Accurate Foot Research Articles

Measuring highly accurate foot position and angle trajectories with foot-mounted IMUs in clinical practice

BackgroundGait analysis using foot-mounted IMUs is a promising method to acquire gait parameters outside of laboratory settings and in everyday clinical practice. However, the need for precise sensor attachment or calibration, the requirement of environments with a homogeneous magnetic field, and the limited applicability to pathological gait patterns still pose challenges. Furthermore, in previously published work, the measurement accuracy of such systems is often only validated for specific points in time or in a single plane. Research questionThis study investigates the measurement accuracy of a gait analysis method based on foot-mounted IMUs in the acquisition of the foot motion, i.e., position and angle trajectories of the foot in the sagittal, frontal, and transversal plane over the entire gait cycle. ResultsA comparison of the proposed method with an optical motion capture system showed an average RMSE of 0.67° for pitch, 0.63° for roll and 1.17° for yaw. For position trajectories, an average RMSE of 0.51 cm for vertical lift and 0.34 cm for lateral shift was found. The measurement error of the IMU-based method is found to be much smaller than the deviations caused by the shoes. SignificanceThe proposed method is found to be sufficiently accurate for clinical practice. It does not require precise mounting, special calibration movements, or magnetometer data, and shows no difference in measurement accuracy between normal and pathological gait. Therefore, it provides an easy-to-use alternative to optical motion capture and facilitates gait analysis independent of laboratory settings.

Perceptive Locomotion Through Nonlinear Model-Predictive Control

Dynamic locomotion in rough terrain requires accurate foot placement, collision avoidance, and planning of the underactuated dynamics of the system. Reliably optimizing for such motions and interactions in the presence of imperfect and often incomplete perceptive information is challenging. We present a complete perception, planning, and control pipeline, which can optimize motions for all degrees of freedom of the robot in real time. To mitigate the numerical challenges posed by the terrain, a sequence of convex inequality constraints is extracted as local approximations of foothold feasibility and embedded into an online model-predictive controller. Steppability classification, plane segmentation, and a signed distance field are precomputed per elevation map to minimize the computational effort during the optimization. A combination of multiple-shooting, real-time iteration, and a filter-based line search is used to solve the formulated problem reliably and at high rate. We validate the proposed method in scenarios with gaps, slopes, and stepping stones in simulation and experimentally on the ANYmal quadruped platform, resulting in state-of-the-art dynamic climbing.

Embodiment of virtual feet correlates with motor performance in a target-stepping task: a pilot study

Immersive Virtual Reality (IVR) has gained popularity in neurorehabilitation for its potential to increase patients’ motivation and engagement. A crucial yet relatively unexplored aspect of IVR interfaces is the patients’ representation in the virtual world, such as with an avatar. A higher level of embodiment over avatars has been shown to enhance motor performance during upper limb training and has the potential to be employed to enhance neurorehabilitation. However, the relationship between avatar embodiment and gait performance remains unexplored. In this work, we present the results of a pilot study with 12 healthy young participants that evaluates the effect of different virtual lower limb representations on foot placement accuracy while stepping over a trail of 16 virtual targets. We compared three levels of virtual representation: i) a full-body avatar, ii) only feet, and iii) no representation. Full-body tracking is computed using standard VR trackers to synchronize the avatar with the participants’ motions. Foot placement accuracy is measured as the distance between the foot’s center of mass and the center of the selected virtual target. Additionally, we evaluated the level of embodiment over each virtual representation through a questionnaire. Our findings indicate that foot placement accuracy increases with some form of virtual representation, either full-body or foot, compared to having no virtual representation. However, the foot and full-body representations do not show significant differences in accuracy. Importantly, we found a negative correlation between the level of embodiment of the foot representation and the distance between the placed foot and the target. However, no such correlation was found for the full-body representation. Our results highlight the importance of embodying a virtual representation of the foot when performing a task that requires accurate foot placement. However, showing a full-body avatar does not appear to further enhance accuracy. Moreover, our results suggest that the level of embodiment of the virtual feet might modulate motor performance in this stepping task. This work motivates future research on the effect of embodiment over virtual representations on motor control to be exploited for IVR gait rehabilitation.

