Biplane Fluoroscopy for Hindfoot Motion Analysis during Gait: A Model-based Evaluation

The purpose of this study was to quantify the accuracy and precision of a biplane fluoroscopy system for model-based tracking of in vivo hindfoot motion during over-ground gait. Gait was simulated by manually manipulating a cadaver foot specimen through a biplane fluoroscopy system attached to a walkway. Three 1.6-mm diameter steel beads were implanted into the specimen to provide marker-based tracking measurements for comparison to model-based tracking. A CT scan was acquired to define a gold standard of implanted bead positions and to create 3D models for model-based tracking. Static and dynamic trials manipulating the specimen through the capture volume were performed. Marker-based tracking error was calculated relative to the gold standard implanted bead positions. The bias, precision, and root-mean-squared (RMS) error of model-based tracking was calculated relative to the marker-based measurements. The overall RMS error of the model-based tracking method averaged 0.43 ± 0.22 mm and 0.66 ± 0.43° for static and 0.59 ± 0.10 mm and 0.71 ± 0.12° for dynamic trials. The model-based tracking approach represents a non-invasive technique for accurately measuring dynamic hindfoot joint motion during in vivo, weight bearing conditions. The model-based tracking method is recommended for application on the basis of the study results

Development of a Planar Piecewise Continuous Lumped Muscle Parameter Model for Investigation of Joint Stiffness in Walking on a Level Surface

When joint stiffnesses are affected by injuries or illnesses they can interfere with gait and with activities of daily living, work, and leisure. Biomechanical models have been proposed for describing the effects of various conditions and interventions on the phases of gait. This dissertation reports the development of a planar piecewise continuous lumped muscle parameter (PPCLMP) model for investigating how different joint stiffnesses affect the gait phases individually and collectively. The proposed PPCLMP model characterizes the movements of lower limbs during each gait phase by a simplified dynamic system: the single stance phase by an inverted pendulum, the double stance phase by a kinematic chain, and the swing phase by a double pendulum. The model uses lumped muscle parameters to characterize the joint torques during each phase. The phase continuity is achieved by setting the joint angles and angular velocities at the end of one phase equal to those at the start of the next phase. The model can predict gait movements from given initial conditions (initial joint angles and angular velocities), anthropometry, lumped muscle parameters, and joint stiffness in a forward-dynamic mode. Also, if the gait movements are known, the model could estimate the lumped muscle parameters in an inverse dynamic mode. In the first study, the model was used in the forward-dynamic mode to predict joint angles and gait parameters for six healthy subjects’ anthropometry, ankle joint stiffnesses (without ankle-foot orthosis (AFO), with a low-stiffness AFO, and with a high-stiffness AFO), initial conditions, and constant lumped muscle parameters. Results showed that the trend of gait parameters changings (longer step length and shorter swing time on the AFO side for higher AFO stiffness) with different AFO stiffnesses were qualitatively well predicted by the model but quantitative prediction accuracy was limited (the mean errors were 0.15 m and 5% for the predicted step length and swing time, respectively) due to the constant values of lump muscle parameters. The second study examined the use of the model in an inverse-dynamic mode using data from a single inertial measurement unit (IMU) attached to the lower shank in order to estimate the initial conditions and lumped muscle parameters for each gait cycle. These were used by the model in the forward-dynamic mode to enhance the gait prediction. Results from two patients wearing AFOs demonstrated that the model prediction was markedly improved comparing with the first study by utilizing the inverse-dynamic mode as the mean RMSE was 0.07 m and 2% for predicted step length and swing time, respectively. The third study investigated the PPCLMP model prediction accuracy using the inverse and forward dynamic processes proposed in the second study. Three male and three female healthy subjects were recruited to walk with IMU-instrumented AFOs on their left feet to measure step lengths and swing time, while surface electrodes measured selected muscle activities for comparison with lumped muscle parameters. Results showed that the model prediction accuracy of step lengths and walking speed improved significantly (p < 0.05) with increasing stature; however, model prediction accuracy of swing time unaffected by stature. It was concluded that the PPCLMP model of gait has the potential for predicting how the prescription of an AFO of a given stiffness will affect gait, but more research is needed to refine model predictions by improving the representation of joint torques during gait.PHDIndustrial & Operations EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/163175/1/qifu_1.pd

