Subject-specific axes of the ankle joint complex

The aim of this study was to use a two-axis ankle joint model and an optimisation process (van den Bogert et al., 1994) to calculate and compare the talocrural and subtalar hinge axes for non-weight-bearing ankle motion, weight-bearing ankle motion, and walking in normal, healthy adult subjects and to see which of the first two sets of axes better fit the walking data. Motion data for the foot and shank were collected on eight subjects whilst they performed the activities mentioned. After choosing the best marker sets for motion tracking, a two-hinge ankle joint model was fit to the motion data. Ankle joint ranges of motion were also calculated. It was found that the model fit the experimental data well, with non-weight-bearing motion achieving the best fit. Despite this, the calculated axis orientations were highly variable both between motion types and between subjects. No significant difference between the fit of the non-weight-bearing and weight-bearing models to the walking data was found, which implies that either set of functional axes is adequate for modeling walking; however, the subtalar deviation angle was significantly closer for the weight-bearing activity and walking than for the non-weight-bearing activity and walking, which suggests that it is marginally better to use the weight-bearing functional motions. The results lead to questions about the appropriateness of the two-hinge ankle model for use in applications in which the behaviour of the individual joints of the ankle complex, rather than simply the relative motion of the leg and foot, is important.     

Ankle and midfoot kinetics during normal gait: a multi-segment approach

Multi-segment foot models are increasingly being used to evaluate intra and inter-segment foot kinematics such as the motion between the hindfoot/tibia (ankle) and the forefoot/hindfoot (midfoot) during walking. However, kinetic analysis have been mainly restricted to one-segment foot models and could be improved by considering a multi-segment approach. Therefore, the aims of this study were to (1) implement a kinetic analysis of the ankle and theoretical midfoot joints using the existing Oxford Foot Model (OFM) through a standard inverse dynamics approach using only marker, force plate and anthropometric data and (2) to compare OFM ankle joint kinetics to those output by the one-segment foot plugin-gait model (PIG). 10 healthy adolescents fitted with both the OFM and PIG markers performed barefoot comfortable speed walking trials over an instrumented walkway. The maximum ankle power generation was significantly reduced by approximately 40% through OFM calculations compared to PIG estimates (p<0.001). This result was not caused by a decrease in OFM computed joint moments, but by a reduction in the angular velocity between the tibia/hindfoot (OFM) compared to the tibia/foot (PIG) (p<0.001). Additionally, analysis revealed considerable midfoot loading. One-segment foot models overestimate ankle power, and may also overestimate the contribution of the triceps surae. A multi-segment approach may help quantify the important contribution of the midfoot ligaments and musculature to power generation. We therefore recommend the use of multi-segment foot models to estimate ankle and midfoot kinetics, especially when surgical decision-making is based on the results of three-dimensional gait analysis.     

Foot modeling affects ankle sagittal plane kinematics during jump-landing

The foot-ankle complex is a key-element to mitigate impact forces during jump-landing activities. Biomechanical studies commonly model the foot as a single-segment, which can provide different ankle kinematics compared to a multi-segmented model. Also, it can neglect intersegmental kinematics of the foot-ankle joints, such as the hindfoot-tibia, forefoot-hindfoot, and hallux-forefoot joints, that are used during jump-landing activities. The purpose of this short communication was to compare ankle kinematics between a three- and single-segmented foot models, during forward and lateral single-leg jump-landings. Marker trajectories and synchronized ground reaction forces of 30 participants were collected using motion capture and a force plate, during multidirectional single-leg jump-landings. Ankle kinematics were computed using a three- (hindfoot-tibia) and a single-segmented (ankle) foot models, at initial contact (IC), peak vertical ground reaction force (PvGRF) and peak knee flexion (PKF). Repeated measures ANOVAs were conducted (p < 0.05). The findings of this study showed that during lateral and forward jump-landing directions, the three-segmented foot model exhibited lower hindfoot-tibia dorsiflexion angles (PvGRF and PKF, p < 0.001) and excursions (sagittal: p < 0.001; frontal: p < 0.05) during the weightbearing acceptance phase than the single-segmented model. Overall, the two foot models provided distinctive sagittal ankle kinematics, with lower magnitudes in the hindfoot-tibia of the three-segmented foot. Furthermore, the three-segmented foot model may provide additional and representative kinematic data of the ankle and foot joints, to better comprehend its function, particularly in populations whose foot-ankle complex plays an important role (e.g., dancers).     