Between a Walk and a Hard Place: How Stepping Patterns Change While Navigating Environmental Obstacles.

Maintaining a consistent relationship between each footfall and the body's motion is a key mechanism to maintain balance while walking. However, environmental features, for example, puddles/obstacles, impose additional constraints on foot placement. This study investigated how healthy young individuals alter foot placements to simultaneously manage body-centric and environmental constraints during an obstacle-crossing task. Consistent step length promotes balance for all steps, whereas accurate foot placement around the obstacle is essential to avoid a trip. While crossing an obstacle, any error in positioning one foot relative to the obstacle can be compensated by selecting the placement of the subsequent step. However, compensation will necessarily alter step length from its average value. The interstep covariance index computed from two consecutive foot placements was used to quantify this tradeoff between body-centric and environmental constraints for six consecutive steps while approaching, crossing, and resuming unobstructed gait after crossing the obstacle. The index declined only when either one or both feet were adjacent to the obstacle. The decline was driven in part by a tendency toward higher step length variability. Thus, changes in the stepping patterns to address the environmental constraint occurred at the cost of the body-centric constraint. However, the step length never ceased to be controlled; the interstep covariance index was positive for all steps. Overall, participants adapted foot placement control to account for the larger threat to balance. The environmental constraint was prioritized only when a potential trip posed greater threat to balance compared with the threat posed by variable step length.

UnderPressure: Deep Learning for Foot Contact Detection, Ground Reaction Force Estimation and Footskate Cleanup

AbstractHuman motion synthesis and editing are essential to many applications like video games, virtual reality, and film post‐production. However, they often introduce artefacts in motion capture data, which can be detrimental to the perceived realism. In particular, footskating is a frequent and disturbing artefact, which requires knowledge of foot contacts to be cleaned up. Current approaches to obtain foot contact labels rely either on unreliable threshold‐based heuristics or on tedious manual annotation. In this article, we address automatic foot contact label detection from motion capture data with a deep learning based method. To this end, we first publicly release Under Pressure, a novel motion capture database labelled with pressure insoles data serving as reliable knowledge of foot contact with the ground. Then, we design and train a deep neural network to estimate ground reaction forces exerted on the feet from motion data and then derive accurate foot contact labels. The evaluation of our model shows that we significantly outperform heuristic approaches based on height and velocity thresholds and that our approach is much more robust when applied on motion sequences suffering from perturbations like noise or footskate. We further propose a fully automatic workflow for footskate cleanup: foot contact labels are first derived from estimated ground reaction forces. Then, footskate is removed by solving foot constraints through an optimisation‐based inverse kinematics (IK) approach that ensures consistency with the estimated ground reaction forces. Beyond footskate cleanup, both the database and the method we propose could help to improve many approaches based on foot contact labels or ground reaction forces, including inverse dynamics problems like motion reconstruction and learning of deep motion models in motion synthesis or character animation. Our implementation, pre‐trained model as well as links to database can be found at github.com/InterDigitalInc/UnderPressure.

The dynamic characteristics of the center of pressure for toe-out gait: implications for footwear design

BackgroundToe-out gait is often used as a conservative technique to reduce knee adduction moment, which has been targeted to modify knee osteoarthritis progression. The center of pressure (COP) can not only be used to evaluate gait stability, but is also more reliable and practical than local plantar pressures as it does not depend on accurate foot zone divisions. However, to the authors’ knowledge, few study has reported the influence of the foot progression angle on the dynamic characteristics of the COP.Research questionThe aim of the study was to investigate the effects of the deliberately toe-out gait on the COP trajectory and stability during walking in healthy individuals.MethodsThirty healthy young adults were asked to walk along an 8-m walkway. A Footscan 1 m pressure plate was used to measure the center of pressure during walking.ResultsCompared to the normal gait, the COP of the toe-out gait shifted laterally during the initial contact phase, and shifted laterally and anteriorly during the forefoot contact phase. The mean anterior–posterior velocity of COP reduced by 0.109 m/s during the foot flat phase and the duration of the foot flat phase and forefoot push off phase increased by 4.5% and reduced by 7.0%, respectively.SignificanceCompared to the normal gait, the findings of this study suggest that biomechanical alteration of foot under our experimental conditions may decrease gait stability and increase forefoot load during toe-out walking. The situation may be improved by well-designed footwear or custom-made insole and the biomechanics analysis method can be used to test the efficacy of therapeutic footwear or insole for individuals with deliberately toe-out walking.Graphical

