Joint kinematics estimation using a multi-body kinematics optimisation and an extended Kalman filter,and embedding a soft tissue artefact model

To reduce the impact of the soft tissue artefact (STA) on the estimate of skeletal movement using stereophotogrammetric and skin-marker data, multi-body kinematics optimisation (MKO) and extended Kalman filters (EKF) have been proposed. This paper assessed the feasibility and efficiency of these methods when they embed a mathematical model of the STA and simultaneously estimate the ankle, knee and hip joint kinematics and the model parameters. A STA model was used that provides an estimate of the STA affecting the marker-cluster located on a body segment as a function of the kinematics of the adjacent joints. The MKO and the EKF were implemented with and without the STA model. To assess these methods, intra-cortical pin and skin markers located on the thigh, shank, and foot of three subjects and tracked during the stance phase of running were used. Embedding the STA model in MKO and EKF reduced the average RMS of marker tracking from 12.6 to 1.6 mm and from 4.3 to 1.9 mm, respectively, showing that a STA model trial-specific calibration is feasible. Nevertheless, with the STA model embedded in MKO, the RMS difference between the estimated and the reference joint kinematics determined from the pin markers slightly increased (from 2.0 to 2.1 deg) On the contrary, when the STA model was embedded in the EKF, this RMS difference was slightly reduced (from 2.0 to 1.7 deg) thus showing a better potentiality of this method to attenuate STA effects and improve the accuracy of joint kinematics estimate.     

Approximation of the functional kinematics of posterior stabilised total knee replacements using a two-dimensional sagittal plane patello-femoral model: comparing model approximation to in vivo measurement

Previous in vivo studies have observed that current designs of posterior stabilised (PS) total knee replacements (TKRs) may be ineffective in restoring normal kinematics in Late flexion. Computer-based models can prove a useful tool in improving PS knee replacement designs. This study investigates the accuracy of a two-dimensional (2D) sagittal plane model capable of predicting the functional sagittal plane kinematics of PS TKR implanted knees against direct in vivo measurement. Implant constraints are often used as determinants of anterior–posterior tibio-femoral positioning. This allowed the use of a patello-femoral modelling approach to determine the effect of implant constraints. The model was executed using motion simulation software which uses the constraint force algorithm to achieve a solution. A group of 10 patients implanted with Scorpio PS implants were recruited and underwent fluoroscopic imaging of their knees. The fluoroscopic images were used to determine relative implant orientation using a three-dimensional reconstruction method. The determined relative tibio-femoral orientations were then input to the model. The model calculated the patella tendon angles (PTAs) which were then compared with those measured from the in vivo fluoroscopic images. There were no significant differences between the measured and calculated PTAs. The average root mean square error between measured and modelled ranged from 1.17° to 2.10° over the flexion range. A sagittal plane patello-femoral model could conceivably be used to predict the functional 2D kinematics of an implanted knee joint. This may prove particularly useful in optimising PS designs.     

A soft tissue artefact model driven by proximal and distal joint kinematics

When analysing human movement through stereophotogrammetry, skin-markers are used. Their movement relative to the underlying bone is known as a soft tissue artefact (STA). A mathematical model to estimate subject- and marker-specific STAs generated during a given motor task, is required for both skeletal kinematic estimators and comparative assessment using simulation. This study devises and assesses such a mathematical model using the paradigmatic case of thigh STAs. The model was based on two hypotheses: (1) that the artefact mostly depends on skin sliding, and thus on the angles of hip and knee; (2) that the relevant relationship is linear. These hypotheses were tested using data obtained from passive hip and knee movements in non-obese specimens and from running volunteers endowed with both skin- and pin-markers.     

Dissipative particle dynamics of non-spherical particles using a Gaussian density model

The Gaussian density molecular model has been adapted for dissipative particle dynamics. The model, when combined with a soft potential, is shown to be a very flexible mesoscale model exhibiting a wide range of phase behaviour. The soft potential allows relatively large time steps to be used and hence a more rapid equilibration. In addition, the model can be used to study both uniaxial and biaxial systems. We have undertaken a number of pilot studies and have demonstrated that the Gaussian model is able to identify nematic–isotropic phase transitions in liquid crystals and the formation of ordered discotic phases.     

