The efficacy of a video-based marker-less tracking system for gait analysis

Most clinical gait analyses are conducted using motion capture systems which track retro-reflective markers that are placed on key landmarks of the participants. An alternative to a three-dimensional (3D) motion capture, marker-based, optical camera system may be a marker-less video-based tracking system. The aim of our study was to investigate the efficacy of the use of a marker-less tracking system in the calculation of 3D joint angles for possible use in clinical gait analysis. Ten participants walked and jogged on a treadmill and their kinematic data were captured with a marker and marker-less tracking system simultaneously. The hip, knee and ankle angles in the frontal, sagittal and transverse planes were computed. Root Mean Square differences (RMS_diff) between corresponding angles for each participant’s support phase were calculated and averaged to derive the mean within-subject RMS_diff. These within-subject means were averaged to obtain the mean between-subject RMS_diff for the relevant joint angles in the two gait conditions (walking and jogging). The RMS_diff between the two tracking systems was less than 1° for all rotations of the three joint angles of the hip and knee. However, there were slightly larger differences in the ankle joint angles. The results of this study suggest a potential application in gait analysis in clinical settings where observations of anatomical motions may provide meaningful feedback.     

Muscle force estimation in clinical gait analysis using AnyBody and OpenSim

A variety of musculoskeletal models are applied in different modelling environments for estimating muscle forces during gait. Influence of different modelling assumptions and approaches on model outputs are still not fully understood, while direct comparisons of standard approaches have been rarely undertaken. This study seeks to compare joint kinematics, joint kinetics and estimated muscle forces of two standard approaches offered in two different modelling environments (AnyBody, OpenSim). It is hypothesised that distinctive differences exist for individual muscles, while summing up synergists show general agreement. Experimental data of 10 healthy participants (28 ± 5 years, 1.72 ± 0.08 m, 69 ± 12 kg) was used for a standard static optimisation muscle force estimation routine in AnyBody and OpenSim while using two gait-specific musculoskeletal models. Statistical parameter mapping paired t-test was used to compare joint angle, moment and muscle force waveforms in Matlab. Results showed differences especially in sagittal ankle and hip angles as well as sagittal knee moments. Differences were also found for some of the muscles, especially of the triceps surae group and the biceps femoris short head, which occur as a result of different anthropometric and anatomical definitions (mass and inertia of segments, muscle properties) and scaling procedures (static vs. dynamic). Understanding these differences and their cause is crucial to operate such modelling environments in a clinical setting. Future research should focus on alternatives to classical generic musculoskeletal models (e.g. implementation of functional calibration tasks), while using experimental data reflecting normal and pathological gait to gain a better understanding of variations and divergent behaviour between approaches.     

Kalman smoothing improves the estimation of joint kinematics and kinetics in marker-based human gait analysis

We developed a Kalman smoothing algorithm to improve estimates of joint kinematics from measured marker trajectories during motion analysis. Kalman smoothing estimates are based on complete marker trajectories. This is an improvement over other techniques, such as the global optimisation method (GOM), Kalman filtering, and local marker estimation (LME), where the estimate at each time instant is only based on part of the marker trajectories. We applied GOM, Kalman filtering, LME, and Kalman smoothing to marker trajectories from both simulated and experimental gait motion, to estimate the joint kinematics of a ten segment biomechanical model, with 21 degrees of freedom. Three simulated marker trajectories were studied: without errors, with instrumental errors, and with soft tissue artefacts (STA). Two modelling errors were studied: increased thigh length and hip centre dislocation. We calculated estimation errors from the known joint kinematics in the simulation study. Compared with other techniques, Kalman smoothing reduced the estimation errors for the joint positions, by more than 50% for the simulated marker trajectories without errors and with instrumental errors. Compared with GOM, Kalman smoothing reduced the estimation errors for the joint moments by more than 35%. Compared with Kalman filtering and LME, Kalman smoothing reduced the estimation errors for the joint accelerations by at least 50%. Our simulation results show that the use of Kalman smoothing substantially improves the estimates of joint kinematics and kinetics compared with previously proposed techniques (GOM, Kalman filtering, and LME) for both simulated, with and without modelling errors, and experimentally measured gait motion.     