A CPG-based gait planning and motion performance analysis for quadruped robot

PurposeTo achieve stable gait planning and enhance the motion performance of quadruped robot, this paper aims to propose a motion control strategy based on central pattern generator (CPG) and back-propagation neural network (BPNN).Design/methodology/approachFirst, the Kuramoto phase oscillator is used to construct the CPG network model, and a piecewise continuous phase difference matrix is designed to optimize the duty cycle of walk gait, so as to realize the gait planning and smooth switching. Second, the mapper between CPG output and joint drive is established based on BP neural network, so that the quadruped robot based on CPG control has better foot trajectory to enhance the motion performance. Finally, to obtain better mapping effect, an evaluation function is resigned to evaluate the proximity between the actual foot trajectory and the ideal foot trajectory. Genetic algorithm and particle swarm optimization are used to optimize the initial weights and thresholds of BPNN to obtain more accurate foot trajectory.FindingsThe method provides a solution for the smooth gait switching and foot trajectory of the robot. The quintic polynomial trajectory is selected to testify the validity and practicability of the method through simulation and prototype experiment.Originality/valueThe paper solved the incorrect duty cycle under the walk gait of CPG network constructed by Kuramoto phase oscillator, and made the robot have a better foot trajectory by mapper to enhance its motion performance.

Finite Element Analysis of Cushioned Diabetic Footwear Using Ethylene Vinyl Acetate Polymer.

With the development of societies, diabetic foot ulcers have become one of the most common diseases requiring lower extremity amputation. The early treatment and prevention of diabetic foot ulcers can considerably reduce the possibility of amputation. Using footwear to redistribute and relieve plantar pressure is one of the important measures for the treatment and prevention of diabetic foot ulcers. Thus, the evaluation and prediction of the distribution of plantar pressure play an important role in designing footwears. Herein, the finite element method was used to study plantar pressure under two kinds of foot models, namely, the skeletal structure foot model and the whole foot model, to explore the influence of human bones on the pressure of the soles of the feet and obtain accurate foot pressure. Simulation results showed that under the two models, the plantar pressure and the pressure from the footwear with ethylene vinyl acetate were all reduced. The total deformation demonstrated a slight increase. These stresses are very useful as they enable the design of suitable orthotic footwear that reduces the amount of stress in individuals with diabetic foot ulcers.

Spatiotemporal Gait Measurement With a Side-View Depth Sensor Using Human Joint Proposals.

We propose a method for calculating standard spatiotemporal gait parameters from individual human joints with a side-view depth sensor. Clinical walking trials were measured concurrently by a side-view Kinect and a pressure-sensitive walkway, the Zeno Walkway. Multiple joint proposals were generated from depth images by a stochastic predictor based on the Kinect algorithm. The proposals are represented as vertices in a weighted graph, where the weights depend on the expected and measured lengths between body parts. A shortest path through the graph is a set of joints from head to foot. Accurate foot positions are selected by comparing pairs of shortest paths. Stance phases of the feet are detected by examining the motion of the feet over time. The stance phases are used to calculate four gait parameters: stride length, step length, stride width, and stance percentage. A constant frame rate was assumed for the calculation of stance percentage because time stamps were not captured during the experiment. Gait parameters from 52 trials were compared to the ground truth walkway using Bland-Altman analysis and intraclass correlation coefficients. The large spatial parameters had the strongest agreements with the walkway (ICC(2, 1) = 1.00 and 0.98 for stride and step length with normal pace, respectively). The presented system directly calculates gait parameters from individual foot positions while previous side-view systems relied on indirect measures. Using a side-view system allows for tracking walking in both directions with one camera, extending the range in which the subject is in the field of view.