The relationship between foot arch measurements and walking parameters in children

BACKGROUND: Walking mechanics are influenced by body morphology. Foot arch height is one aspect of body morphology central to walking. However, generalizations about the relationship between arch height and walking are limited due to previous methodologies used for measuring the arch and the populations that have been studied. To gain the knowledge needed to support healthy gait in children and adults, we need to understand this relationship in unimpaired, typically developing children and adults using dynamic measures. The purpose of the current study was to examine the relationship between arch height and gait in a sample of healthy children and adults using dynamic measures. METHODS: Data were collected from 638 participants (n = 254 children and n = 384 adults) at the Museum of Science, Boston (MOS) and from 18 4- to 8-year-olds at the Motor Development and Motor Control Laboratories. Digital footprints were used to calculate two arch indices: the Chippaux-Smirak (CSI) and the Keimig Indices (KI). The height of the navicular bone was measured. Gait parameters were captured with a mechanized gait carpet at the MOS and three-dimensional motion analyses and in-ground force plates in the Motor Development and Motor Control Laboratories. RESULTS: Linear regression analyses on data from the MOS confirmed that as age increases, step length increases. With a linear mixed effect regression model, we found that individuals who took longer steps had higher arches as measured by the KI. However, this relationship was no longer significant when only adults were included in the model. A model restricted to children found that amongst this sample, those with higher CSI and higher KI values take longer relative step lengths. Data from the Motor Development and Motor Control Laboratories showed that both CSI and KI added to the prediction; children with lower anterior ground reaction forces had higher CSI and higher KI values. Arch height indices were correlated with navicular height. CONCLUSIONS: These results suggest that more than one measure of the arch may be needed elucidate the relationship between arch height and gait.K12 HD055931 - NICHD NIH HHS; K12HD055931 - NICHD NIH HH

Automated quantitative gait analysis in animal models of movement disorders

<p>Abstract</p> <p>Background</p> <p>Accurate and reproducible behavioral tests in animal models are of major importance in the development and evaluation of new therapies for central nervous system disease. In this study we investigated for the first time gait parameters of rat models for Parkinson's disease (PD), Huntington's disease (HD) and stroke using the Catwalk method, a novel automated gait analysis test. Static and dynamic gait parameters were measured in all animal models, and these data were compared to readouts of established behavioral tests, such as the cylinder test in the PD and stroke rats and the rotarod tests for the HD group.</p> <p>Results</p> <p>Hemiparkinsonian rats were generated by unilateral injection of the neurotoxin 6-hydroxydopamine in the striatum or in the medial forebrain bundle. For Huntington's disease, a transgenic rat model expressing a truncated huntingtin fragment with multiple CAG repeats was used. Thirdly, a stroke model was generated by a photothrombotic induced infarct in the right sensorimotor cortex. We found that multiple gait parameters were significantly altered in all three disease models compared to their respective controls. Behavioural deficits could be efficiently measured using the cylinder test in the PD and stroke animals, and in the case of the PD model, the deficits in gait essentially confirmed results obtained by the cylinder test. However, in the HD model and the stroke model the Catwalk analysis proved more sensitive than the rotarod test and also added new and more detailed information on specific gait parameters.</p> <p>Conclusion</p> <p>The automated quantitative gait analysis test may be a useful tool to study both motor impairment and recovery associated with various neurological motor disorders.</p

Optimality Principles for Model-Based Prediction of Human Gait

Although humans have a large repertoire of potential movements, gait patterns tend to be stereotypical and appear to be selected according to optimality principles such as minimal energy. When applied to dynamic musculoskeletal models such optimality principles might be used to predict how a patient\u27s gait adapts to mechanical interventions such as prosthetic devices or surgery. In this paper we study the effects of different performance criteria on predicted gait patterns using a 2D musculoskeletal model. The associated optimal control problem for a family of different cost functions was solved utilizing the direct collocation method. It was found that fatigue-like cost functions produced realistic gait, with stance phase knee flexion, as opposed to energy-related cost functions which avoided knee flexion during the stance phase. We conclude that fatigue minimization may be one of the primary optimality principles governing human gait

Nonlinear vibration and dynamics of ceramic on ceramic artificial hip joints : a spatial multibody modelling