Comparative assessment of bone pose estimation using Point Cluster Technique and OpenSim

Estimating the position of the bones from optical motion capture data is a challenge associated with human movement analysis. Bone pose estimation techniques such as the Point Cluster Technique (PCT) and simulations of movement through software packages such as OpenSim are used to minimize soft tissue artifact and estimate skeletal position; however, using different methods for analysis may produce differing kinematic results which could lead to differences in clinical interpretation such as a misclassification of normal or pathological gait. This study evaluated the differences present in knee joint kinematics as a result of calculating joint angles using various techniques. We calculated knee joint kinematics from experimental gait data using the standard PCT, the least squares approach in OpenSim applied to experimental marker data, and the least squares approach in OpenSim applied to the results of the PCT algorithm. Maximum and resultant RMS differences in knee angles were calculated between all techniques. We observed differences in flexion/extension, varus/valgus, and internal/external rotation angles between all approaches. The largest differences were between the PCT results and all results calculated using OpenSim. The RMS differences averaged nearly 5° for flexion/extension angles with maximum differences exceeding 15°. Average RMS differences were relatively small (< 1.08°) between results calculated within OpenSim, suggesting that the choice of marker weighting is not critical to the results of the least squares inverse kinematics calculations. The largest difference between techniques appeared to be a constant offset between the PCT and all OpenSim results, which may be due to differences in the definition of anatomical reference frames, scaling of musculoskeletal models, and/or placement of virtual markers within OpenSim. Different methods for data analysis can produce largely different kinematic results, which could lead to the misclassification of normal or pathological gait. Improved techniques to allow non-uniform scaling of generic models to more accurately reflect subject-specific bone geometries and anatomical reference frames may reduce differences between bone pose estimation techniques and allow for comparison across gait analysis platforms.     

A comparative collision-based analysis of human gait

This study compares human walking and running, and places them within the context of other mammalian gaits. We use a collision-based approach to analyse the fundamental dynamics of the centre of mass (CoM) according to three angles derived from the instantaneous force and velocity vectors. These dimensionless angles permit comparisons across gait, species and size. The collision angle Φ, which is equivalent to the dimensionless mechanical cost of transport CoT_mech, is found to be three times greater during running than walking of humans. This threefold difference is consistent with previous studies of walking versus trotting of quadrupeds, albeit tends to be greater in the gaits of humans and hopping bipeds than in quadrupeds. Plotting the collision angle Φ together with the angles of the CoM force vector Θ and velocity vector Λ results in the functional grouping of bipedal and quadrupedal gaits according to their CoM dynamics—walking, galloping and ambling are distinguished as separate gaits that employ collision reduction, whereas trotting, running and hopping employ little collision reduction and represent more of a continuum that is influenced by dimensionless speed. Comparable with quadrupedal mammals, collision fraction (the ratio of actual to potential collision) is 0.51 during walking and 0.89 during running, indicating substantial collision reduction during walking, but not running, of humans.     