‘Haste makes waste’: The tradeoff between walking speed and target-stepping accuracy

BackgroundWhen environmental conditions require accurate foot placement during walking (e.g., on a rough path), we typically walk slower to avoid tripping, slipping or stumbling. Likewise, hurrying too much is a common situational circumstance of walking-related falls. This suggests a tradeoff between walking speed and stepping accuracy in situations that demand precise foot placement. Research questionHow can this expected tradeoff between walking speed and stepping accuracy best be parameterized? MethodsIn Experiment 1, participants (n = 20) walked at five different speeds over an irregularly spaced sequence of projected stepping targets. Participants were instructed to place their feet accurately onto the targets, while following a constant-speed cue running alongside the walkway. Stepping accuracy was parameterized as overall (RMSE, root mean square error), variable (VE) and constant (CE) stepping errors, quantified over targets as well as per target. In Experiment 2, we determined preferred walking speed and stepping accuracy for regularly and irregularly spaced stepping targets. ResultsRepeated-measures ANOVAs revealed that RMSE and VE grew linearly with increasing speeds, both over targets as well as per target. Per target CE varied in magnitude and sign with variations in inter-target spacing: for shorter inter-target spacing targets were overshot (CE > 0), while for longer inter-target spacing targets were undershot (CE < 0). This effect was stronger for faster speeds and for targets preceded by the shortest and longest inter-target spacing. Preferred walking speed and per-target VE did not differ between regularly and irregularly spaced targets. SignificanceParticipants stepped less precisely when walking faster. The linear increase in VE with faster speeds was consistent with Schmidt’s law regarding the speed-accuracy tradeoff. The systematic comparison of stepping errors over regularly and irregularly spaced stepping-target conditions further provided important clues on how to best parameterize stepping accuracy: per stepping target using VE (i.e., stepping inconsistency), complemented with CE (i.e., stepping bias) in case of irregular inter-target spacing.

Construction of Wireless Underground Footwork Mobile Training and Monitoring Sensor Network in Venues of Major Sports Events

At the Summer Olympics in Tokyo, technology was used extensively in major sports events. The level of foot movement ability greatly affects the performance of sports technology. Modern sports are developing in the direction of high speed, high skills, flexibility, and rapidity, and more and more reflect the important position of reasonable and accurate foot movement ability in sports. This article uses wireless sensor technology and wireless communication technology to design the overall architecture of the wireless underground footwork mobile training and monitoring network in venues of major sports events. According to the determined monitoring parameters and data transmission plan, a wireless remote monitoring data acquisition system is designed, and the hardware design, software design, and networking of the wireless monitoring node are completed, so as to realize the real‐time monitoring and remote transmission of the underlying data. This paper proposes a wireless sensor network management architecture and method based on multiagent cooperation and combines active and passive wireless underground footwork mobile training and monitoring for experimental verification. A multitask allocation strategy optimized for network working life is proposed. A genetic algorithm is used to model and optimize the task data report routing of cluster head nodes. The simulation experiment results show that the wireless sensor network management method based on multiagent cooperation can effectively coordinate different monitoring sensor nodes to complete the assigned monitoring tasks; the multitask assignment strategy based on a genetic algorithm can optimize the working life of the application network.

Objective measurement of adherence to wearing foot orthoses using an embedded temperature sensor

The objective of this study was to evaluate the validity of a temperature sensor for the measurement of adherence to wearing foot orthoses. Ten participants were provided with foot orthoses containing an embedded temperature sensor and wore the orthoses for a randomly-determined duration over a five-day period. Sensor-detected wear time was compared to a reference standard (objectively measured wear time using a smart-phone application). Ambient temperature and physical activity were recorded with a temperature gauge and wearable activity tracker, respectively. A simple peak detection algorithm which identified the largest one-minute changes in sensor temperature provided highly accurate wear time values (r = 0.999, coefficient of variation=0.2%). Ambient temperature and physical activity did not significantly influence temperature sensor scores. These findings demonstrate that the temperature sensor provides accurate foot orthosis wear time data and may therefore be a useful tool for documenting adherence in clinical practice and intervention studies.