A comparison of dorsal and heel plate foot tracking methods on lower extremity dynamics

The primary method to model ankle motion during inverse dynamic calculations of the lower limb is through the use of skin-mounted markers, with the foot modeled as a rigid segment. Motion of the foot is often tracked via the use of a marker cluster triad on either the dorsum, or heel, of the foot/shoe. The purpose of this investigation was to evaluate differences in calculated lower extremity dynamics during the stance phase of gait between these two tracking techniques. In an analysis of 7 subjects, it was found that sagittal ankle angles and sagittal ankle, hip and knee moments were strongly correlated between the two conditions, however, there was a significant difference in peak ankle plantar flexion and dorsiflexion angles. Frontal ankle angles were only moderately correlated and there was a significant difference in peak ankle eversion and inversion, resulting in moderate correlations in frontal plane moments and a significant difference in peak hip adductor moments. We demonstrate that the technique used to track the foot is an important consideration in interpreting lower extremity dynamics for clinical and research purposes.     

A validated computational framework to evaluate the stiffness of 3D printed ankle foot orthoses

The purpose of this study was to create and validate a standardized framework for the evaluation of the ankle stiffness of two designs of 3D printed ankle foot orthoses (AFOs). The creation of four finite element (FE) models allowed patient-specific quantification of the stiffness and stress distribution over their specific range of motion during the second rocker of the gait. Validation was performed by comparing the model outputs with the results obtained from a dedicated experimental setup, which showed an overall good agreement with a maximum relative error of 10.38% in plantarflexion and 10.66% in dorsiflexion. The combination of advanced computer modelling algorithms and 3D printing techniques clearly shows potential to further improve the manufacturing process of AFOs.     

A generic analytical foot rollover model for predicting translational ankle kinematics in gait simulation studies

The objective of this paper is to develop an analytical framework to representing the ankle–foot kinematics by modelling the foot as a rollover rocker, which cannot only be used as a generic tool for general gait simulation but also allows for case-specific modelling if required. Previously, the rollover models used in gait simulation have often been based on specific functions that have usually been of a simple form. In contrast, the analytical model described here is in a general form that the effective foot rollover shape can be represented by any polar function ρ=ρ(φ). Furthermore, a normalized generic foot rollover model has been established based on a normative foot rollover shape dataset of 12 normal healthy subjects. To evaluate model accuracy, the predicted ankle motions and the centre of pressure (CoP) were compared with measurement data for both subject-specific and general cases. The results demonstrated that the ankle joint motions in both vertical and horizontal directions (relative RMSE ～10%) and CoP (relative RMSE ～15% for most of the subjects) are accurately predicted over most of the stance phase (from 10% to 90% of stance). However, we found that the foot cannot be very accurately represented by a rollover model just after heel strike (HS) and just before toe off (TO), probably due to shear deformation of foot plantar tissues (ankle motion can occur without any foot rotation). The proposed foot rollover model can be used in both inverse and forward dynamics gait simulation studies and may also find applications in rehabilitation engineering.     

Determination of dynamic ankle ligament strains from a computational model driven by motion analysis based kinematic data

External rotation of the foot has been implicated in high ankle sprains. Recent studies by this laboratory, and others, have suggested that torsional traction characteristics of the shoe-surface interface may play a role in ankle injury. While ankle injuries most often involve damage to ligaments due to excessive strains, the studies conducted by this laboratory and others have largely used surrogate models of the lower extremity to determine shoe-surface interface characteristics based on torque measures alone. The objective of this study was to develop a methodology that would integrate a motion analysis-based kinematic foot model with a computational model of the ankle to determine dynamic ankle ligament strains during external foot rotation. Six subjects performed single-legged, internal rotation of the body with a planted foot while a marker-based motion analysis was conducted to track the hindfoot motion relative to the tibia. These kinematic data were used to drive an established computational ankle model. Ankle ligament strains, as a function of time, were determined. The anterior tibiofibular ligament (ATiFL) experienced the highest strain at 9.2±1.1%, followed by the anterior deltoid ligament (ADL) at 7.8±0.7%, averaged over the six subjects. The peak ATiFL strain occurred prior to peak strain in the ADL in all subjects. This novel methodology may provide new insights into mechanisms of high ankle sprains and offer a basis for future evaluations of shoe-surface interface characteristics using human subjects rather than mechanical surrogate devices.     

