Determination of ankle muscle power in normal gait using an EMG-to-force processing approach

The purpose of this study was to determine the contribution of individual ankle muscles to the net ankle power and to examine each muscle’s role in propulsion or support of the body during normal, self-selected-speed walking. An EMG-to-force processing (EFP) model was developed which scaled muscle tendon unit force output to gait EMG, with that muscle’s power output being the product of muscle force and contraction velocity. Net EFP power was determined by summing individual ankle muscle power. Net ankle power was also calculated for these subjects via inverse dynamics. Closeness of fit of the power curves of the two methods was used to validate the model. The curves were highly correlated (r² = .91), thus the model was deconstructed to analyze the power contribution and role of each ankle muscle during normal gait. Key findings were that the plantar flexors control tibial rotation in single support, and act to propel the entire limb into swing phase. The dorsiflexors provide positive power for swing phase foot clearance, negative power to control early stance phase foot placement, and a second positive power burst to actively advance the tibia in the transition from double to single support. Co-contraction of agonists and antagonists was limited to only a small percentage of the gait cycle.     

Quantitative assessment of gait determinants during single stance via a three-dimensional model--Part 2. Pathological gait

A three-dimensional model for normal gait formulated in Part 1 is now altered to simulate the dynamics of pathological walking. Mechanisms fundamental to the production of a normal gait pattern are systematically removed, in order to assess contributions from individual gait determinants. Four separate pathological cases are studied: a model neglecting ankle plantarflexor activity; absence of stance knee flexion-extension and foot and knee interaction; both pelvic list and transverse pelvic rotation removed; and finally, a model with all major gait determinants missing. These are used collectively to show that stance knee flexion-extension and foot and knee interaction successively dominate lower-extremity dynamical response during the single support phase of normal gait. The hip abductor muscles, while effecting pelvic list, serve to stabilize this limb, rather than actively determine whole-body vertical acceleration. Mechanisms compensating for a loss in joint motion are also explored. Complete ankle loss may be successfully compensated with increased hip abductor muscle activity; the loss of both ankle and knee, however, demand unacceptable levels of vertical pelvic displacement.     

Adaptive control of center of mass (global) motion and its joint (local) origin in gait

Dynamic gait stability can be quantified by the relationship of the motion state (i.e. the position and velocity) between the body center of mass (COM) and its base of support (BOS). Humans learn how to adaptively control stability by regulating the absolute COM motion state (i.e. its position and velocity) and/or by controlling the BOS (through stepping) in a predictable manner, or by doing both simultaneously following an external perturbation that disrupts their regular relationship. Post repeated-slip perturbation training, for instance, older adults learned to forward shift their COM position while walking with a reduced step length, hence reduced their likelihood of slip-induced falls. How and to what extent each individual joint influences such adaptive alterations is mostly unknown. A three-dimensional individualized human kinematic model was established. Based on the human model, sensitivity analysis was used to systematically quantify the influence of each lower limb joint on the COM position relative to the BOS and the step length during gait. It was found that the leading foot had the greatest effect on regulating the COM position relative to the BOS; and both hips bear the most influence on the step length. These findings could guide cost-effective but efficient fall-reduction training paradigm among older population.     

A numerical method for simulating the dynamics of human walking

This paper presents a general method for simulating the movement of the lower extremity during human walking. It is based upon two separate algorithms: one for single support (an open kinematic chain), and the other for the double support phase (a closed-loop linkage). Central to each of these is the recursive Newton-Euler inverse dynamics algorithm, applicable, as given, to any serial, spatial linkage.

For the unconstrained single support model, the Newton-Euler scheme is applied directly to numerically generate the equations of motion. In the case of double support, however, the kinematic constraint equations are used to first eliminate the redundant degrees of freedom, and then solve for the unknown ground reactions under the constrained limb.

The attractiveness of the method is that it offers a compact alternative to manually deriving the equations defining a mathematical model for human gait.     

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.     

