Accurate Foot Research Articles

Estimation of Foot Plantar Center of Pressure Trajectories with Low-Cost Instrumented Insoles Using an Individual-Specific Nonlinear Model.

Postural control is a complex skill based on the interaction of dynamic sensorimotor processes, and can be challenging for people with deficits in sensory functions. The foot plantar center of pressure (COP) has often been used for quantitative assessment of postural control. Previously, the foot plantar COP was mainly measured by force plates or complicated and expensive insole-based measurement systems. Although some low-cost instrumented insoles have been developed, their ability to accurately estimate the foot plantar COP trajectory was not robust. In this study, a novel individual-specific nonlinear model was proposed to estimate the foot plantar COP trajectories with an instrumented insole based on low-cost force sensitive resistors (FSRs). The model coefficients were determined by a least square error approximation algorithm. Model validation was carried out by comparing the estimated COP data with the reference data in a variety of postural control assessment tasks. We also compared our data with the COP trajectories estimated by the previously well accepted weighted mean approach. Comparing with the reference measurements, the average root mean square errors of the COP trajectories of both feet were 2.23 mm (±0.64) (left foot) and 2.72 mm (±0.83) (right foot) along the medial–lateral direction, and 9.17 mm (±1.98) (left foot) and 11.19 mm (±2.98) (right foot) along the anterior–posterior direction. The results are superior to those reported in previous relevant studies, and demonstrate that our proposed approach can be used for accurate foot plantar COP trajectory estimation. This study could provide an inexpensive solution to fall risk assessment in home settings or community healthcare center for the elderly. It has the potential to help prevent future falls in the elderly.

Low Price Foot Pressure Distribution Screening Technique: Optical Podoscope with Accurate Foot Print Segmentation using Hidden Markov Random Field Model.

Background: Foot pressure assessment systems are widely used to diagnose foot pathologies. The human foot plays an important role in maintaining the biomechanical function of the lower extremities which includes the provision of balance and stabilization of the body during gait.Objective: There are different types of assessment tools with different capabilities which are discussed in detail in this paper. In this project, we introduce a new camera-based pressure distribution estimation system which can give a numerical estimation in addition to giving a visual illustration of pressure distribution of the sole.Material and Methods: In this analytical study we proposed an accurate Foot Print segmentation using hidden Markov Random Field model. In the first step, an image is captured from the traditional Podoscope device. Then, the HMRF-EM image segmentation scheme applies to extract the contacting part of the sole to the ground. Finally, based on a simple calibration method, per mm2, pressure estimates to give an accurate pressure distribution measure.Results: A significant and usable estimation of foot pressure has been introduced in this article. The main drawback of introduced systems is the low resolution of sensors which is solved using a high resolution camera as a sensor. Another problem is the patchy edge extracted by the systems which is automatically solved in the proposed device using an accurate image segmentation algorithm.Conclusion: We introduced a camera-based plantar pressure assessment tool which uses HMRF-EM-based method has been explained in more detail which gives a brilliant sole segmentation from the captured images.

Coordination of Gaze Behavior and Foot Placement During Walking in Persons With Glaucoma.

Vision normally provides environmental information necessary to direct the foot to safe locations during walking. Peripheral visual field loss limits what a person can see, and may alter how a person visually samples the environment. Here we tested the hypothesis that the spatial-temporal coupling between gaze and stepping in a precision-based walking task is altered in persons with glaucoma, particularly under dual task situations, and results in reduced foot-placement accuracy. Twenty persons with glaucoma and 20 normally sighted controls performed a precision walking task that involved stepping to the center of 4 targets under 3 conditions: targets only, walking, and counting backwards to simulate a conversation, and walking while performing a concurrent visual search task to simulate locating a landmark. We quantified foot-placement error and error variability with respect to the targets, as well as saccade and fixation timing with respect to foot placement. Compared with controls, persons with glaucoma looked earlier at future stepping targets (with respect to toe-off of the foot) in the targets only and count conditions, and transferred gaze away sooner from the current stepping target in all conditions (P<0.05). Persons with glaucoma also had increased foot-placement error, particularly in the count condition, and increased foot-placement error variability compared with normally sighted controls (P<0.05). Glaucoma significantly disrupts gaze-foot coordination and results in less accurate foot placement when precision is required during walking. This may increase the risk of trips and falls in this population.