Segmental motion of forefoot and hindfoot as a diagnostic tool

Segmental motions derived from non-invasive motion analysis are being used to investigate the intrinsic functional behavior of the foot and ankle in health and disease. The goal of this research was to examine the ability of a generic segmented model of the foot to capture and differentiate changes in internal skeletal kinematics due to neuromuscular disease and/or trauma. A robotic apparatus that reproduces the kinematics and kinetics of gait in cadaver lower extremities was employed to produce motion under normal and aberrant neuromuscular activation patterns of tibialis posterior and/or tibialis anterior. Stance phase simulations were conducted on 10 donor limbs while recording three-dimensional kinematic trajectories of (1) skin-mounted markers used clinically to construct segmented foot models, and (2) bone-mounted marker clusters to capture actual internal bone motion as the gold standard for comparison. The models constructed from external marker data were able to differentiate the kinematic behaviors elicited by different neuromuscular conditions in a manner similar to that using the bone-derived data. Measurable differences between internal and externally measured kinematics were small, variable and random across the three axes of rotation and neuromuscular conditions, with a tendency toward more differences noted during early and late stance. Albeit slightly different, three-dimensional motion profiles of the hindfoot and forefoot segments correlated well with internal skeletal motion under all neuromuscular conditions, thereby confirming the utility of measuring segmental motions as a valid means of clinical assessment.     

A real-time computational model for estimating kinematics of ankle ligaments

Background: An accurate assessment of ankle ligament kinematics is crucial in understanding the injury mechanisms and can help to improve the treatment of an injured ankle, especially when used in conjunction with robot-assisted therapy. A number of computational models have been developed and validated for assessing the kinematics of ankle ligaments. However, few of them can do real-time assessment to allow for an input into robotic rehabilitation programs. Method: An ankle computational model was proposed and validated to quantify the kinematics of ankle ligaments as the foot moves in real-time. This model consists of three bone segments with three rotational degrees of freedom (DOFs) and 12 ankle ligaments. This model uses inputs for three position variables that can be measured from sensors in many ankle robotic devices that detect postures within the foot–ankle environment and outputs the kinematics of ankle ligaments. Validation of this model in terms of ligament length and strain was conducted by comparing it with published data on cadaver anatomy and magnetic resonance imaging. Results: The model based on ligament lengths and strains is in concurrence with those from the published studies but is sensitive to ligament attachment positions. Conclusions: This ankle computational model has the potential to be used in robot-assisted therapy for real-time assessment of ligament kinematics. The results provide information regarding the quantification of kinematics associated with ankle ligaments related to the disability level and can be used for optimizing the robotic training trajectory.     

Development of a patient-specific anatomical foot model from structured light scan data

The use of anatomically accurate finite element (FE) models of the human foot in research studies has increased rapidly in recent years. Uses for FE foot models include advancing knowledge of orthotic design, shoe design, ankle–foot orthoses, pathomechanics, locomotion, plantar pressure, tissue mechanics, plantar fasciitis, joint stress and surgical interventions. Similar applications but for clinical use on a per-patient basis would also be on the rise if it were not for the high costs associated with developing patient-specific anatomical foot models. High costs arise primarily from the expense and challenges of acquiring anatomical data via magnetic resonance imaging (MRI) or computed tomography (CT) and reconstructing the three-dimensional models. The proposed solution morphs detailed anatomy from skin surface geometry and anatomical landmarks of a generic foot model (developed from CT or MRI) to surface geometry and anatomical landmarks acquired from an inexpensive structured light scan of a foot. The method yields a patient-specific anatomical foot model at a fraction of the cost of standard methods. Average error for bone surfaces was 2.53 mm for the six experiments completed. Highest accuracy occurred in the mid-foot and lowest in the forefoot due to the small, irregular bones of the toes. The method must be validated in the intended application to determine if the resulting errors are acceptable.     