Estimation of hurdle clearance parameters using a monocular human motion tracking method

This paper presents a method of monocular human motion tracking for estimation of hurdle clearance kinematic parameters. The analysis involved 10 image sequences of five hurdlers at various training levels. Recording of the sequences was carried out under simulated starting conditions of a 110 m hurdle race. The parameters were estimated using the particle swarm optimization algorithm and they are based on analysis of the images recorded with a 100 Hz camera. The proposed method does not involve using any special clothes, markers, inertial sensors, etc. As the quality criteria, the mean absolute error and mean relative error were used. The level of computed errors justifies the use of this method to estimate hurdle clearance parameters.     

Sub-millimetre accurate human hand kinematics: from surface to skeleton

A highly accurate human hand kinematics model and identification are proposed. The model includes the five digits and the palm arc based on mapping function between surface landmarks and estimated joint centres of rotation. Model identification was experimentally performed using a motion tracking system. The evaluation of the marker position estimation error, which is on sub-millimetre level across all digits, underlines model quality and accuracy. Noticeably, with the development of this model, we were able to improve various modelling assumptions from literature and found a basic linear relationship between surface and skeleton rotational angles.     

A novel method to replicate the kinematics of the carpus using a six degree-of-freedom robot

Understanding the kinematics of the carpus is essential to the understanding and treatment of wrist pathologies. However, many of the previous techniques presented are limited by non-functional motion or the interpolation of points from static images at different postures. We present a method that has the capability of replicating the kinematics of the wrist during activities of daily living using a unique mechanical testing system. To quantify the kinematics of the carpal bones, we used bone pin-mounted markers and optical motion capture methods. In this paper, we present a hammering motion as an example of an activity of daily living. However, the method can be applied to a wide variety of movements. Our method showed good accuracy (1.0–2.6°) of in vivo movement reproduction in our ex vivo model. Most carpal motion during wrist flexion–extension occurs at the radiocarpal level while in ulnar deviation the motion is more equally shared between radiocarpal and midcarpal joints, and in radial deviation the motion happens mainly at the midcarpal joint. For all rotations, there was more rotation of the midcarpal row relative to the lunate than relative to the scaphoid or triquetrum. For the functional motion studied (hammering), there was more midcarpal motion in wrist extension compared to pure wrist extension while radioulnar deviation patterns were similar to those observed in pure wrist radioulnar deviation. Finally, it was found that for the amplitudes studied the amount of carpal rotations was proportional to global wrist rotations.     

Real-time inverse kinematics and inverse dynamics for lower limb applications using OpenSim

Real-time estimation of joint angles and moments can be used for rapid evaluation in clinical, sport, and rehabilitation contexts. However, real-time calculation of kinematics and kinetics is currently based on approximate solutions or generic anatomical models. We present a real-time system based on OpenSim solving inverse kinematics and dynamics without simplifications at 2000 frame per seconds with less than 31.5 ms of delay. We describe the software architecture, sensitivity analyses to minimise delays and errors, and compare offline and real-time results. This system has the potential to strongly impact current rehabilitation practices enabling the use of personalised musculoskeletal models in real-time.     

A learning-based markerless approach for full-body kinematics estimation in-natura from a single image