Slip-induced fall-risk assessment based on regular gait pattern in older adults

Aging-associated fall-risk assessment is crucial for fall prevention. Thus, this study aimed to develop a prognostic model to predict fall-risk following an unexpected over-ground slip perturbation based on normal gait pattern in healthy older adults. 112 healthy older adults who experienced a novel slip in a safe laboratory environment were included. Their slip trial and natural walking trial immediately prior to it were analyzed. To identify the best fall-risk predictive model, gait related variables including step length, segment angles, center of mass state, and ground reaction force (GRF) were determined and inputted into a stepwise logistic regression. The optimal slip-induced fall prediction model was based on the right thigh angle at slipping foot touchdown (TD), the maximum GRF of the slipping limb after TD, and the momentum change from TD to recovery foot liftoff (LO), with an overall prediction accuracy of 75.9%, predicting 74.5% of falls (sensitivity) and 77.2% of recoveries (specificity). Conversely, a model based on clinical and demographic measures predicted 78.2% of falls and 47.4% of recoveries, resulting in a much lower overall accuracy of 62.5%. The fall-risk model based on normal gait pattern which was developed for slip-induced perturbations in healthy older adults was able to provide a high predictive accuracy. This information could provide insight about the ideal normal gait measures which could be used to contribute towards development of therapeutic strategies related to dynamic balance and fall prevention to enhance preventive interventions in populations with high-risk for slip-induced falls.     

Biomechanical analysis of the three-dimensional foot structure during gait: a basic tool for clinical applications

A novel three-dimensional numerical model of the foot, incorporating, for the first time in the literature, realistic geometric and material properties of both skeletal and soft tissue components of the foot, was developed for biomechanical analysis of its structural behavior during gait. A system of experimental methods, integrating the optical Contact Pressure Display (CPD) method for plantar pressure measurements and a Digital Radiographic Fluoroscopy (DRF) instrument for acquisition of skeletal motion during gait, was also developed in this study and subsequently used to build the foot model and validate its predictions. Using a Finite Element solver, the stress distribution within the foot structure was obtained and regions of elevated stresses for six subphases of the stance (initial-contact, heel-strike, midstance, forefoot-contact, push-off, and toe-off) were located. For each of these subphases, the model was adapted according to the corresponding fluoroscopic data, skeletal dynamics, and active muscle force loading. Validation of the stress state was achieved by comparing model predictions of contact stress distribution with respective CPD measurements. The presently developed measurement and numerical analysis tools open new approaches for clinical applications, from simulation of the development mechanisms of common foot disorders to pre- and post-interventional evaluation of their treatment.     

Evaluation of a patient-specific cost function to predict the influence of foot path on the knee adduction torque during gait

A large external knee adduction torque during gait has been correlated with the progression of knee osteoarthritis (OA). Though foot path changes (e.g. toeing out) can reduce the adduction torque, no method currently exists to predict whether an optimal foot path exists for a specific patient. This study evaluates a patient-specific optimization cost function to predict how foot path changes influence both adduction torque peaks. Video motion and ground reaction data were collected from a patient with knee OA performing normal, toe out, and wide stance gait. Joint and inertial parameters in a dynamic, 27 degree-of-freedom, full-body gait model were calibrated to the patient's normal gait data. The model was then used in gait optimizations that predicted how the patient's adduction torque peaks would change due to changes in foot path. The cost function tracked the patient's normal gait data using weight factors calibrated to toe out gait and tested using wide stance gait. For both gait motions, the same cost function weights predicted the change in both adduction torque peaks to within 7% error. With further development, this approach may eventually permit the design of patient-specific rehabilitation procedures such as an optimal foot path for patients with knee OA.     