Parametric study of orthopedic insole of valgus foot on partial foot amputation

Orthopedic insole was important for partial foot amputation (PFA) to achieve foot balance and avoid foot deformity. The inapposite insole orthosis was thought to be one of the risk factors of reamputation for foot valgus patient, but biomechanical effects of internal tissues on valgus foot had not been clearly addressed. In this study, plantar pressure on heel and metatarsal regions of PFA was measured using F-Scan. The three-dimensional finite element (FE) model of partial foot evaluated different medial wedge angles (MWAs) (0.0°–10.0°) of orthopedic insole on valgus foot. The effect of orthopedic insole on the internal bone stress, the medial ligament tension of ankle, plantar fascia tension, and plantar pressure was investigated. Plantar pressure on medial heel region was about 2.5 times higher than that of lateral region based on the F-Scan measurements. FE-predicted results showed that the tension of medial ankle ligaments was the lowest, and the plantar pressure was redistributed around the heel, the first metatarsal, and the lateral longitudinal arch regions when MWA of orthopedic insole ranged from 7.5° to 8.0°. The plantar fascias maintained about 3.5% of the total load bearing on foot. However, the internal stresses from foot bones increased. The simulation in this study would provide the suggestion of guiding optimal design of orthopedic insole and therapeutic planning to pedorthist.     

Influence of joint constraints on lower limb kinematics estimation from skin markers using global optimization

In order to obtain the lower limb kinematics from skin-based markers, the soft tissue artefact (STA) has to be compensated. Global optimization (GO) methods rely on a predefined kinematic model and attempt to limit STA by minimizing the differences between model predicted and skin-based marker positions. Thus, the reliability of GO methods depends directly on the chosen model, whose influence is not well known yet.This study develops a GO method that allows to easily implement different sets of joint constraints in order to assess their influence on the lower limb kinematics during gait. The segment definition was based on generalized coordinates giving only linear or quadratic joint constraints. Seven sets of joint constraints were assessed, corresponding to different kinematic models at the ankle, knee and hip: SSS, USS, PSS, SHS, SPS, UHS and PPS (where S, U and H stand for spherical, universal and hinge joints and P for parallel mechanism). GO was applied to gait data from five healthy males.Results showed that the lower limb kinematics, except hip kinematics, knee and ankle flexion–extension, significantly depend on the chosen ankle and knee constraints. The knee parallel mechanism generated some typical knee rotation patterns previously observed in lower limb kinematic studies. Furthermore, only the parallel mechanisms produced joint displacements.Thus, GO using parallel mechanism seems promising. It also offers some perspectives of subject-specific joint constraints.     

A musculoskeletal foot model for clinical gait analysis

Several full body musculoskeletal models have been developed for research applications and these models may potentially be developed into useful clinical tools to assess gait pathologies. Existing full-body musculoskeletal models treat the foot as a single segment and ignore the motions of the intrinsic joints of the foot. This assumption limits the use of such models in clinical cases with significant foot deformities. Therefore, a three-segment musculoskeletal model of the foot was developed to match the segmentation of a recently developed multi-segment kinematic foot model. All the muscles and ligaments of the foot spanning the modeled joints were included. Muscle pathways were adjusted with an optimization routine to minimize the difference between the muscle flexion–extension moment arms from the model and moment arms reported in literature. The model was driven by walking data from five normal pediatric subjects (aged 10.6±1.57 years) and muscle forces and activation levels required to produce joint motions were calculated using an inverse dynamic analysis approach. Due to the close proximity of markers on the foot, small marker placement error during motion data collection may lead to significant differences in musculoskeletal model outcomes. Therefore, an optimization routine was developed to enforce joint constraints, optimally scale each segment length and adjust marker positions. To evaluate the model outcomes, the muscle activation patterns during walking were compared with electromyography (EMG) activation patterns reported in the literature. Model-generated muscle activation patterns were observed to be similar to the EMG activation patterns.     

