Bone position estimation from skin marker co-ordinates using global optimisation with joint constraints

Widespread use of gait or motion analysis in the diagnosis of patients with locomotor pathology and the subsequent planning and assessment of treatment has been limited because of its reliability, particularly in evaluating frontal and transverse plane components. This is because spatial reconstruction of the musculoskeletal system and calculation of its kinematics and kinetics via a skin marker-based multi-link model are subject to marker skin movement artefacts. Traditional methods treat each body segment separately without imposing joint constraints, resulting in apparent dislocations at joints predominantly because of skin movement artefacts. An optimisation method for the determination of the positions and orientations of multi-link musculoskeletal models from marker co-ordinates is presented. It is based on the minimisation of the weighted sum of squared distances between measured and model-determined marker positions. The model imposes joint constraints. Numerical experiments were performed to show that the new method is capable of eliminating joint dislocations and giving more accurate model position and orientation estimations. It is suggested that, with joint constraints and a global error compensation scheme, the effects of measurement errors on the reconstruction of the musculoskeletal system and subsequent mechanical analyses can be reduced globally. The proposed method minimises errors in axial rotation and ab/adduction at the joints and may extend the applicability of gait analysis to clinical problems.     

Soft tissue artefacts of skin markers on the lower limb during cycling: Effects of joint angles and pedal resistance

Soft tissue artefacts (STA) are a major error source in skin marker-based measurement of human movement, and are difficult to eliminate non-invasively. The current study quantified in vivo the STA of skin markers on the thigh and shank during cycling, and studied the effects of knee angles and pedal resistance by using integrated 3D fluoroscopy and stereophotogrammetry. Fifteen young healthy adults performed stationary cycling with and without pedal resistance, while the marker data were measured using a motion capture system, and the motions of the femur and tibia/fibula were recorded using a bi-plane fluoroscopy-to-CT registration method. The STAs with respect to crank and knee angles over the pedaling cycle, as well as the within-cycle variations, were obtained and compared between resistance conditions. The thigh markers showed greater STA than the shank ones, the latter varying linearly with adjacent joint angles, the former non-linearly with greater within-cycle variability. Both STA magnitudes and within-cycle variability were significantly affected by pedal resistance (p < 0.05). The STAs appeared to be composed of one component providing the stable and consistent STA patterns and another causing their variations. Mid-segment markers experienced smaller STA ranges than those closer to a joint, but tended to have greater variations primarily associated with pedal resistance and muscle contractions. The current data will be helpful for a better choice of marker positions for data collection, and for developing methods to compensate for both stable and variation components of the STA.     

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.     

Regression techniques for the prediction of lower limb kinematics

This work presents a novel and extensive investigation of mathematical regression techniques, for the prediction of laboratory-type kinematic measurements during human gait, from wearable measurement devices, such as gyroscopes and accelerometers. Specifically, we examine the hypothesis of predicting the segmental angles of the legs (left and right foot, shank and thighs), from rotational foot velocities and translational foot accelerations. This first investigation is based on kinematic data emulated from motion-capture laboratory equipment. We employ eight established regression algorithms with different properties, ranging from linear methods and neural networks with polynomial support and expanded nonlinearities, to radial basis functions, nearest neighbors and kernel density methods. Data from five gait cycles of eight subjects are used to perform both inter-subject and intra-subject assessments of the prediction capabilities of each algorithm, using cross-validation resampling methods. Regarding the algorithmic suitability to gait prediction, results strongly indicate that nonparametric methods, such as nearest neighbors and kernel density based, are particularly advantageous. Numerical results show high average prediction accuracy (rho = 0.98/0.99, RMS = 5.63 degrees/2.30 degrees, MAD = 4.43 degrees/1.52 degrees for inter/intra-subject testing). The presented work provides a promising and motivating investigation on the feasibility of cost-effective wearable devices used to acquire large volumes of data that are currently collected only from complex laboratory environments.     

Estimating joint kinematics from skin motion observation: modelling and validation

Modelling of soft tissue motion is required in many areas, such as computer animation, surgical simulation, 3D motion analysis and gait analysis. In this paper, we will focus on the use of modelling of skin deformation during 3D motion analysis. The most frequently used method in 3D human motion analysis involves placing markers on the skin of the analysed segment which is composed of the rigid bone and the surrounding soft tissues. Skin and soft tissue deformations introduce a significant artefact which strongly influences the resulting bone position, orientation and joint kinematics. For this study, we used a statistical solid dynamics approach which is a combination of several previously reported tools: the point cluster technique (PCT) and a Kalman filter which was added to the PCT. The methods were tested and evaluated on controlled human-arm motions, using an optical motion capture system (Vicon^TM).