A multi-segment kinematic model of the foot with a novel definition of forefoot motion for use in clinical gait analysis during walking

A multi-segment kinematic model of the foot was developed for use in a gait analysis laboratory. The foot was divided into hindfoot, talus, midfoot and medial and lateral forefoot segments. Six functional joints were defined: ankle and subtalar joints, frontal and transverse plane motions of the hindfoot relative to midfoot, supination/pronation twist of the forefoot relative to midfoot and medial longitudinal arch height-to-length ratio. Twelve asymptomatic subjects were tested during barefoot walking with a six-camera optical stereometric system and auto-reflective markers organized in triads. Repeatability of the joint motions was tested using coefficients of multiple correlation. Ankle and subtalar joint motions and twisting of the forefoot were most repeatable. Hindfoot motions were least repeatable both within-subjects and between-subjects. Hindfoot and forefoot pronation in the frontal plane was found to coincide with dropping of the medial longitudinal arch between early to mid-stance, followed by supination and rising of the arch in late stance and swing phase. This multi-segment foot model addresses an unfortunate shortcoming in current gait analysis practice-the inability to measure motion within the foot. Such measurements are crucial if gait analysis is to remain relevant in the orthopaedic and rehabilitative treatment of the foot and ankle.     

Symmetrical gaits of Cebus apella: implications for the functional significance of diagonal sequence gait in primates

Quadrupedal locomotion of primates is distinguished from the quadrupedalism of many other mammals by several features, including a diagonal sequence (DS) footfall used in symmetrical gaits. This presumably unique feature of primate locomotion has been attributed to an ancestral adaptation for cautious arboreal quadrupedalism on thin, flexible branches. However, the functional significance of DS gait remains largely hypothetical. The study presented here tests hypotheses about the functional significance of DS gait by analyzing the gait mechanics of a primate that alternates between DS and lateral sequence (LS) gaits, Cebus apella. Kinematic and kinetic data were gathered from two subjects as they moved across both terrestrial and simulated arboreal substrates. These data were used to test four hypotheses: (1) locomotion on arboreal supports is associated with increased use of DS gait, (2) DS gait is associated with lower peak vertical substrate reaction forces than LS gait, (3) DS gait is associated with greater forelimb/hind limb differentiation in force magnitudes, and (4) DS gait offers increased stability. Our results indicate that animals preferred DS gait on the arboreal substrate, and LS gait while on the ground. Peak vertical substrate reaction forces showed a tendency to be lower in DS gait, but not consistently so. Pole ("arboreal") forces were lower than ground forces in DS gait, but not in LS gait. The preferred symmetrical gait on both substrates was a grounded run or amble, with the body supported by only one limb throughout most of the stride. During periods of bilateral support, the DS gait had predominantly diagonal support couplets. This benefit for stability on an arboreal substrate is potentially outweighed by overstriding, its associated ipsilateral limb interference in DS gait and hind foot positioning in front of the hand on untested territory. DS gait also did not result in an optimal anchoring position of the hind foot under the center of mass of the body at forelimb touchdown. In sum, the results are mixed regarding the superiority of DS gait in an arboreal setting. Consequently, the notion that DS gait is an ancestral adaptation of primates, conditioned by the selection demands of an arboreal environment, remains largely hypothetical.     

Active control of lateral balance in human walking

We measured variability of foot placement during gait to test whether lateral balance must be actively controlled against dynamic instability. The hypothesis was developed using a simple dynamical model that can walk down a slight incline with a periodic gait resembling that of humans. This gait is entirely passive except that it requires active control for a single unstable mode, confined mainly to lateral motion. An especially efficient means of controlling this instability is to adjust lateral foot placement. We hypothesized that similar active feedback control is performed by humans, with fore-aft dynamics stabilized either passively or by very low-level control. The model predicts that uncertainty within the active feedback loop should result in variability in foot placement that is larger laterally than fore-aft. In addition, loss of sensory information such as by closing the eyes should result in larger increases in lateral variability. The control model also predicts a slight coupling between step width and length. We tested 15 young normal human subjects and found that lateral variability was 79% larger than fore-aft variability with eyes open, and a larger increase in lateral variability (53% vs. 21%) with eyes closed, consistent with the model's predictions. We also found that the coupling between lateral and fore-aft foot placements was consistent with a value of 0.13 predicted by the control model. Our results imply that humans may harness passive dynamic properties of the limbs in the sagittal plane, but must provide significant active control in order to stabilize lateral motion.     