Low cost 3D foot scan with Kinect

Accurate 3D digital foot model is extremely useful in shoe or orthotics design and other medical situations such as podiatric therapy. In view of the fact that most of the 3D data-acquisition devices on the market are either expensive though high accuracy (e.g., high-end laser scanner), or with poor maneuverability and efficiency (e.g., image-based stereography), or deficient portability (e.g., large-size scanning machine or types requiring support frame), we propose a new method for human foot scanning in this paper. Microsoft Kinect sensor was adopted as the key device in this approach and proved a smart and efficient scanner in 3D foot data acquisition according to a detailed comparison with other scanners in terms of scan time, cost, operability and portability. Accuracy check of the sphere and foot scanning results also demonstrates decent precision of the proposed scanning system.

Effects of hip abduction and adduction accuracy on post-stroke gait

BackgroundGait instability often limits post-stroke function, although the mechanisms underlying this instability are not entirely clear. Our recent work has suggested that one possible factor contributing to post-stroke gait instability is a reduced ability to accurately control foot placement. The purpose of the present experiments was to investigate whether post-stroke gait function is related to the ability to accurately abduct and adduct the hip, as required for accurate foot placement. Methods35 chronic stroke survivors and 12 age-matched controls participated in this experiment. Participants performed hip oscillation trials designed to quantify hip abduction/adduction accuracy, in which they lay supine and moved their leg through a prescribed range of motion in time with a metronome. Stroke survivors also performed overground walking trials at their self-selected speed. Findings28 of the 35 stroke survivors had sufficient active range of motion to perform the prescribed hip oscillation task. In comparison to controls, these 28 stroke survivors were significantly less accurate at matching the abduction target, matching the adduction target, and moving in time with the metronome. Across these stroke survivors, a multiple regression revealed that only paretic hip abduction accuracy made a unique contribution to predicting paretic step width and paretic step period, metrics of gait performance. InterpretationThe present results demonstrate that the ability to accurately abduct the hip is related to post-stroke gait performance, as predicted from a model-based gait stabilization strategy. Therefore, interventions designed to improve lower limb movement accuracy may hold promise for restoring post-stroke gait stability.

Action-oriented colour-coded foot length calliper for primary healthcare workers as a proxy for birth weight & gestational period.

Background & objectives:Foot length of the newborn has a good correlation with the birth weight and is recommended to be used as a proxy measure. There can be variations in the measurement of foot length. A study was, therefore, carried out to develop a foot length calliper for accurate foot length measurement and to find cut-off values for birth weight and gestational age groups to be used by primary healthcare workers.Methods:This study was undertaken on 645 apparently healthy newborn infants with known gestational age. Nude birth weight was taken within 24 h of birth on a standard electronic weighing machine. A foot length calliper was developed. Correlation between foot length and birth weight as well as gestational age was calculated. Correctness of cut-off values was tested using another set of 133 observations on the apparently healthy newborns. Action-oriented colour coding was done to make it easy for primary healthcare workers to use it.Results:There was a significant correlation of foot length with birth weight (r=0.75) and gestational age (r=0.63). Cut-off values for birth weight groups were 6.1, 6.8 and 7.3 cm and for gestational age of 6.1, 6.8 and 7.0 cm. Correctness of these cut-off values ranged between 77.1 and 95.7 per cent for birth weight and 60-93.3 per cent for gestational age. Considering 2.5 kg as cut-off between normal birth weight and low birth weight (LBW), cut-off values of 6.1, 6.8 and 7.3 were chosen. Action-oriented colour coding was done by superimposing the colours on the scale of the calliper, green indicating home care, yellow indicating supervised home care, orange indicating care at newborn care units at primary health centres and red indicating Neonatal Intensive Care Unit care for infants.Interpretation & conclusions:A simple device was developed so that the primary health care workers and trained Accredited Social Health Activist workers can identify the risk of LBW in the absence of accurate weighing facilities and decide on the type of care needed by the newborn and take action accordingly.

Foot placement relies on state estimation during visually guided walking.