Two-dimensional electrophoretic analysis of human erythrocyte cylindrin

In the absence of a peptidylproline substrate, the oxidative decarboxylation of 2-oxoglutarate by prolyl 4-hydroxylase (prolyl-glycyl-peptide,2-oxoglutarate:oxygen oxidoreductase (4-hydroxylating), EC 1.14.11.2) is stoicheiometrically coupled to the oxidation of ascorbate. The Km and Kd for O2 in this partial reaction are 1.5 mM, this value being one order of magnitude higher than the Km and Kd for O2 in the complete reaction in the presence of (Pro-Pro-Gly)5, indicating that in this case O2 can become enzyme-bound predominantly after the interaction of the peptide substrate with the enzyme. The Km values for 2-oxoglutarate in the partial and the complete reactions are the same. In the absence of both a peptide substrate and ascorbate 2 mol CO2 per mol enzyme are produced in the first 1-1.5 min, during which the enzyme becomes inactivated and, as shown earlier (De Jong , L., Albracht , S.P.J. and Kemp, A. (1982) Biochim. Biophys. Acta 704, 326-332) enzyme-bound Fe2+ becomes oxidized to Fe3+. The results are consistent with a mechanism in which a Fe2+O complex is the O-transferring intermediate involved in peptidylproline hydroxylation.     

Feasibility of using a video-based motion analysis system for measuring thumb kinematics

While several different methods have been used to measure hand kinematics, fluoroscopy is generally considered to be the most accurate. Recently, video-based motion analysis has been developed for the measurement of joint kinematics. This method is versatile, easy to use, and can measure motions dynamically. Surface markers are most commonly used in the video-based motion systems. However, whether the surface markers placed on the thumb accurately represent the true kinematics of the underlying bony segment is questionable.In this study, the feasibility of surface markers to represent thumb kinematics was investigated by fluoroscopy. Both the positions of surface markers and bony landmarks were simultaneous recorded and then digitized. The Ra(2) values comparing the angular changes of the thumb interphalangeal, metacarpal and carpometacarpal joints derived using the surface markers or bony landmarks were 0.9986, 0.9730 and 0.9186 in the flexion/extension plane respectively, 0.8837, 0.9697 and 0.8775 in the abduction/adduction plane; and 0.9884, 0.9643 and 0.9431 in the opposition plane. The ranges, mean and standard deviation of the absolute differences between calculated angles of different marker sets were also compared. These data revealed that the similarities of the two different marker techniques throughout the motion cycle were high. The differences between the two methods were also within clinically allowable range of +/-5 degrees. It is concluded that the application of the video-based motion analysis system with surface markers to thumb kinematics is warranted.     

A physiology-based inverse dynamic analysis of human gait using sequential convex programming: a comparative study

This paper presents an enhanced version of the previously proposed physiological inverse approach (PIA) to calculate musculotendon (MT) forces and evaluates the proposed methodology in a comparative study. PIA combines an inverse dynamic analysis with an optimisation approach that imposes muscle physiology and optimises performance over the entire motion. To solve the resulting large-scale, nonlinear optimisation problem, we neglected muscle fibre contraction speed and an approximate quadratic optimisation problem (PIA-QP) was formulated. Conversely, the enhanced version of PIA proposed in this paper takes into account muscle fibre contraction speed. The optimisation problem is solved using a sequential convex programing procedure (PIA-SCP). The comparative study includes PIA-SCP, PIA-QP and two commonly used approaches from the literature: static optimisation (SO) and computed muscle control (CMC). SO and CMC make simplifying assumptions to limit the computational time. Both methods minimise an instantaneous performance criterion. Furthermore, SO does not impose muscle physiology. All methods are applied to a gait cycle of six control subjects. The relative root mean square error averaged over all subjects, ε(RMS), between the joint torques simulated from the optimised activations and the joint torques obtained from the inverse dynamic analysis was about twice as large for SO (ε(RMS) = 86) as compared with CMC (ε(RMS) = 39) and PIA-SCP (ε(RMS) = 50). ε(RMS) was at least twice as large for PIA-QP (ε(RMS) = 197) than for all other methods. As compared with CMC, muscle activation patterns predicted by PIA-SCP better agree with experimental electromyography (EMG). This study shows that imposing muscle physiology as well as globally optimising performance is important to accurately calculate MT forces underlying gait.     

