Foot shape and plantar pressure relationships in shod and barefoot populations

Biomechanical Effects of the Badminton Split-Step on Forecourt Lunging Footwork

BACKGROUND

This research investigates the biomechanical impact of the split-step technique on forehand and backhand lunges in badminton, aiming to enhance players' on-court movement efficiency. Despite the importance of agile positioning in badminton, the specific contributions of the split-step to the biomechanical impact of lunging footwork still need to be determined.

METHODS

This study examined the lower limb kinematics and ground reaction forces of 18 male badminton players performing forehand and backhand lunges. Data were collected using the VICON motion capture system and Kistler force platforms. Variability in biomechanical characteristics was assessed using paired-sample t-tests and Statistical Parametric Mapping 1D (SPM1D).

RESULTS

The study demonstrates that the split-step technique in badminton lunges significantly affects lower limb biomechanics. During forehand lunges, the split-step increases hip abduction and rotation while decreasing knee flexion at foot contact. In backhand lunges, it increases knee rotation and decreases ankle rotation. Additionally, the split-step enhances the loading rate of the initial ground reaction force peak and narrows the time gap between the first two peaks.

CONCLUSIONS

These findings underscore the split-step's potential in optimizing lunging techniques, improving performance and reducing injury risks in badminton athletes.

Influence of motor capacity of the lower extremity and mobility performance on foot plantar pressures in community-dwelling older women

Objectives

To investigate the associations of motor capacity of the lower extremity and mobility performance in daily physical activities with peak foot plantar pressures during walking among older women.

Methods

Using the data collected among 58 community-dwelling older women (68.66 ± 3.85 years), Pearson correlation and multiple linear regression analyses were performed to analyze the associations of motor capacity of the lower extremity (the 30-s chair stand test, the timed one-leg stance with eyes closed, and the Fugl-Meyer assessment of lower extremity), mobility performance in daily physical activities (the average minutes of moderate to vigorous physical activity every day and the metabolic equivalents), and foot plantar pressures (peak force and peak pressure) with the age and body fat percentage as covariates.

Results

(1) The motor capacity of the lower extremity has higher explanatory power for peak foot plantar pressures compared with the mobility performance in daily physical activities. (2) Higher body fat percentage was positively associated with peak force and pressure, while a lower score on the Fugl-Meyer assessment of lower extremity was negatively associated with both of them. (3) The metabolic equivalents were positively associated with the peak force, while the 30-s chair stand test was negatively associated with it.

Conclusions

Mobility performance in daily physical activities can be significant predictors for peak foot plantar pressures among older women. The significant predictor variables include the Fugl-Meyer assessment of lower extremity, the 30-s chair stand test, and metabolic equivalents.

Design of Double Conductive Layer and Grid-Assistant Face-to-Face Structure for Wide Linear Range, High Sensitivity Flexible Pressure Sensors

Recently, flexible pressure sensors have drawn great attention because of their potential application in human-machine interfaces, healthcare monitoring, electronic skin, etc. Although many sensors with good performance have been reported, researchers mostly focused on surface morphology regulation, and the effect of the resistance characteristics on the performance of the sensor was still rarely systematically investigated. In this paper, a strategy for modulating electron transport is proposed to adjust the linear range and sensitivity of the sensor. In the modulating process, we constructed a double conductive layer (DCL) and grid-assistant face-to-face structure and obtained the sensor with a wide linear range of 0-700 kPa and a high sensitivity of 57.5 kPa-1, which is one of the best results for piezoresistive sensors. In contrast, the sensor with a single conductive layer (SCL) and simple face-to-face structure exhibited a moderate linear range (7 kPa) and sensitivity (2.8 kPa-1). Benefiting from the great performance, the modulated sensor allows for clear pulse wave detection and good recognition of gait signals, which indicates the great application potential in human daily life.

Pedobarographic evaluations in physical medicine and rehabilitation practice

The feet are complex structures that transmit loads transferred by other parts of the body to the ground and are involved in many static and dynamic activities, such as standing and walking. The contact area and pressure changes between the feet and the ground surface can be measured using pedobarographic devices. With pedobarographic examinations, it is possible to obtain a wide range of information needed to support clinical evaluation and diagnostic tests in physical medicine and rehabilitation practice. Foot structure and function, postural stability, lower extremity biomechanics, and gait analysis are among the areas that can be further investigated using pedobarography.

A Data-Driven Approach for Fatigue Detection during Running Using Pedobarographic Measurements

Background

Detecting fatigue at the early stages of a run could aid training programs in making adjustments, thereby reducing the heightened risk of injuries from overuse. The study aimed to investigate the effects of running fatigue on plantar force distribution in the dominant and nondominant feet of amateur runners.