Accurate foot placement is essential for safe walking. We used computational models and human walking experiments to test how our nervous system achieves this accuracy. We find that our control of foot placement beneficially combines sensory feedback with internal forward model predictions to accurately estimate the body's state. Our results match recent computational neuroscience findings for reaching movements, suggesting that state estimation is a general mechanism of human motor control.

Synchrony of gaze and stepping patterns in people with Parkinson’s disease

The aim of the present study was to test the hypothesis that people with Parkinson’s disease (PD) are more dependent than healthy individuals on visual information in an on-line manner to guarantee accurate foot placement into an intended stepping target. Patients with PD and age-matched healthy participants walked along a pathway and were required to step onto either one or two targets during the walk trial. Outcome measures included absolute error (accuracy) and error variability (precision) of foot placement onto the first target, and the time interval between the gaze transfer away from the first target and heel contact on the same target. When there was a single target in the travel path, both groups fixated the target until after heel contact on the target. However, when challenged with an additional target, both groups transferred their gaze from the first target prior to heel contact. Interestingly, only people with PD increased anterior-posterior absolute error (first target) when there was more than one target in the travel path. Premature gaze transfer was associated with decline in stepping accuracy (anterior-posterior absolute error) in people with PD. These findings suggest that both people with PD and healthy individuals prioritize the planning of future actions over the execution of ongoing steps, while walking. Additionally, current findings support the notion people with PD are more dependent on visual feedback to make on-line corrections and adjustments to their foot trajectory in order to guarantee accurate foot placement into an intended stepping target.

Task dependency of movement regulation in female gymnastic vaulting

Background: In gymnastics vaulting it is thought that gymnasts regulate their run-up on the basis of visually perceived environmental information, such as the position of the springboard, with the aim of an accurate foot placement on the springboard. The question, however, arises if these regulative processes found in gymnastics vaulting can be generalized to other tasks with similar demands but differing dynamics? Material/Methods: To answer this question, ten female gymnasts were asked to perform two target-directed gymnastics tasks that were similar in task demands but differed in task dy-namics. When performing the two tasks, the position of the springboard was manipulated without the gymnast’s awareness. Results: Results revealed that manipulating the position of the springboard had neither an effect on the distance of the hurdle, nor on the placement of the feet on the spring-board during the reactive leap. The two parameters, however, clearly differed between experimental tasks. Additionally, regulation during run-up occurred on average one step earlier when performing the tucked leap on the balance beam. Conclusions: It can be concluded from the results that gymnasts exhibit a different movement behavior when performing tasks with similar demands but different dynamics, thereby integrating environmental information in the regulation of the run-up and the reactive leap from trial to trial.

Residual Elimination Algorithm Enhancements to Improve Foot Motion Tracking During Forward Dynamic Simulations of Gait.

Patient-specific gait optimizations capable of predicting post-treatment changes in joint motions and loads could improve treatment design for gait-related disorders. To maximize potential clinical utility, such optimizations should utilize full-body three-dimensional patient-specific musculoskeletal models, generate dynamically consistent gait motions that reproduce pretreatment marker measurements closely, and achieve accurate foot motion tracking to permit deformable foot-ground contact modeling. This study enhances an existing residual elimination algorithm (REA) Remy, C. D., and Thelen, D. G., 2009, “Optimal Estimation of Dynamically Consistent Kinematics and Kinetics for Forward Dynamic Simulation of Gait,” ASME J. Biomech. Eng., 131(3), p. 031005) to achieve all three requirements within a single gait optimization framework. We investigated four primary enhancements to the original REA: (1) manual modification of tracked marker weights, (2) automatic modification of tracked joint acceleration curves, (3) automatic modification of algorithm feedback gains, and (4) automatic calibration of model joint and inertial parameter values. We evaluated the enhanced REA using a full-body three-dimensional dynamic skeletal model and movement data collected from a subject who performed four distinct gait patterns: walking, marching, running, and bounding. When all four enhancements were implemented together, the enhanced REA achieved dynamic consistency with lower marker tracking errors for all segments, especially the feet (mean root-mean-square (RMS) errors of 3.1 versus 18.4 mm), compared to the original REA. When the enhancements were implemented separately and in combinations, the most important one was automatic modification of tracked joint acceleration curves, while the least important enhancement was automatic modification of algorithm feedback gains. The enhanced REA provides a framework for future gait optimization studies that seek to predict subject-specific post-treatment gait patterns involving large changes in foot-ground contact patterns made possible through deformable foot-ground contact models.