The present study investigates nonlinear vibration and dynamic behaviour of a ceramic on ceramic hip implant. The aim of this research is to firstly gain a better understanding of hip squeaking and vibration and secondly to investigate the effect of friction on contact point path during normal gait. For this purpose, a spatial multibody dynamic hip model was developed, using a friction-velocity constitutive law combined with a Hertzian contact model. Furthermore, the physiological three-dimensional rotation angles and forces are taken into account to calculate tangential and normal contact forces, respectively. Comparing the outcomes with that available in the literature allowed for the validation of our approach. It was shown that the cause of hip squeaking is friction-induced vibration owing to different phenomena such as stick-slip friction, negative-sloping friction and contact force changes. Moreover, friction-induced vibration does significantly change contact point path during the gait when compared to non-friction analysis.Fundação para a Ciência e a Tecnologia (FCT

Gait dynamic stability analysis and motor control prediction for varying terrain conditions

This work presents the gait dynamic stability modelling for different walking terrains adopted by the motor. The sensory-motor transitional gait assessment is difficult in clinical environment in case of disorders. The aim of present study was to model and analyse dynamic stability thresholds for gait transitional phases. Experimental data were collected from four healthy subjects while walking on a force platform placed at ramp and level ground walking tracks. The rate-dependent variations in the center of pressure (COP) and ground reaction forces (GRF) were modelled as motor output and input responses. Finite difference and non-linear regression algorithms were implemented to model gait transitions. Dynamic stability estimation for ramp and level ground walking were performed by analysis in time and frequency domains. Our investigation provided interesting results; 1) the overdamped motor output response acts as a compensator for instabilities and oscillations in unloading phase and initial contact, and 2) prediction of ramp ascend walking as the least stable gait than ramp descend for healthy subjects

A DYNAMICS-BASED FIDELITY ASSESSMENT OF PARTIAL GRAVITY GAIT SIMULATION USING UNDERWATER BODY SEGMENT BALLASTING

In-water testing is frequently used to simulate reduced gravity for quasi-static tasks. For dynamic motions, however, the assumption has been that drag effects invalidate any data, and in-water testing has been dismissed in favor of complex and restrictive techniques such as counterweight suspension and parabolic flight. In this study, motion-capture was used to estimate treadmill gait metrics for three environments: underwater and ballasted to 1 g and to 1/6th g, and on dry land at 1 g. Ballast was distributed anthropometrically. Motion-capture results were compared with those for a simulated dynamic walker/runner, and used to assess the effect of the in-water environment on simulation fidelity. For each test case, the model was tuned to the subject's anthropometry, and stride length, pendulum frequency, and hip displacement were computed. In-water environmental effects were found to be sufficiently quantifiable to justify using in-water testing, under certain conditions, to study partial-gravity gait dynamics

Comparison of lower body segment alignment of elite level hockey players to age-matched non-hockey players

Master's Project (M.A.) University of Alaska Fairbanks, 2015Lower body overuse and insidious onset injuries are thought to have an underlying biomechanical component which may be predisposing to injury. The purpose of this study was to compare lower body biomechanical characteristics for elite hockey players to matched controls. I hypothesize that elite hockey players have a greater degree of anterior pelvic tilt, greater varus knee angle, a higher foot arch and feet held in parallel more during gait than a matched non-skating population. Measures were taken of elite level, college aged, male hockey players and compared to cross country runners (ten subjects in each group) who served as controls for trunk angle, pelvic tilt angle, knee alignment, (varus/valgus angle), foot angle, arch index (arch height), hip, center of range of motion, hip external rotation, hip internal rotation, hip total range of motion (ROM), knee transverse plane ROM, and step width. The results obtained support the hypothesis for anterior pelvic tilt and foot angle during gait. Although knee angle was in the expected varus direction it was not significant and no differences were observed in the foot arch between the groups. All other measurements not directly related to the hypothesis were not significantly different with the exception of mean step width. The obtained results are important as recent literature describes a lower body posture of medial collapse into "dynamic valgus" as being predisposing to injury. Results show, on the spectrum from lower body varus to lower body valgus, hockey players are on the varus side of the spectrum in all attributes except arch height, which was similar in both populations. Since lower body alignment is thought to be coupled, this inconsistency appears contrary to the "medial collapse into dynamic valgus" model and may explain why foot orthotics and athletic shoes used as an injury intervention often fail