The addition of a Kalman filter to the PCT for rigid body motion estimation results in a smoother signal that better represents the joint motion. Calculations indicate less signal distortion than when using a digital low-pass filter. Furthermore, adding a Kalman filter to the PCT substantially reduces the dispersion of the maximal and minimal instantaneous frequencies. For controlled human movements, the result indicated that adding a Kalman filter to the PCT produced a more accurate signal. However, it could not be concluded that the proposed Kalman filter is better than a low-pass filter for estimation of the motion. We suggest that implementation of a Kalman filter with a better biomechanical motion model will be more likely to improve the results.     

Estimating joint kinematics from skin motion observation: modelling and validation

Modelling of soft tissue motion is required in many areas, such as computer animation, surgical simulation, 3D motion analysis and gait analysis. In this paper, we will focus on the use of modelling of skin deformation during 3D motion analysis. The most frequently used method in 3D human motion analysis involves placing markers on the skin of the analysed segment which is composed of the rigid bone and the surrounding soft tissues. Skin and soft tissue deformations introduce a significant artefact which strongly influences the resulting bone position, orientation and joint kinematics. For this study, we used a statistical solid dynamics approach which is a combination of several previously reported tools: the point cluster technique (PCT) and a Kalman filter which was added to the PCT. The methods were tested and evaluated on controlled human-arm motions, using an optical motion capture system (Vicon(TM)). The addition of a Kalman filter to the PCT for rigid body motion estimation results in a smoother signal that better represents the joint motion. Calculations indicate less signal distortion than when using a digital low-pass filter. Furthermore, adding a Kalman filter to the PCT substantially reduces the dispersion of the maximal and minimal instantaneous frequencies. For controlled human movements, the result indicated that adding a Kalman filter to the PCT produced a more accurate signal. However, it could not be concluded that the proposed Kalman filter is better than a low-pass filter for estimation of the motion. We suggest that implementation of a Kalman filter with a better biomechanical motion model will be more likely to improve the results.     

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)     

An estimation of joint kinematics for a standing reach task using ground reaction data

The objective of this work was to derive a procedure able to estimate joint kinematics, relative to a simple, yet functionally relevant, motor task, starting from ground reaction data. The minimum number of input data has been used: force platform data, few and simple measurements relative to the subject, and protocol-specific parameters. Standing reach (SR) is the motor task analysed. The biomechanical model is a two degrees-of-freedom inverted pendulum moving on the vertical sagittal plane. Joint kinematics has been estimated solving the related direct dynamic problem stated in function of ground reaction data. The original nonlinear differential equation system of the model showed a high sensitivity to errors affecting initial conditions and experimental input data. Consequently, an approximate solution has been looked for in order to reduce the coupling between the model differential equations. This was possible taking into account the peculiar characteristics of the motor task. An optimization procedure has been deemed necessary in order to minimize the effects of the assumed approximation. The method has been tested both with simulated and with experimental data. In this latter case the validation of the angular kinematics estimated by the proposed method has been performed by means of data obtained by a stereophotogrammetric system. Results show a satisfactory behaviour of the whole optimization procedure. Very good results have been obtained in the case of slow reaching tasks.     

Ground reaction force estimation using an insole-type pressure mat and joint kinematics during walking

Kinetic analysis of walking requires joint kinematics and ground reaction force (GRF) measurement, which are typically obtained from a force plate. GRF is difficult to measure in certain cases such as slope walking, stair climbing, and track running. Nevertheless, estimating GRF continues to be of great interest for simulating human walking. The purpose of the study was to develop reaction force models placed on the sole of the foot to estimate full GRF when only joint kinematics are provided (Type-I), and to estimate ground contact shear forces when both joint kinematics and foot pressure are provided (Type-II and Type-II-val). The GRF estimation models were attached to a commercial full body skeletal model using the AnyBody Modeling System, which has an inverse dynamics-based optimization solver. The anterior–posterior shear force and medial–lateral shear force could be estimated with approximate accuracies of 6% BW and 2% BW in all three methods, respectively. Vertical force could be estimated in the Type-I model with an accuracy of 13.75% BW. The accuracy of the force estimation was the highest during the mid-single-stance period with an average RMS for errors of 3.10% BW, 1.48% BW, and 7.48% BW for anterior–posterior force, medial–lateral force, and vertical force, respectively. The proposed GRF estimation models could predict full and partial GRF with high accuracy. The design of the contact elements of the proposed model should make it applicable to various activities where installation of a force measurement system is difficult, including track running and treadmill walking.     