The contributions of active and passive modes of control during walking over complex terrain

When walking over complex terrain, humans use visual information about the upcoming ground surface layout to exploit the passive physical forces inherent to bipedal locomotion. We previously showed that visual information about potential target footholds for an upcoming step is critical for control during the end of the preceding step. Visual information about target position presented during this critical control phase was sufficient for subjects to accurately step to a target, while the same information presented before or after the critical phase resulted in less accurate foot placement. Although visual information about target position is not essential once the step to that target is initiated, it remains unclear whether humans are capable of using such information to improve stepping accuracy following a perturbation during that step. Reynolds and Day (2005) demonstrated that, when taking a single step, participants rapidly respond to changes in target position while the foot is in flight. However, it is not known whether humans exhibit such active corrections during continuous walking over longer stretches of complex terrain, when locomotion is largely under passive control. In the present study, subjects walked along a path of irregularly spaced targets projected onto the ground while their movements were recorded with motion capture. As subjects approached targets, each target briefly disappeared and then reappeared. On a subset of trials, the location of one of the six targets was perturbed in either a medial-lateral or anterior-posterior direction while invisible. Subjects' responses to the perturbation depended on the timing of visual information during that step. DISCUSSION focuses on the contributions of active control, to respond to perturbations during the swing phase, and passive control, to efficiently adapt the gait cycle to upcoming terrain. Meeting abstract presented at VSS 2015. Language: en

The biomechanics of walking shape the use of visual information during locomotion over complex terrain.

The aim of this study was to examine how visual information is used to control stepping during locomotion over terrain that demands precision in the placement of the feet. More specifically, we sought to determine the point in the gait cycle at which visual information about a target is no longer needed to guide accurate foot placement. Subjects walked along a path while stepping as accurately as possible on a series of small, irregularly spaced target footholds. In various conditions, each of the targets became invisible either during the step to the target or during the step to the previous target. We found that making targets invisible after toe off of the step to the target had little to no effect on stepping accuracy. However, when targets disappeared during the step to the previous target, foot placement became less accurate and more variable. The findings suggest that visual information about a target is used prior to initiation of the step to that target but is not needed to continuously guide the foot throughout the swing phase. We propose that this style of control is rooted in the biomechanics of walking, which facilitates an energetically efficient strategy in which visual information is primarily used to initialize the mechanical state of the body leading into a ballistic movement toward the target foothold. Taken together with previous studies, the findings suggest the availability of visual information about the terrain near a particular step is most essential during the latter half of the preceding step, which constitutes a critical control phase in the bipedal gait cycle.

Footstep parameterized motion blending using barycentric coordinates

This paper presents a real-time animation system for fully embodied virtual humans that satisfies accurate foot placement constraints for different human walking and running styles. Our method offers a fine balance between motion fidelity and character control, and can efficiently animate over sixty agents in real time (25 FPS) and over a hundred characters at 13 FPS. Given a point cloud of reachable support foot configurations extracted from the set of available animation clips, we compute the Delaunay triangulation. At runtime, the triangulation is queried to obtain the simplex containing the next footstep, which is used to compute the barycentric blending weights of the animation clips. Our method synthesizes animations to accurately follow footsteps, and a simple IK solver adjusts small offsets, foot orientation, and handles uneven terrain. To incorporate root velocity fidelity, the method is further extended to include the parametric space of root movement and combine it with footstep based interpolation. The presented method is evaluated on a variety of test cases and error measurements are calculated to offer a quantitative analysis of the results achieved.

Inertial sensor-based smoother for gait analysis.