We present a supervised machine learning approach for markerless estimation of human full-body kinematics for a cyclist from an unconstrained colour image. This approach is motivated by the limitations of existing marker-based approaches restricted by infrastructure, environmental conditions, and obtrusive markers. By using a discriminatively learned mixture-of-parts model, we construct a probabilistic tree representation to model the configuration and appearance of human body joints. During the learning stage, a Structured Support Vector Machine (SSVM) learns body parts appearance and spatial relations. In the testing stage, the learned models are employed to recover body pose via searching in a test image over a pyramid structure. We focus on the movement modality of cycling to demonstrate the efficacy of our approach. In natura estimation of cycling kinematics using images is challenging because of human interaction with a bicycle causing frequent occlusions. We make no assumptions in relation to the kinematic constraints of the model, nor the appearance of the scene. Our technique finds multiple quality hypotheses for the pose. We evaluate the precision of our method on two new datasets using loss functions. Our method achieves a score of 91.1 and 69.3 on mean Probability of Correct Keypoint (PCK) measure and 88.7 and 66.1 on the Average Precision of Keypoints (APK) measure for the frontal and sagittal datasets respectively. We conclude that our method opens new vistas to robust user-interaction free estimation of full body kinematics, a prerequisite to motion analysis.     

Isolation of a novel RNA-binding protein and its association with a large ribonucleoprotein particle present in the nucleoplasm of tobacco cells

A cDNA encoding a protein with a consensus sequence-type RNA-binding domain (CS-RBD) has been isolated from a Nicotiana sylvestris cDNA library. The deduced protein (designated RZ-1) contains CS-RBD in its N-terminal half, arginine/aspartic acid repeats in its center and a glycine-rich C-terminal region in which a zinc finger motif of the CCHC type is present. The corresponding gene appears to be expressed constitutively in all tobacco organs. Immunocytochemical assays revealed that RZ-1 is localized in the nucleoplasm of tobacco cultured cells. Glycerol gradient fractionation of tobacco nuclear lysates showed that RZ-1 is associated with a large ribonucleoprotein particle of around 60 S in size. Nucleic acid-binding assays indicated that RZ-1 binds preferentially to poly (G) and both the CS-RBD and glycine-rich region are necessary for its binding activity. A possible role of RZ-1 is discussed.     

A constrained extended Kalman filter for the optimal estimate of kinematics and kinetics of a sagittal symmetric exercise

This paper presents a method for real-time estimation of the kinematics and kinetics of a human body performing a sagittal symmetric motor task, which would minimize the impact of the stereophotogrammetric soft tissue artefacts (STA). The method is based on a bi-dimensional mechanical model of the locomotor apparatus the state variables of which (joint angles, velocities and accelerations, and the segments lengths and inertial parameters) are estimated by a constrained extended Kalman filter (CEKF) that fuses input information made of both stereophotogrammetric and dynamometric measurement data. Filter gains are made to saturate in order to obtain plausible state variables and the measurement covariance matrix of the filter accounts for the expected STA maximal amplitudes. We hypothesised that the ensemble of constraints and input redundant information would allow the method to attenuate the STA propagation to the end results. The method was evaluated in ten human subjects performing a squat exercise. The CEKF estimated and measured skin marker trajectories exhibited a RMS difference lower than 4 mm, thus in the range of STAs. The RMS differences between the measured ground reaction force and moment and those estimated using the proposed method (9 N and 10 N m) were much lower than obtained using a classical inverse dynamics approach (22 N and 30 N m). From the latter results it may be inferred that the presented method allows for a significant improvement of the accuracy with which kinematic variables and relevant time derivatives, model parameters and, therefore, intersegmental moments are estimated.     

Objective classification of scapular kinematics in participants with movement faults of the scapula on clinical assessment

The aim of this study was to assess the potential of employing a classification tool to objectively classify participants with clinically assessed movement faults (MFs) of the scapula. Six participants with a history of shoulder pain with MFs of the scapula and 12 healthy participants with no movement faults (NMFs) performed a flexion movement control test of the scapula, while scapular kinematic data were collected. Principal component scores and discrete kinematic variables were used as input into a classifier. Five out of the six participants with a history of pain were successfully classified as having scapular MFs with an accuracy of 72%. Variables related to the upward rotation of the scapula had the most influence on the classification. The results of the study demonstrate the potential of adopting a multivariate approach in objective classification of participants with altered scapular kinematics in pathological groups.     