The effects of alignment of an articulated ankle-foot orthosis on lower limb joint kinematics and kinetics during gait in individuals post-stroke

Mechanical tuning of an ankle-foot orthosis (AFO) is important in improving gait in individuals post-stroke. Alignment and resistance are two factors that are tunable in articulated AFOs. The aim of this study was to investigate the effects of changing AFO ankle alignment on lower limb joint kinematics and kinetics with constant dorsiflexion and plantarflexion resistance in individuals post-stroke. Gait analysis was performed on 10 individuals post-stroke under four distinct alignment conditions using an articulated AFO with an ankle joint whose alignment is adjustable in the sagittal plane. Kinematic and kinetic data of lower limb joints were recorded using a Vicon 3-dimensional motion capture system and Bertec split-belt instrumented treadmill. The incremental changes in the alignment of the articulated AFO toward dorsiflexion angles significantly affected ankle and knee joint angles and knee joint moments while walking in individuals post-stroke. No significant differences were found in the hip joint parameters. The alignment of the articulated AFO was suggested to play an important role in improving knee joint kinematics and kinetics in stance through improvement of ankle joint kinematics while walking in individuals post-stroke. Future studies should investigate long-term effects of AFO alignment on gait in the community in individuals post-stroke.     

Evaluation of the global optimisation method within the upper limb kinematics analysis

The aim of this study is to assess the performances of the global optimisation (GO) method (Bone position estimation from skin marker co-ordinates using GO with joint constraints. Journal of Biomechanics 32, 129-134) within the upper limb kinematics analysis. First the model of the upper limb is presented. Then we apply GO method in order to reduce skin movement artefacts that imply relative movement between markers and bones. The performances of the method are then evaluated with the help of simulated movements of the upper limb. Results show a significant reduction of the errors and of the variability due to skin movement.     

Influence of saddle height on lower limb kinematics in well-trained cyclists: static vs. Dynamic evaluation in bike fitting

ABSTRACT: Ferrer-Roca, V, Roig, A, Galilea, P, and García-López, J. Influence of saddle height on lower limb kinematics in well-trained cyclists: Static vs. dynamic evaluation in bike fitting. J Strength Cond Res 26(11): 3025-3029, 2012-In cycling, proper saddle height is important because it contributes to the mechanical work of the lower limb joints, thus altering pedaling efficiency. The appropriate method to select optimal saddle height is still unknown. This study was conducted to compare a static (anthropometric measurements) vs. a dynamic method (2D analysis) to adjust saddle height. Therefore, an examination of the relationship between saddle height, anthropometrics, pedaling angles, and hamstring flexibility was carried out. Saddle height outside of the recommended range (106-109% of inseam length) was observed in 56.5% of the subjects. Inappropriate knee flexion angles using the dynamic method were observed in 26% of subjects. The results of this study support the concept that adjusting saddle height to 106-109% of inseam length may not ensure an optimal knee flexion (30-40°). To solve these discrepancies, we applied a multiple linear regression to study the relationship between anthropometrics, pedaling angles, and saddle height. The results support the contention that saddle height, inseam length, and knee angle are highly related (R = 0.963, p < 0.001). We propose a novel equation that relates these factors to recommend an optimal saddle height (108.6-110.4% of inseam length).     

Kinematics estimation of straddled movements on high bar from a limited number of skin markers using a chain model

To reduce the effects of skin movement artefacts and apparent joint dislocations in the kinematics of whole body movement derived from marker locations, global optimisation procedures with a chain model have been developed. These procedures can also be used to reduce the number of markers when self-occlusions are hard to avoid. This paper assesses the kinematics precision of three marker sets: 16, 11 and 7 markers, for movements on high bar with straddled piked posture. A three-dimensional person-specific chain model was defined with 9 parameters and 12 degrees of freedom and an iterative procedure optimised the gymnast posture for each frame of the three marker sets. The time histories of joint angles obtained from the reduced marker sets were compared with those from the 16 marker set by means of a root mean square difference measure. Occlusions of medial markers fixed on the lower limb occurred when the legs were together and the pelvis markers disappeared primarily during the piked posture. Despite these occlusions, reconstruction was possible with 16, 11 and 7 markers. The time histories of joint angles were similar; the main differences were for the thigh mediolateral rotation and the knee flexion because the knee was close to full extension. When five markers were removed, the average angles difference was about 3 degrees . This difference increased to 9 degrees for the seven marker set. It is concluded that kinematics of sports movement can be reconstructed using a chain model and a global optimisation procedure for a reduced number of markers.     