Targeted Walking in Incomplete Spinal Cord Injury: Role of Corticospinal Control.

Locomotor recovery after incomplete spinal cord injury (iSCI) is influenced by spinal and supraspinal networks. Conventional clinical gait analysis fails to differentiate between these components. There is evidence that corticospinal control is enhanced during targeted walking, where each foot must be continuously placed on visual targets in randomized order. This study investigates the potential of targeted walking in the functional assessment of corticospinal integrity. Twenty-one controls and 16 individuals with chronic iSCI performed normal and targeted walking on a treadmill while electromyograms (EMGs) and kinematics were recorded. Precision (% of accurate foot placements) in targeted walking was significantly lower in individuals with iSCI (82.9 ± 14.7%, controls: 94.9 ± 4.0%). Although the overall kinematic pattern was comparable between walking conditions, controls showed significantly higher semitendinosus (ST) activity before heel-strike during targeted walking. This was accompanied by a shift of relative EMG intensity from 90-120 Hz to lower frequencies of 20-60 Hz, previously associated with corticospinal control of muscle activity. Targeted walking in individuals with iSCI evoked smaller EMG changes, suggesting that the switch to more corticospinal control is impaired. Accordingly, mildly impaired iSCI individuals revealed higher adaptations to the targeted walking task than more-impaired individuals. Recording of EMGs during targeted walking holds potential as a research tool to reveal further insights into the neuromuscular control of locomotion. It also complements findings of pre-clinical studies and is a promising novel surrogate marker of integrity of corticospinal control in individuals with iSCI and other neurological impairments. Future studies should investigate its potential for diagnosis or tracking recovery during rehabilitation.

Individuals with unilateral transtibial amputation exhibit reduced accuracy and precision during a targeted stepping task

Accurate foot placement is important for dynamic balance during activities of daily living. Disruption of sensory information and prosthetic componentry characteristics may result in increased locomotor task difficulty for individuals with lower limb amputation. This study investigated the accuracy and precision of prosthetic and intact foot placement during a targeted stepping task in individuals with unilateral transtibial amputation (IUTAs; N = 8, 47 ± 13 yrs), compared to the preferred foot of control participant’s (N = 8, 33 ± 15 yrs). Participants walked along a 10-metre walkway, placing their foot into a rectangular floor-based target with dimensions normalised to a percentage of participant’s foot length and width; ‘standard’ = 150% x 150%, ‘wide’ = 150% x 200%, ‘long’ = 200% x 150%. Foot placement accuracy (relative distance between foot and target centre), precision (between-trial variability), and foot-reach kinematics were determined for each limb and target, using three-dimensional motion capture. A significant foot-by-target interaction revealed less mediolateral foot placement accuracy for IUTAs in the wide target, which was significantly less accurate for the intact (28 ± 12 mm) compared to prosthetic foot (16 ± 14 mm). Intact peak foot velocity (4.6 ± 0.8 m.s−1) was greater than the prosthetic foot (4.5 ± 0.8 m.s−1) for all targets. Controls were more accurate and precise than IUTAs, regardless of target size. Less accurate and precise intact foot placement in IUTAs, coupled with a faster moving intact limb, is likely due to several factors including reduced proprioceptive feedback and active control during prosthetic limb single stance. This could affect activities of daily living where foot placement is critical, such as negotiating cluttered travel paths or obstacles whilst maintaining balance.

Accurate foot clearance estimation during level and uneven ground walking using inertial sensors