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 robotic cadaveric flatfoot analysis of stance phase

The symptomatic flatfoot deformity (pes planus with peri-talar subluxation) can be a debilitating condition. Cadaveric flatfoot models have been employed to study the etiology of the deformity, as well as invasive and noninvasive surgical treatment strategies, by evaluating bone positions. Prior cadaveric flatfoot simulators, however, have not leveraged industrial robotic technologies, which provide several advantages as compared with the previously developed custom fabricated devices. Utilizing a robotic device allows the researcher to experimentally evaluate the flatfoot model at many static instants in the gait cycle, compared with most studies, which model only one to a maximum of three instances. Furthermore, the cadaveric tibia can be statically positioned with more degrees of freedom and with a greater accuracy, and then a custom device typically allows. We created a six degree of freedom robotic cadaveric simulator and used it with a flatfoot model to quantify static bone positions at ten discrete instants over the stance phase of gait. In vivo tibial gait kinematics and ground reaction forces were averaged from ten flatfoot subjects. A fresh frozen cadaveric lower limb was dissected and mounted in the robotic gait simulator (RGS). Biomechanically realistic extrinsic tendon forces, tibial kinematics, and vertical ground reaction forces were applied to the limb. In vitro bone angular position of the tibia, calcaneus, talus, navicular, medial cuneiform, and first metatarsal were recorded between 0% and 90% of stance phase at discrete 10% increments using a retroreflective six-camera motion analysis system. The foot was conditioned flat through ligament attenuation and axial cyclic loading. Post-flat testing was repeated to study the pes planus deformity. Comparison was then made between the pre-flat and post-flat conditions. The RGS was able to recreate ten gait positions of the in vivo pes planus subjects in static increments. The in vitro vertical ground reaction force was within ± 1 standard deviation (SD) of the in vivo data. The in vitro sagittal, coronal, and transverse plane tibial kinematics were almost entirely within ± 1 SD of the in vivo data. The model showed changes consistent with the flexible flatfoot pathology including the collapse of the medial arch and abduction of the forefoot, despite unexpected hindfoot inversion. Unlike previous static flatfoot models that use simplified tibial degrees of freedom to characterize only the midpoint of the stance phase or at most three gait positions, our simulator represented the stance phase of gait with ten discrete positions and with six tibial degrees of freedom. This system has the potential to replicate foot function to permit both noninvasive and surgical treatment evaluations throughout the stance phase of gait, perhaps eliciting unknown advantages or disadvantages of these treatments at other points in the gait cycle.     

Dynamic gait stability index based on plantar pressures and fuzzy logic

Stability during locomotion, or dynamic stability, is critical to ensure safe locomotion and a high quality of life. A dynamic stability measure should be easily applied in a clinical setting and must provide a quantitative index that can be used for comparisons over a range of tasks and environments. Plantar foot pressure data acquired by shoe-insole sensors have potential to provide such a measure. To generate a quantitative dynamic gait stability index, six gait parameters were extracted from a commercial plantar pressure measurement system (F-Scan): anterior–posterior (A/P) center of force (CoF) motion, medial–lateral (M/L) CoF motion, maximum lateral position, cell triggering, stride time (ST), and double support time (DST). A fuzzy logic controller combined these six parameters and generated the index. To validate the stability index, 15 healthy subjects performed four tasks intended to induce increasing levels of instability. Fifty-seven gait parameter combinations were assessed to determine the most effective index. A combination of A/P motion, M/L motion, maximum lateral position, and cell triggering parameters was the most consistently effective index across all subjects. However, small changes in ST and DST for able-bodied subjects may have reduced the effectiveness of these measures in the index calculation. The index combining all six parameters should be investigated further with populations with disabilities or pathological gait.     