An off-line smoother algorithm is proposed to estimate foot motion using an inertial sensor unit (three-axis gyroscopes and accelerometers) attached to a shoe. The smoother gives more accurate foot motion estimation than filter-based algorithms by using all of the sensor data instead of using the current sensor data. The algorithm consists of two parts. In the first part, a Kalman filter is used to obtain initial foot motion estimation. In the second part, the error in the initial estimation is compensated using a smoother, where the problem is formulated in the quadratic optimization problem. An efficient solution of the quadratic optimization problem is given using the sparse structure. Through experiments, it is shown that the proposed algorithm can estimate foot motion more accurately than a filter-based algorithm with reasonable computation time. In particular, there is significant improvement in the foot motion estimation when the foot is moving off the floor: the z-axis position error squared sum (total time: 3.47 s) when the foot is in the air is 0.0807 m2 (Kalman filter) and 0.0020 m2 (the proposed smoother).

Intruder Identification Using Footprint Recognition with PCA and SVM Classifiers

In modern digital era authentication has been done using biometric recognition. This biometric includes finger print, footprint, facial recognition, DNA of a person’s gene, hand palm print and eye’s iris recognition. The widely used among these is finger print and iris recognition. In this work we proposed a biometric recognition using footprints of a person. Earlier work deals with capturing footprint on a paper or on a surface. This won’t give us accurate foot print, since it depends on nature of the surface, quality of the paper and proper placement of the foot to give good foot print impression. To avoid all these we proposed a touch less method to obtain foot prints. The footprint can be obtained using any digital camera. We can take footprint image in many angles to conform the individuality of a person. In this work we used Principle Component Analysis (PCA) for pattern recognition and feature extraction. Then the SVM classifier split the patterns in to relevant classes. In early stage of our work itself we got remarkable quality and it is comparatively better than conventional footprint images obtained using paper or surface

Dynamic 3D shape of the plantar surface of the foot using coded structured light: a technical report

BackgroundThe foot provides a crucial contribution to the balance and stability of the musculoskeletal system, and accurate foot measurements are important in applications such as designing custom insoles/footwear. With better understanding of the dynamic behavior of the foot, dynamic foot reconstruction techniques are surfacing as useful ways to properly measure the shape of the foot. This paper presents a novel design and implementation of a structured-light prototype system providing dense three dimensional (3D) measurements of the foot in motion. The input to the system is a video sequence of a foot during a single step; the output is a 3D reconstruction of the plantar surface of the foot for each frame of the input.MethodsEngineering and clinical tests were carried out to test the accuracy and repeatability of the system. Accuracy experiments involved imaging a planar surface from different orientations and elevations and measuring the fitting errors of the data to a plane. Repeatability experiments were done using reconstructions from 27 different subjects, where for each one both right and left feet were reconstructed in static and dynamic conditions over two different days.ResultsThe static accuracy of the system was found to be 0.3 mm with planar test objects. In tests with real feet, the system proved repeatable, with reconstruction differences between trials one week apart averaging 2.4 mm (static case) and 2.8 mm (dynamic case).ConclusionThe results obtained in the experiments show positive accuracy and repeatability results when compared to current literature. The design also shows to be superior to the systems available in the literature in several factors. Further studies need to be done to quantify the reliability of the system in clinical environments.

Neurophysiology of gait: From the spinal cord to the frontal lobe

Locomotion is a purposeful, goal-directed behavior initiated by signals arising from either volitional processing in the cerebral cortex or emotional processing in the limbic system. Regardless of whether the locomotion initiation is volitional or emotional, locomotion is accompanied by automatic controlled movement processes, such as the adjustment of postural muscle tone and rhythmic limb movements. Sensori-motor integration in the brainstem and the spinal cord plays crucial roles in this process. The basic locomotor motor pattern is generated by spinal interneuronal networks, termed central pattern generators (CPGs). Responding to signals in proprioceptive and skin afferents, the spinal interneuronal networks modify the locomotor pattern in cooperation with descending signals from the brainstem structures and the cerebral cortex. Information processing between the basal ganglia, the cerebellum, and the brainstem may enable automatic regulation of muscle tone and rhythmic limb movements in the absence of conscious awareness. However, when a locomoting subject encounters obstacles, the subject has to intentionally adjust bodily alignment to guide limb movements. Such an intentional gait modification requires motor programming in the premotor cortices. The motor programs utilize one's bodily information, such as the body schema, which is preserved and updated in the temporoparietal cortex. The motor programs are transmitted to the brainstem by the corticoreticulospinal system, so that one's posture is anticipatorily controlled. These processes enable the corticospinal system to generate limb trajectory and achieve accurate foot placement. Loops from the motor cortical areas to the basal ganglia and the cerebellum can serve this purpose.