Two-dimensional separation of human plasma proteins using iterative free-flow electrophoresis

Blood plasma is the most complex human-derived proteome, containing other tissue proteomes as subsets. This proteome has only been partially characterized due to the extremely wide dynamic range of the plasma proteins of more than ten orders of magnitude. Thus, the reduction in sample complexity prior to mass spectrometric analysis is particularly important and alternative separation methodologies are required to more effectively mine the lower abundant plasma proteins. Here, we demonstrated a novel separation approach using 2-D free-flow electrophoresis (FFE) separating proteins and peptides in solution according to their pI prior to LC-MS/MS. We used the combination of sequential protein and peptide separation by first separating the plasma proteins into specific FFE fractions. Tryptic digests of the separated proteins were generated and subsequently separated using FFE. The protein separation medium was optimized to segregate albumin into specific fractions containing only few other proteins. An optimization of throughput for the protein separation reduced the separation time of 1 mL of plasma to approximately 3 h providing sufficient material for digestion and the subsequent peptide separation. Our approach revealed low-abundant proteins (e.g., L-selectin at 17 ng/mL and vascular endothelial-cadherin precursor at 30 ng/mL) and several tissue leakage products, thus providing a powerful orthogonal separation step in the proteomics workflow.     

Quantitative gait evaluation of hip diseases using principal component analysis

The measurement of five gait parameters, namely, joint angular displacement of lower extremities, floor reaction forces, trajectory for a point of force application, temporal factor and distance factor has been performed with ease and high speed using mini-computer on-line real-time processing. Gait data of 211 patients with hip diseases was normalized, quantified and summarized by the principal component analysis. A 'gait evaluation plane' was formed according to the results obtained by the principal component analysis. The gait evaluation using the plane was compared with clinical conditions of patients, and it was evident that this system can evaluate the recovery of the gait by treatment.     

A computational model for dynamic analysis of the human gait

Biomechanical models are important tools in the study of human motion. This work proposes a computational model to analyse the dynamics of lower limb motion using a kinematic chain to represent the body segments and rotational joints linked by viscoelastic elements. The model uses anthropometric parameters, ground reaction forces and joint Cardan angles from subjects to analyse lower limb motion during the gait. The model allows evaluating these data in each body plane. Six healthy subjects walked on a treadmill to record the kinematic and kinetic data. In addition, anthropometric parameters were recorded to construct the model. The viscoelastic parameter values were fitted for the model joints (hip, knee and ankle). The proposed model demonstrated that manipulating the viscoelastic parameters between the body segments could fit the amplitudes and frequencies of motion. The data collected in this work have viscoelastic parameter values that follow a normal distribution, indicating that these values are directly related to the gait pattern. To validate the model, we used the values of the joint angles to perform a comparison between the model results and previously published data. The model results show a same pattern and range of values found in the literature for the human gait motion.     

Footprint analysis of gait using a pressure sensor system.

The purpose of this study was to investigate if the detailed pressure data of the footprints of normal gait add essential information to the spatio-temporal variables of gait. The gait of 62 healthy adult subjects was investigated using GAITRite pressure sensor system. Each footprint was divided into 12 equal trapezoids and after that the hindfoot, midfoot and forefoot analysis was developed. A typical activation pattern of the sensors with two peaks of active area and peak pressure distribution during normal walking was obtained. The first peak reflected the heel strike, and the second peak reflected push-off at the end of the stance phase. The lowest pressure values were in the midfoot, where the lateral part of the foot activated sensors more than the medial part. The footprint patterns of right and left legs were symmetrical and corresponded with the symmetry found in the spatio-temporal variables of gait. The variability for the active area and the peak pressure were more pronounced for the lateral part of the midfoot and a smaller variation was seen in areas with concentrated observations (e.g. 1st, 2nd and 5th lateral trapezoids). Increasing active area in the forefoot was associated with decreasing pressure sensor activity in the midfoot. The footprint patterns identified the symmetry between the legs and at the same time revealed the velocity performance.     