Linear approximations for swing leg motion during gait

The applicability of a linear systems analysis of two-dimensional swing leg motion was investigated. Two different linear systems were developed. A linear time-varying system was developed by linearizing the nonlinear equations describing swing leg motion about a set of nominal system and control trajectories. Linear time invariant systems were developed by linearizing about three different fixed limb positions. Simulations of swing leg motion were performed with each of these linear systems. These simulations were compared to previously performed nonlinear simulations of two-dimensional swing leg motion and the actual subject motion. Additionally, a linear system analysis was used to gain some insight into the interdependency of the state variables and controls. It was shown that the linear time varying approximation yielded an accurate representation of limb motion for the thigh and shank but with diminished accuracy for the foot. In contrast, all the linear time invariant systems, if used to simulate more than a quarter of the swing phase, yielded generally inaccurate results for thigh shank and foot motion.     

3D finite element model of the diabetic neuropathic foot: A gait analysis driven approach

Diabetic foot is an invalidating complication of diabetes that can lead to foot ulcers. Three-dimensional (3D) finite element analysis (FEA) allows characterizing the loads developed in the different anatomical structures of the foot in dynamic conditions. The aim of this study was to develop a subject specific 3D foot FE model (FEM) of a diabetic neuropathic (DNS) and a healthy (HS) subject, whose subject specificity can be found in term of foot geometry and boundary conditions. Kinematics, kinetics and plantar pressure (PP) data were extracted from the gait analysis trials of the two subjects with this purpose. The FEM were developed segmenting bones, cartilage and skin from MRI and drawing a horizontal plate as ground support. Materials properties were adopted from previous literature. FE simulations were run with the kinematics and kinetics data of four different phases of the stance phase of gait (heel strike, loading response, midstance and push off). FEMs were then driven by group gait data of 10 neuropathic and 10 healthy subjects. Model validation focused on agreement between FEM-simulated and experimental PP.     

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.     

Kinematic analysis of a multi-segment foot model for research and clinical applications: a repeatability analysis

An unbiased understanding of foot kinematics has been difficult to achieve due to the complexity of foot structure and motion. We have developed a protocol for evaluation of foot kinematics during barefoot walking based on a multi-segment foot model. Stereophotogrammetry was used to measure retroreflective markers on three segments of the foot plus the tibia. Repeatability was evaluated between-trial, between-day and between-tester using two subjects and two testers. Subtle patterns and ranges of motion between segments of the foot were consistently detected. We found that repeatability between different days or different testers is primarily subject to variability of marker placement more than inter-tester variability or skin movement. Differences between inter-segment angle curves primarily represent a shift in the absolute value of joint angles from one set of trials to another. In the hallux, variability was greater than desired due to vibration of the marker array used. The method permits objective foot measurement in gait analysis using skin-mounted markers. Quantitative and objective characterisation of the kinematics of the foot during activity is an important area of clinical and research evaluation. With this work we hope to have provided a firm basis for a common protocol for in vivo foot study.     

Assessment of the influence of foot orthoses in the hip loading conditions during walking: a single case study

Despite their large clinical application, the understanding of the effects of foot orthoses on the lower limb kinematics and kinetics is limited. In this context, we propose an advanced musculoskeletal model to assess the influence of foot orthoses in the loading conditions within an osteoarthritic hip joint during gait. Experimental data are collected for a single pathological subject presenting a coxarthrosis (with and without orthoses), and a healthy subject during walking. An inverse dynamic approach coupled with an optimisation method evaluates the forces developed by 14 muscles and the hip contact reaction force. Contact reaction and muscular force magnitudes are closed whether the patient is walking with or without foot orthoses. Nevertheless, contact reaction amplitudes and orientations show differences in relation to those calculated for the healthy subject. The results obtained allow us to formulate some assumptions concerning the causes of coxarthrosis evolution and treatment.