Methods

Thirty amateur runners were recruited for this study. Bilateral time-series plantar forces were employed to facilitate automatic fatigue gait recognition using convolutional neural network (CNN) and CNN-based long short-term memory network (ConvLSTM) models. Plantar force data collection was conducted both before and after a running-induced fatigue protocol using a FootScan force plate. The Keras library in Python 3.8.8 was used to train and tune deep learning models.

Results

The results demonstrated that more mid-forefoot and heel force occurs during bilateral plantar and less midfoot fore force occurs in the dominant limb after fatigue (p < 0.001). The time of peak forces was significantly shortened at the midfoot and sum region of the nondominant foot, while it was delayed at the hallux region of the dominant foot (p < 0.001). In addition, the ConvLSTM model showed higher performance (Accuracy = 0.867, Sensitivity = 0.874, and Specificity = 0.859) in detecting fatigue gait than CNN (Accuracy = 0.800, Sensitivity = 0.874, and Specificity = 0.718).

Conclusions

The findings of this study could offer empirical data for evaluating risk factors linked to overuse injuries in a single limb, as well as facilitate early detection of fatigued gait.

Intelligent prediction of lower extremity loadings during badminton lunge footwork in a lab-simulated court

Introduction: Playing badminton has been reported with extensive health benefits, while main injuries were documented in the lower extremity. This study was aimed to investigate and predict the knee- and ankle-joint loadings of athletes who play badminton, with "gold standard" facilities. The axial impact acceleration from wearables would be used to predict joint moments and contact forces during sub-maximal and maximal lunge footwork. Methods: A total of 25 badminton athletes participated in this study, following a previously established protocol of motion capture and musculoskeletal modelling techniques with the integration of a wearable inertial magnetic unit (IMU). We developed a principal component analysis (PCA) statistical model to extract features in the loading parameters and a multivariate partial least square regression (PLSR) machine learning model to correlate easily collected variables, such as the stance time, approaching velocity, and peak accelerations, with knee and ankle loading parameters (moments and contact forces). Results: The key variances of joint loadings were observed from statistical principal component analysis modelling. The promising accuracy of the partial least square regression model using input parameters was observed with a prediction accuracy of 94.52%, while further sensitivity analysis found a single variable from the ankle inertial magnetic unit that could predict an acceptable range (93%) of patterns and magnitudes of the knee and ankle loadings. Conclusion: The attachment of this single inertial magnetic unit sensor could be used to record and predict loading accumulation and distribution, and placement would exhibit less influence on the motions of the lower extremity. The intelligent prediction of loading patterns and accumulation could be integrated to design training and competition schemes in badminton or other court sports in a scientific manner, thus preventing fatigue, reducing loading-accumulation-related injury, and maximizing athletic performance.

Complexity of spatio-temporal plantar pressure patterns during everyday behaviours

The human foot sole is the primary interface with the external world during balance and walking, and also provides important tactile information on the state of contact. However, prior studies on plantar pressure have focused mostly on summary metrics such as overall force or centre of pressure under limited conditions. Here, we recorded spatio-temporal plantar pressure patterns with high spatial resolution while participants completed a wide range of daily activities, including balancing, locomotion and jumping tasks. Contact area differed across task categories, but was only moderately correlated with the overall force experienced by the foot sole. The centre of pressure was often located outside the contact area or in locations experiencing relatively low pressure, and therefore a result of disparate contact regions spread widely across the foot. Non-negative matrix factorization revealed low-dimensional spatial complexity that increased during interaction with unstable surfaces. Additionally, pressure patterns at the heel and metatarsals decomposed into separately located and robustly identifiable components, jointly capturing most variance in the signal. These results suggest optimal sensor placements to capture task-relevant spatial information and provide insight into how pressure varies spatially on the foot sole during a wide variety of natural behaviours.

Understanding the Role of Children's Footwear on Children's Feet and Gait Development: A Systematic Scoping Review

Children's footwear plays an important role in the healthy growth of foot and gait development during the growing stage. This review aims to synthesize findings of previous investigations and to explore the biomechanical influences of different types of children's footwear on foot health and gait development, thus guiding the healthy and safe growth of children's feet and gait. Online databases were searched for potential eligible articles, including Web of Science, Google Scholar, and PubMed. In total, nineteen articles were identified after searching based on the inclusion requirements. The following five aspects of biomechanical parameters were identified in the literature, including spatiotemporal, kinematics, kinetics, electromyography (EMG), and plantar pressure distribution. Children's footwear can affect their foot health and gait performance. In addition, children's shoes with different flexibility and sole hardness have different effects on children's feet and gait development. Compared to barefoot, the stride length, step length, stride time, and step time were increased, but cadence was decreased with wearing shoes. Furthermore, the support base and toe-off time increased. Double support time and stance time increased, but single support time decreased. The hip, knee, and ankle joints showed increased range of motion in children with the rear-foot strike with larger ground reaction force as well. Future studies may need to evaluate the influence of footwear types on gait performance of children in different age groups. Findings in this study may provide recommendations for suitable footwear types for different ages, achieving the aim of growth and development in a healthy and safe manner.