Effects of vibration intensity on lower limb joint moments during standing

Muscle activity and joint moment of the lower limbs can provide different information about the stimulation of controlled whole-body vibration (CWBV) on human body. Previous studies investigated the immediate effects of the intensity of CWBV on enhancing lower-limb muscle activity. However, no study has examined the possible influence of CWBV intensity on joint loading. It remains unexplored how CWBV intensity impacts joint loading. This study was carried out (1) to quantify the effects of CWBV intensity in terms of vibration frequency and amplitude on the lower limb joint moments and (2) to examine the relationship between leg joint moments and vibration intensity characterized by the platform’s acceleration, that is determined by frequency and amplitude, during standing among young adults. Thirty healthy young adults participated in this study. Each participant experienced nine vibration intensity levels dependent upon the frequency (10, 20, and 30 Hz) and amplitude (1, 2, and 3 mm) while standing on a side-alternating vibration platform. Their body kinematics and vertical reaction forces between the feet and platform were collected. Inverse dynamics was employed to calculate the resultant moment for the ankle, knee, and hip joints in the sagittal plane. Our results revealed that the root-mean-square moment significantly increases with increasing vibration frequency or amplitude for all three joints. Further, all joint moments are strongly and positively correlated with the platform acceleration.     

Dynamic structure of lower limb joint angles during walking post-stroke

BackgroundVariability in joint kinematics is necessary for adaptability and response to everyday perturbations; however, intrinsic neuromotor changes secondary to stroke often cause abnormal movement patterns. How these abnormal movement patterns relate to joint kinematic variability and its influence on post-stroke walking impairments is not well understood.ObjectiveThe purpose of this study was to evaluate the movement variability at the individual joint level in the paretic and non-paretic limbs of individuals post-stroke.MethodsSeven individuals with hemiparesis post-stroke walked on a treadmill for two minutes at their self-selected speed and the average speed of the six-minute walk test while kinematics were recorded using motion-capture. Variability in hip, knee, and ankle flexion/extension angles during walking were quantified with the Lyapunov exponent (LyE). Interlimb differences were evaluated.ResultsThe paretic side LyE was higher than the non-paretic side at both self-selected speed (Hip: 50%; Knee: 74%), and the average speed of the 6-min walk test (Hip: 15%; Knee: 93%).ConclusionDifferences in joint kinematic variability between limbs of persons post-stroke supports further study of the source of non-paretic limb deviations as well as the clinical implications of joint kinematic variability in persons post-stroke. The development of bilaterally-targeted post-stroke gait interventions to address variability in both limbs may promote improved outcomes.     

Standing sway: iterative estimation of the kinematics and dynamics of the lower extremities from force-plate measurements

In this study, a model for the estimation of the dynamics of the lower extremities in standing sway from force plate data only is presented. A three-dimensional, five-segment, four-joint model of the human body was used to describe postural standing sway dynamics. Force-plate data of the reactive forces and centers of pressure were measured bilaterally. By applying the equations of motion to these data, the transversal trajectory of the center of gravity (CG) of the body was resolved in the sagittal and coronal planes. An inverse kinematics algorithm was used to evaluate the kinematics of the body segments. The dynamics of the segments was then resolved by using the Newton-Euler equations, and the model's estimated dynamic quantities of the distal segments were compared with those actually measured. Differences between model and measured dynamics were calculated and minimized, using an iterative algorithm to re-estimate joint positioning and anthropometric properties. The above method was tested with a group of 11 able-bodied subjects, and the results indicated that the relative errors obtained in the final iteration were of the same order of magnitude as those reported for closed loop problems involved in direct kinematics measurements of human gait. Received: 22 July 1997 / Accepted in revised form: 29 January 1998     

The effects of running in an exerted state on lower extremity kinematics and joint timing

Runners rarely run to the point of maximum fatigue or exhaustion. However, no studies have investigated how the level of exertion associated with a typical running session influences running mechanics. The purpose of this study was to investigate the effects that running in an exerted state had on the kinematics and joint timing within the lower extremity of uninjured, recreational runners. Twenty runners performed a prolonged treadmill run at a self-selected pace that best represented each runner’s typical training run. The run ended based on heart rate or perceived exertion levels that represented a typical training run. Kinematics and joint timing between the foot, knee, and hip were analyzed at the beginning and end of the run. Increases were primarily observed at the end of the run for the peak angles, excursions, and peak velocities of eversion, tibial internal rotation, and knee internal rotation. No differences were observed for knee flexion, hip internal rotation, or any joint timing relationship. Based on these results, runners demonstrated subtle changes in kinematics in the exerted state, most notably for eversion. However, runners were able to maintain joint timing throughout the leg, which may have been a function of the knee. Thus, uninjured runners normally experience small alterations in kinematics when running with typical levels of exertion. It remains unknown how higher levels of exertion influence kinematics with joint timing and the association with running injuries, or how populations with running injuries respond to typical levels of exertion.