Analysis of finger vein variety in patients with various diseases using vein authentication technology

In finger vein authentication technology, near‐infrared rays penetrate the finger and are absorbed by the hemoglobin in blood. The veins appear as dark areas. The finger vein pattern images of patients with various diseases were acquired; a new evaluation method applying image processing technique (“E value”) was developed, and it was examined whether the patterns have any characteristics differentiating them from those of healthy volunteers. As a result, low E values appeared in systemic sclerosis, mixed connective tissue disease, Sjögren's syndrome, and polymyositis/dermatomyositis. No statistical reduction in E value was shown in patients with rheumatoid arthritis, pernio (without rheumatic diseases), arteriosclerosis obliterans, diabetes, hypertension, hypothyroidism and alopecia areata. This technology could be used for screening and evaluation of some diseases and their conditions with impaired peripheral venous circulation. E value may be useful as an indicator of venous circulation.      

An automatic particle pickup method using a neural network applicable to low-contrast electron micrographs

Three-dimensional reconstruction from electron micrographs requires the selection of many single-particle projection images; more than 10 000 are generally required to obtain 5- to 10-A structural resolution. Consequently, various automatic detection algorithms have been developed and successfully applied to large symmetric protein complexes. This paper presents a new automated particle recognition and pickup procedure based on the three-layer neural network that has a large application range than other automated procedures. Its use for both faint and noisy electron micrographs is demonstrated. The method requires only 200 selected particles as learning data and is able to detect images of proteins as small as 200 kDa.     

Quantitative underwater 3D motion analysis using submerged video cameras: accuracy analysis and trajectory reconstruction

In this study we aim at investigating the applicability of underwater 3D motion capture based on submerged video cameras in terms of 3D accuracy analysis and trajectory reconstruction. Static points with classical direct linear transform (DLT) solution, a moving wand with bundle adjustment and a moving 2D plate with Zhang's method were considered for camera calibration. As an example of the final application, we reconstructed the hand motion trajectories in different swimming styles and qualitatively compared this with Maglischo's model. Four highly trained male swimmers performed butterfly, breaststroke and freestyle tasks. The middle fingertip trajectories of both hands in the underwater phase were considered. The accuracy (mean absolute error) of the two calibration approaches (wand: 0.96 mm – 2D plate: 0.73 mm) was comparable to out of water results and highly superior to the classical DLT results (9.74 mm). Among all the swimmers, the hands' trajectories of the expert swimmer in the style were almost symmetric and in good agreement with Maglischo's model. The kinematic results highlight symmetry or asymmetry between the two hand sides, intra- and inter-subject variability in terms of the motion patterns and agreement or disagreement with the model. The two outcomes, calibration results and trajectory reconstruction, both move towards the quantitative 3D underwater motion analysis.     

A new method for motion capture of the scapula using an optoelectronic tracking device: a feasibility study

Optoelectronic tracking systems are rarely used in 3D studies examining shoulder movements including the scapula. Among the reasons is the important slippage of skin markers with respect to scapula. Methods using electromagnetic tracking devices are validated and frequently applied. Thus, the aim of this study was to develop a new method for in vivo optoelectronic scapular capture dealing with the accepted accuracy issues of validated methods.

Eleven arm positions in three anatomical planes were examined using five subjects in static mode. The method was based on local optimisation, and recalculation procedures were made using a set of five scapular surface markers.

The scapular rotations derived from the recalculation-based method yielded RMS errors comparable with the frequently used electromagnetic scapular methods (RMS up to 12.6° for 150° arm elevation). The results indicate that the present method can be used under careful considerations for 3D kinematical studies examining different shoulder movements.     

A simple,reliable method to determine the mean gait speed using heel markers on a treadmill

Gait speed is an essential parameter of gait analysis. Our study proposed a simple and accurate method to extract a mean gait speed during walking on a treadmill using only kinematic data from markers placed on the heels of the participants’ feet. This method provided an attractive, simple method that remains resistant to errors in treadmill calibration. In addition, this method required only two markers, since heel markers are essential to gait analysis, and the proposed method is robust enough to differentiate among various gait speeds (mean error <1%).