Effects of a Foot Placement Constraint on Use of Motor Equivalence during Human Hopping

Humans can robustly locomote over complex terrains even while simultaneously attending to other tasks such as accurate foot placement on the ground. We investigated whether subjects would exploit motor redundancy across the joints of the leg to stabilize overall limb kinematics when presented with a hopping task that constrained foot placement position. Subjects hopped in place on one leg (2.2 Hz) while having to place their foot into one of three target sizes upon landing (0.250, 0.063, 0.010 m2). As takeoff and landing angles are critical to this task performance, we hypothesized smaller target sizes would increase the need to stabilize (i.e., make more consistent) the leg orientation through motor equivalent combinations of segment angles. As it was not critical to the targeting task, we hypothesized no changes for leg length stabilization across target size. With smaller target sizes, we saw total segment angle variance increase due to greater signal-dependent noise associated with an increased activation of leg extensor muscles (medial and lateral gastrocnemius, vastus medialis, vastus lateralis and rectus femoris). At smaller target sizes, more segment angle variance was aligned to kinematic deviations with the goal of maintaining leg orientation trajectory. We also observed a decrease in the variance structure for stabilizing leg length at the smallest target conditions. This trade-off effect is explained by the nearly orthogonal relationship between the two goal-equivalent manifolds for leg length vs. leg orientation stabilization. Our results suggest humans increasingly rely on kinematic redundancy in their legs to achieve robust, consistent locomotion when faced with novel conditions that constrain performance requirements. These principles may generalize to other human locomotor gaits and provide important insights into the control of the legs during human walking and running.

Step scaling and behaviour selection in a constrained set of manual material handling transfers

Predictive biomechanical analysis of manual material handling (MMH) transfers is dependent on accurate prediction of foot locations relative to the task. Previous studies have classified common acyclic stepping patterns used during those transfer tasks, but the influence of walking distance prior to the transfer is not well understood. Twenty men and women performed transfers for a minimum of six different delivery distance conditions. The number of steps used by the participants ranged from two to seven. A theoretical framework for idealised step-scaling strategies is proposed and compared with the experimental data. The maximum observed increase in step length prior to delivery was 1.43 times the nominal step length calculated for each participant. The data suggest that although participants can scale their steps to facilitate the use of a single terminal stance at the transfer, the majority of participants chose to utilise a combination of stepping strategies if the preferred contralateral lead foot strategy could not be easily implemented. Practitioner summary: Accurate foot placements are needed for predictive biomechanical analysis of MMH. A laboratory study investigated the influence of previous step positions on MMH. A flexible step-scaling strategy, in which step lengths and strategy were varied, suggests that analysis based on simulated movements should consider multiple lifting postures.

Why you need to look where you step for precise foot placement: The effects of gaze eccentricity on stepping errors

Previous research has shown that accurate stepping involves the fixation of gaze on the intended step location. One possible explanation for this visual strategy is that the fixation of locations that are eccentric relative to the step target, results in systematic localization errors, as has previously been demonstrated in pointing. To test this idea, we assessed the possible role of gaze stabilization in the spatial planning of accurate steps, and determined whether the direction of mediolateral stepping errors depended on the direction of gaze. Final foot position was recorded from ten healthy participants when making steps towards prints of their own foot, in light and in darkness, and fixating their gaze on (i) the stepping target or (ii) locations 30cm to the left or right of the target. The results showed that accuracy and precision of foot placement were reduced when stepping in darkness or when fixating eccentric gaze targets, demonstrating that visual feedback on the target and/or foot facilitates spatial control of the foot, and that foveal information is superior to perifoveal information in this respect. Crucially, the direction of the mediolateral stepping errors depended on the direction of gaze: on average participants overstepped 12mm contralateral to the direction of gaze when fixating eccentric locations, indicating that the fixation of locations eccentric to the stepping target results in inaccuracies in foot placement. These results provide new insights into the contributions of foveal vision to the spatial planning of precise steps, and explain why it is important to look where you step when accurate foot placement is required.