Using an extended kalman filter for rigid body pose estimation

Rigid body pose is commonly represented as the rigid body transformation from one (often reference) pose to another This is usually computed for each frame of data without any assumptions or restrictions on the temporal change of the pose. The most common algorithm was proposed by S?derkvist and Wedin (1993, "Determining the Movements of the Skeleton Using Well-configured Markers," J. Biomech., 26, pp. 1473-1477), and implies the assumption that measurement errors are isotropic and homogenous. This paper describes an alternative method based on a state space formulation and the application of an extended Kalman filter (EKF). State space models are formulated, which describe the kinematics of the rigid body. The state vector consists of six generalized coordinates (corresponding to the 6 degrees of freedom), and their first time derivatives. The state space models have linear dynamics, while the measurement function is a non-linear relation between the state vector and the observations (marker positions). An analytical expression for the linearized measurement function is derived. Tracking the rigid body motion using an EKF enables the use of a priori information on the measurement noise and type of motion to tune the filter. The EKF is time variant, which allows for a natural way of handling temporarily missing marker data. State updates are based on all the information available at each time step, even when data from fewer than three markers are available. Comparison with the method of S?derkvist and Wedin on simulated data showed a considerable improvement in accuracy with the proposed EKF method when marker data was temporarily missing. The proposed method offers an improvement in accuracy of rigid body pose estimation by incorporating knowledge of the characteristics of the movement and the measurement errors. Analytical expressions for the linearized system equations are provided, which eliminate the need for approximate discrete differentiation and which facilitate a fast implementation.     

基于高分辨率网络的大熊猫姿态估计方法

对圈养大熊猫(Ailuropoda melanoleuca)开展长期行为监测能及时了解其所处生理周期和健康状况,有助于繁殖饲养机构迅速采取相应繁育保护措施提高饲养管理水平,但目前无法对大熊猫进行24 h监控并及时地获得相应的行为信息。准确的动物姿态估计是动物行为研究的关键,也是诸多下游应用的基础。了解大熊猫的姿态可以促进大熊猫行为研究并提升保护管理水平。为了提高复杂环境下大熊猫姿态估计的准确率,本文以高分辨率网络(High resolution net,HRNet)为基础网络架构提出了一种大熊猫姿态估计方法:针对大熊猫不同部位尺度差异较大的问题,在HRNet-32中引入了空洞空间金字塔池化(Atrous spatial pyramid pooling,ASPP)模块,在提升特征感受野的同时捕获多尺度信息;同时对大熊猫身体关键点进行分组,引入基于部位的多分支结构来学习特定于每个部位组的表征。多次对比实验结果表明本文所用模型具有较高的检测精度:在PCK@0.05中所用模型精度达到了81.51%。本文提出的方法可为大熊猫的行为分析和健康评估提供技术支撑。     

Two-dimensional HPLC on-line analysis of phosphopeptides using titania and monolithic columns

Conventional and comprehensive two-dimensional (2D) HPLC systems using the combination of titania and monolithic columns were established for the on-line analysis of phosphopeptides. Compared with immobilized metal affinity chromatography of a general method for the analysis of phosphopeptides, the use of titania columns in the analysis permits the specific isolation of phosphopeptides in a higher yield. Using the current 2D HPLC systems, phosphopeptides were specifically isolated from nonphosphorylated peptides by the first-dimension titania column, followed by the high-speed separation of the phosphopeptides by the second-dimension monolithic column. Proteolytic digests of beta-casein were analyzed within 30 min using the comprehensive 2D HPLC system; all phosphopeptides from beta-casein could be efficiently isolated and identified by matrix-assisted laser desorption/ionization time-of-flight mass spectrometry. The comprehensive 2D HPLC system coupled with mass spectrometry will be useful for high-throughput and on-line phosphoproteome analyses.     

On the estimation of joint kinematics during gait.