Foot clearance during walking is considered as a key indicator for assessing fall risk, obstacle negotiation strategies and energy expenditure. Foot clearance estimation using inertial measurement units (IMUs) has the advantages of small size, low cost and user-friendliness. However, its application is still limited due to issues with accuracy and reliability. In this paper, we aimed at understanding the limiting factors in foot clearance estimation using low-cost IMUs and proposed a foot clearance estimation method with millimeter-level accuracy. We first analyzed each component in conventional double-integration-based foot clearance estimation, and then proposed a set of new procedures for foot trajectory estimation, including a gait-adaptive complementary filter for orientation estimation, a two-IMU configuration and a shock absorber. Finally, we extracted the foot clearance from the estimated foot trajectory. In the experiments, we recruited eight healthy subjects and instructed them to walk under level and uneven ground conditions; moreover, to validate the applicability of the proposed method, we also instructed the subjects to mimic pathological gaits, including ataxic gait (zigzag walking), waddling gait and Parkinsonian gait. A total of 2640 gait cycles were collected and the extracted foot clearances were benchmarked with the optical motion capture system. With the proposed method, the average mean and standard deviation of the extracted maximal heel clearance and minimal toe clearance in all the gait cycles were −0.34 ± 0.24 cm and 0.02 ± 0.26 cm. The results are more accurate than in previous studies. Most importantly, the proposed method does not require any post correction and flat-floor assumption. The presented foot clearance estimation method provides an applicable and practical clinical solution not only for heel and toe clearance estimation but also for foot trajectory estimation.

Mobility-Related Gaze Training in Individuals With Glaucoma: A Proof-of-Concept Study.

PurposeOlder adults with glaucoma show inappropriate gaze strategies during routine mobility tasks. Furthermore, glaucoma is a risk factor for falling and colliding with objects when walking. However, effective interventions to rectify these strategies and prevent these adverse events are scarce. We designed a gaze training program with the goal of providing proof-of-concept that we could modify mobility-related gaze behavior in this population.MethodsA total of 13 individuals with moderate glaucoma participated in this study. We taught participants general and task-specific gaze strategies over two 1-hour sessions. To determine the efficacy of this gaze training program, participants performed walking tasks that required accurate foot placement onto targets and circumventing obstacles before and after training. We used a mobile eye tracker to quantify gaze and a motion-capture system to quantify body movement.ResultsAfter training, we found changes in the timing between gaze shifts away from targets relative to stepping on them (P < 0.05). In the obstacle negotiation task, we found a greater range of gaze shifts early in walking trials and changes in the timing between gaze shifts away from obstacles after training (P < 0.05), each suggesting better route planning. A posttraining reduction in foot-placement error and obstacle collisions accompanied these changes (P < 0.05).ConclusionsOur results demonstrated that it is possible to modify mobility-related gaze behavior and mobility performance in older adults with glaucoma.Translational RelevanceThis study provides proof-of-concept for a gaze training program for glaucoma. A larger, randomized controlled trial is warranted.

Motor cost affects the decision of when to shift gaze for guiding movement.

Frequent gait modifications are often required to navigate our world. These can involve long or wide steps or changes in direction. People generally prefer to minimize the motor cost (or effort) of a movement, although with changes in gait this is not always possible. The decision of when and where to shift gaze is critical for controlling motor actions, since vision informs the brain about the available choices for movement-in this case, where to step. Here we asked how motor cost influences the allocation of gaze. To address this, we had participants walk and step to the center of sequential targets on the ground. We manipulated the motor cost associated with controlling foot placement by varying the location of one target in the lateral direction on a trial-to-trial basis within environments with different numbers of targets. Costlier steps caused a switch from a gaze strategy of planning future steps to one favoring visual feedback of the current foot placement when participants had to negotiate another target immediately after. Specifically, costlier steps delayed gaze shifts away from the manipulated target. We show that this relates to the cost of moving the leg and redirecting the body's center of mass from target to target. Overall, our results suggest that temporal gaze decisions are affected by motor costs associated with step-to-step demands of the environment. Moreover, they provide insight into what affects the coordination between the eyes and feet for the control of stable and accurate foot placement while walking. NEW & NOTEWORTHY Changes in gait allow us to navigate our world. For instance, one may step long or wide to avoid a spilled drink. The brain can direct gaze to gather relevant information for making these types of motor decisions; however, the factors affecting gaze allocation in natural behaviors are poorly understood. We show how the motor cost associated with a step influences the decision of when to redirect gaze to ensure accurate foot placement while walking.

Gait and Dynamic Balance Sensing Using Wearable Foot Sensors.