Online estimation algorithm for a biaxial ankle kinematic model with configuration dependent joint axes

The kinematics of the human ankle is commonly modeled as a biaxial hinge joint model. However, significant variations in axis orientations have been found between different individuals and also between different foot configurations. For ankle rehabilitation robots, information regarding the ankle kinematic parameters can be used to estimate the ankle and subtalar joint displacements. This can in turn be used as auxiliary variables in adaptive control schemes to allow modification of the robot stiffness and damping parameters to reduce the forces applied at stiffer foot configurations. Due to the large variations observed in the ankle kinematic parameters, an online identification algorithm is required to provide estimates of the model parameters. An online parameter estimation routine based on the recursive least-squares (RLS) algorithm was therefore developed in this research. An extension of the conventional biaxial ankle kinematic model, which allows variation in axis orientations with different foot configurations had also been developed and utilized in the estimation algorithm. Simulation results showed that use of the extended model in the online algorithm is effective in capturing the foot orientation of a biaxial ankle model with variable joint axis orientations. Experimental results had also shown that a modified RLS algorithm that penalizes a deviation of model parameters from their nominal values can be used to obtain more realistic parameter estimates while maintaining a level of estimation accuracy comparable to that of the conventional RLS routine.     

Pre-impact lower extremity posture and brake pedal force predict foot and ankle forces during an automobile collision

BACKGROUND: The purpose of this study was to determine how a driver's foot and ankle forces during a frontal vehicle collision depend on initial lower extremity posture and brake pedal force. METHOD OF APPROACH: A 2D musculoskeletal model with seven segments and six right-side muscle groups was used. A simulation of a three-second braking task found 3647 sets of muscle activation levels that resulted in stable braking postures with realistic pedal force. These activation patterns were then used in impact simulations where vehicle deceleration was applied and driver movements and foot and ankle forces were simulated. Peak rearfoot ground reaction force (F(RF)), peak Achilles tendon force (FAT), peak calcaneal force (F(CF)) and peak ankle joint force (F(AJ)) were calculated. RESULTS: Peak forces during the impact simulation were 476 +/- 687 N (F(RF)), 2934 +/- 944 N (F(CF)) and 2449 +/- 918 N (F(AJ)). Many simulations resulted in force levels that could cause fractures. Multivariate quadratic regression determined that the pre-impact brake pedal force (PF), knee angle (KA) and heel distance (HD) explained 72% of the variance in peak FRF, 62% in peak F(CF) and 73% in peak F(AJ). CONCLUSIONS: Foot and ankle forces during a collision depend on initial posture and pedal force. Braking postures with increased knee flexion, while keeping the seat position fixed, are associated with higher foot and ankle forces during a collision.     

Prediction of mortality in very premature infants: a systematic review of prediction models

Context

Being born very preterm is associated with elevated risk for neonatal mortality. The aim of this review is to give an overview of prediction models for mortality in very premature infants, assess their quality, identify important predictor variables, and provide recommendations for development of future models.

Methods

Studies were included which reported the predictive performance of a model for mortality in a very preterm or very low birth weight population, and classified as development, validation, or impact studies. For each development study, we recorded the population, variables, aim, predictive performance of the model, and the number of times each model had been validated. Reporting quality criteria and minimum methodological criteria were established and assessed for development studies.

Results

We identified 41 development studies and 18 validation studies. In addition to gestational age and birth weight, eight variables frequently predicted survival: being of average size for gestational age, female gender, non-white ethnicity, absence of serious congenital malformations, use of antenatal steroids, higher 5-minute Apgar score, normal temperature on admission, and better respiratory status. Twelve studies met our methodological criteria, three of which have been externally validated. Low reporting scores were seen in reporting of performance measures, internal and external validation, and handling of missing data.

Conclusions

Multivariate models can predict mortality better than birth weight or gestational age alone in very preterm infants. There are validated prediction models for classification and case-mix adjustment. Additional research is needed in validation and impact studies of existing models, and in prediction of mortality in the clinically important subgroup of infants where age and weight alone give only an equivocal prognosis.     

Prediction of Poor Outcome in Patients with Acute Liver Failure—Systematic Review of Prediction Models

Introduction

Acute liver failure is a rare disease with high mortality and liver transplantation is the only life saving therapy. Accurate prognosis of ALF is crucial for proper intervention.

Aim

To identify and characterize newly developed prognostic models of mortality for ALF patients, assess study quality, identify important variables and provide recommendations for the development of improved models in the future.

