force, and torque data, which are used to develop a variety of mathematical model representations of the artifacts. Finally, we describe the fabrication and testing of human abdomen soft tissue artifacts, used to display the magnitude of impact tissue deformation. Impact tests were performed at various maximum impact force and average pressure levels.

Propagation of soft tissue artifacts to the center of rotation: a model for the correction of functional calibration techniques.

This paper presents a mathematical model for the propagation of errors in body segment kinematics to the location of the center of rotation. Three functional calibration techniques, usually employed for the gleno-humeral joint, are studied: the methods based on the pivot of the instantaneous helical axis (PIHA) or the finite helical axis (PFHA), and the "symmetrical center of rotation estimation" (SCoRE). A procedure for correcting the effect of soft tissue artifacts is also proposed, based on the equations of those techniques and a model of the artifact, like the one that can be obtained by double calibration. An experiment with a mechanical analog was performed to validate the procedure and compare the performance of each technique. The raw error (between 57 and 68mm) was reduced by a proportion of between 1:6 and less than 1:15, depending on the artifact model and the mathematical method. The best corrections were obtained by the SCoRE method. Some recommendations about the experimental setup for functional calibration techniques and the choice of a mathematical method are derived from theoretical considerations about the formulas and the results of the experiment.