In gait analysis, the concepts of Euler and helical (screw) angles are used to define the three-dimensional relative joint angular motion of lower extremities. Reliable estimation of joint angular motion depends on the accurate definition and construction of embedded axes within each body segment. In this paper, using sensitivity analysis, we quantify the effects of uncertainties in the definition and construction of embedded axes on the estimation of joint angular motion during gait. Using representative hip and knee motion data from normal subjects and cerebral palsy patients, the flexion-extension axis is analytically perturbed +/- 15 degrees in 5 degrees steps from a reference position, and the joint angles are recomputed for both Euler and helical angle definitions. For the Euler model, hip and knee flexion angles are relatively unaffected while the ab/adduction and rotation angles are significantly affected throughout the gait cycle. An error of 15 degrees in the definition of flexion-extension axis gives rise to maximum errors of 8 and 12 degrees for the ab/adduction angle, and 10-15 degrees for the rotation angles at the hip and knee, respectively. Furthermore, the magnitude of errors in ab/adduction and rotation angles are a function of the flexion angle. The errors for the ab/adduction angles increase with increasing flexion angle and for the rotation angle, decrease with increasing flexion angle. In cerebral palsy patients with flexed knee pattern of gait, this will result in distorted estimation of ab/adduction and rotation. For the helical model, similar results are obtained for the helical angle and associated direction cosines.(ABSTRACT TRUNCATED AT 250 WORDS)     

Reliability of segmental accelerations measured using a new wireless gait analysis system

The purpose of this study was to determine the inter- and intra-examiner reliability, and stride-to-stride reliability, of an accelerometer-based gait analysis system which measured 3D accelerations of the upper and lower body during self-selected slow, preferred and fast walking speeds. Eight subjects attended two testing sessions in which accelerometers were attached to the head, neck, lower trunk, and right shank. In the initial testing session, two different examiners attached the accelerometers and performed the same testing procedures. A single examiner repeated the procedure in a subsequent testing session. All data were collected using a new wireless gait analysis system, which features near real-time data transmission via a Bluetooth network. Reliability for each testing condition (4 locations, 3 directions, 3 speeds) was quantified using a waveform similarity statistic known as the coefficient of multiple determination (CMD). CMD's ranged from 0.60 to 0.98 across all test conditions and were not significantly different for inter-examiner (0.86), intra-examiner (0.87), and stride-to-stride reliability (0.86). The highest repeatability for the effect of location, direction and walking speed were for the shank segment (0.94), the vertical direction (0.91) and the fast walking speed (0.91), respectively. Overall, these results indicate that a high degree of waveform repeatability was obtained using a new gait system under test-retest conditions involving single and dual examiners. Furthermore, differences in acceleration waveform repeatability associated with the reapplication of accelerometers were small in relation to normal motor variability.     

Missing inventory estimation tool using extended input-output analysis

Intention, Goal, Scope, Background  Input-Output Analysis (IOA) has recently been introduced to Life Cycle Assessment (LCA). In applying IOA to LCA studies, however, it is important to note that there are both advantages and disadvantages. Objectives  This paper aims to provide a better understanding of the advantages and disadvantages of adopting IOA in LCA, and introduces the methodology and principles of the Missing Inventory Estimation Tool (MIET) as one of the approaches to combine the strengths of process-specific LCA and IOA. Additionairy, we try to identify a number of possible errors in the use of IOA for LCA purposes, due to confusion between industry output and commodity, consumer’s price and producer’s price. Method  MIET utilises the 1996 US input-output table and various environmental statistics. It is based on an explicit distinction between commodity and industry output. Results and Discussion  MIET is a self-contained, publicly available database which can be applied directly in LCA studies to estimate missing processes. Conclusion  By adopting MILT results in existing, process-based, life-cycle inventory (LCI), LCA practitioners can fully utilise the process-specific information while expanding the system boundary. Recommendations and Outlook  MIET will be continuously updated to reflect both methodological developments and newly available data sources. For supporting information sec http:// wwwJeidenuniv.nl/cml/ssp/softwarc/miet.