Methods

The online databases MEDLINE® (1950–2012) and EMBASE® (1980–2012) were searched for English-language articles that reported original data from clinical trials or observational studies on prognostic models in ALF patients. Studies were included if they developed a new model or modified existing prognostic models. The studies were evaluated based on an existing framework for scoring the methodological and reporting quality of prognostic models.

Results

Twenty studies were included, of which 18 reported on newly developed models, 1 on modification of the Kings College Criteria (KCC) and 1 on the Model for End-Stage Liver Disease (MELD). Ten studies compared the newly developed models to previously existing models (e.g. KCC); they all reported that the new models were superior. In the 12-point methodological quality score, only one study scored full points. On the 38-point reporting score, no study scored full points. There was a general lack of reporting on missing values. In addition, none of the studies used performance measures for calibration and accuracy (e.g. Hosmer-Lemeshow statistics, Brier score), and only 5 studies used the AUC as a measure of discrimination.

Conclusions

There are many studies on prognostic models for ALF but they show methodological and reporting limitations. Future studies could be improved by better reporting and handling of missing data, the inclusion of model calibration aspects, use of absolute risk measures, explicit considerations for variable selection, the use of a more extensive set of reference models and more thorough validation.     

In vivo determination of the anatomical axes of the ankle joint complex: An optimization approach

This study investigates the feasibility of a subject-specific three-dimensional model of the ankle joint complex for kinematic and dynamic analysis of movement. The ankle joint complex was modelled as a three-segment system, connected by two ideal highe joints: the talocrural and the subtalar joint. A mathematical formulation was developed to express the three-dimensional translation and rotation between the foot and shank segments as a function of the two joint angles, and 12 model parameters describing the locations of the joint axes. An optimization method was used to fit the model parameters to three-dimensional kinematic data of foot and shank markers, obtained during test movements throughout the entire physiological range of motion of the ankle joint. The movement of the talus segment, which cannot be measured non-invasively, is not necessary for the analysis.

This optimization method was used to determine the position and orientation of the joint axes in 14 normal subjects. After optimization, the discrepancy between the best fitting model and actual marker kinematics was between 1 and 3 mm for all subjects. The predicted inclination of the subtalar joint axis from the horizontal plane was 37.4±2.7°, and the medial deviation was 18.0±16.2°. The lateral side of the talucrural axis was directed slightly posteriorly (6.8±8.1°), and inclined downward by 7.0±5.4°. These results are similar to previously reported typical results from anatomical, in vitro, studies. Reproducibility was evaluated by repeated testing of one subject, which resulted in variations of about one-fifth of the standard deviation within the group, the inclination of the subtalar joint axis was significantly correlated to the arch height and a radiographic ‘tarsal index’. It is concluded that this optimization method provides the opportunity to incorporate inter-individual anatomical differences into kinematic and dynamic analysis of the ankle joint complex. This allows a more functional interpretation of kinematic data, and more realistic estimates of internal forces.     

A closed-loop cadaveric foot and ankle loading model

Investigations of human foot and ankle biomechanics rely chiefly on cadaver experiments. The application of proper force magnitudes to the cadaver foot and ankle is essential to obtain valid biomechanical data. Data for external ground reaction forces are readily available from human motion analysis. However, determining appropriate forces for extrinsic foot and ankle muscles is more problematic. A common approach is the estimation of forces from muscle physiological cross-sectional areas and electromyographic data. We have developed a novel approach for loading the Achilles and posterior tibialis tendons that does not prescribe predetermined muscle forces. For our loading model, these muscle forces are determined experimentally using independent plantarflexion and inversion angle feedback control. The independent (input) parameters -- calcaneus plantarflexion, calcaneus inversion, ground reaction forces, and peroneus forces -- are specified. The dependent (output) parameters -- Achilles force, posterior tibialis force, joint motion, and spring ligament strain -- are functions of the independent parameters and the kinematics of the foot and ankle. We have investigated the performance of our model for a single, clinically relevant event during the gait cycle. The instantaneous external forces and foot orientation determined from human subjects in a motion analysis laboratory were simulated in vitro using closed-loop feedback control. Compared to muscle force estimates based on physiological cross-sectional area data and EMG activity at 40% of the gait cycle, the posterior tibialis force and Achilles force required when using position feedback control were greater.