Remote monitoring of gait performance offers possibilities for objective evaluation and tackling impairment in motor ability, gait, and balance in populations, such as elderly, stroke, multiple sclerosis, and Parkinson's. This requires a wearable and unobtrusive system capable of estimating ambulatory gait and balance measures, such as the extrapolated center of mass (XCoM) and dynamicmargin of stability. These estimations require the knowledge of 3-D forces and moments (F&M) and accurate foot positions. Though an existing ambulatory gait and balance system (AGBS) consisting of 3-D F&M sensors and inertial measurement units can be used for the purpose, it is bulky and conspicuous. Resistive pressure sensorswere investigated as an alternative to the onboard 3-D F&M sensors. Subject-specific regression models were built to estimate 3-D F&M from 1-D plantar pressures. The model was applicable for different walking speeds. Different pressure sensor configurations were studied to optimize the system complexity and accuracy. Using resistive sensors only under the toe and heel, we were able to estimate the XCoM with a mean absolute rms error of 2.2 ±0.3 cm in the walking direction while walking at a preferred speed, when compared to the AGBS. For the same case, the XCoM was classified as ahead or behind the base of support correctly at 97.7±1.7%. In conclusion, this paper shows that pressure sensors, minimally under the heel and toe, offer a lightweight and inconspicuous alternative for F&M sensing, toward estimating ambulatory gait and dynamic balance.

Influences of Synchronized Metronome Training on Soccer Players' Timing Ability, Performance Accuracy, and Lower-Limb Kinematics.

Planning and performance of all complex movement requires timing, integration, and coordination between sensory-perception and motor production to be successful. Despite this, there is limited research into “if” and “how” timing training may influence movement performance in athletes. The aim of the present study was to investigate the effect of synchronized metronome training (SMT) on sensorimotor timing ability, and in view of that, if improved timing may be transferred to lower-limb movement planning, precision performance, and kinematics. The sample consisted of 24 female elite- and semi-elite soccer players, randomly assigned to receive SMT and a control group. The SMT group received 12 sessions of Interactive Metronome® (IM) training over 4 weeks. At pre- and post-test, timing-precision was assessed through hand and feet movement synchronization with rhythmic sound; and leg-movements performance accuracy, duration, and kinematics were recorded during embodied high cognitive-load stepping task (6 trials×20 s) by use of a optoelectronic motion capture system. Pre- to post-test comparisons showed significant timing improvements as an effect of the IM training. Significant pre- to post-test improvements on the stepping task performance were seen in an increasing number of accurate foot taps during the stepping task sequence and by shorter duration for the SMT-group only. No evident pre- to post-test effects of SMT on the kinematic parameters investigated were found. These findings signify that the guided attention and working-memory functioning may be positively affected by SMT training; thereby, resulting in better motor planning, performance, and movement precision. Still, independent of group and test-occasion, significant correlations were found between the participants’ outcome performance differences and the kinematic parameters. It was found that a decreasing 3D movement distance and less segmented movements correlating negatively, and increasing velocity (speed) positively, with accuracy and performance duration, respectively. These findings are likely associated with inter-individual variations in the nature of higher-order cognitive processing capacity due to the highly cognitive demanding stepping task.

The Role of Movement-Specific Reinvestment in Visuomotor Control of Walking by Older Adults.

The aim of this study was to examine the association between conscious monitoring and control of movements (i.e., movement-specific reinvestment) and visuomotor control during walking by older adults. The Movement-Specific Reinvestment Scale (MSRS) was administered to 92 community-dwelling older adults, aged 65-81 years, who were required to walk along a 4.8-m walkway and step on the middle of a target as accurately as possible. Participants' movement kinematics and gaze behavior were measured during approach to the target and when stepping on it. High scores on the MSRS were associated with prolonged stance and double support times during approach to the stepping target, and less accurate foot placement when stepping on the target. No associations between MSRS and gaze behavior were observed. Older adults with a high propensity for movement-specific reinvestment seem to need more time to "plan" future stepping movements, yet show worse stepping accuracy than older adults with a low propensity for movement-specific reinvestment. Future research should examine whether older adults with a higher propensity for reinvestment are more likely to display movement errors that lead to falling.