Toward improved understanding of foot shape, foot posture, and foot biomechanics during running: A narrative review

The current narrative review has explored known associations between foot shape, foot posture, and foot conditions during running. The artificial intelligence was found to be a useful metric of foot posture but was less useful in developing and obese individuals. Care should be taken when using the foot posture index to associate pronation with injury risk, and the Achilles tendon and longitudinal arch angles are required to elucidate the risk. The statistical shape modeling (SSM) may derive learnt information from population-based inference and fill in missing data from personalized information. Bone shapes and tissue morphology have been associated with pathology, gender, age, and height and may develop rapid population-specific foot classifiers. Based on this review, future studies are suggested for 1) tracking the internal multi-segmental foot motion and mapping the biplanar 2D motion to 3D shape motion using the SSM; 2) implementing multivariate machine learning or convolutional neural network to address nonlinear correlations in foot mechanics with shape or posture; 3) standardizing wearable data for rapid prediction of instant mechanics, load accumulation, injury risks and adaptation in foot tissue and bones, and correlation with shapes; 4) analyzing dynamic shape and posture via marker-less and real-time techniques under real-life scenarios for precise evaluation of clinical foot conditions and performance-fit footwear development.

Analysis of hallux valgus angles automatically extracted from 3D foot scans taken in North America, Europe, and Asia

The forefoot is the foot part most affected by ill-fitting shoes. Footwear fitting considers the measurements of length, width, and arch length. Toe shape has not yet been used in sizing feet and fitting shoes. This study aims to investigate the variation in toe shape, as measured by the hallux valgus angle. An automatic and reproducible hallux valgus angle measuring method using 3D foot scans with no palpation markers is proposed and applied to about half a million samples collected across North America, Europe, and Asia. The measuring method is robust and can detect the medial contour along the proximal phalanx even in extreme cases. The hallux valgus angle has a normal distribution with long tails on both sides in the general population. Large dispersions of HVA values were observed for both genders and in all three geographical regions. Practitioner summary: The hallux valgus angle has a broad distribution in the general population. Females have larger hallux valgus angles than males, and people from Asia have larger hallux valgus angles than people from North America and Europe. Shoe toe boxes should be designed to fit the actual shapes of shoppers' toes. The proposed method for measuring HVA opens a new opportunity to study the causal relationship between shoe wearing habits and HVA on a large scale.

Recent Machine Learning Progress in Lower Limb Running Biomechanics With Wearable Technology: A Systematic Review

With the emergence of wearable technology and machine learning approaches, gait monitoring in real-time is attracting interest from the sports biomechanics community. This study presents a systematic review of machine learning approaches in running biomechanics using wearable sensors. Electronic databases were retrieved in PubMed, Web of Science, SPORTDiscus, Scopus, IEEE Xplore, and ScienceDirect. A total of 4,068 articles were identified via electronic databases. Twenty-four articles that met the eligibility criteria after article screening were included in this systematic review. The range of quality scores of the included studies is from 0.78 to 1.00, with 40% of articles recruiting participant numbers between 20 and 50. The number of inertial measurement unit (IMU) placed on the lower limbs varied from 1 to 5, mainly in the pelvis, thigh, distal tibia, and foot. Deep learning algorithms occupied 57% of total machine learning approaches. Convolutional neural networks (CNN) were the most frequently used deep learning algorithm. However, the validation process for machine learning models was lacking in some studies and should be given more attention in future research. The deep learning model combining multiple CNN and recurrent neural networks (RNN) was observed to extract different running features from the wearable sensors and presents a growing trend in running biomechanics.

Machine Learning Strategies for Low-Cost Insole-Based Prediction of Center of Gravity during Gait in Healthy Males

Whole-body center of gravity (CG) movements in relation to the center of pressure (COP) offer insights into the balance control strategies of the human body. Existing CG measurement methods using expensive measurement equipment fixed in a laboratory environment are not intended for continuous monitoring. The development of wireless sensing technology makes it possible to expand the measurement in daily life. The insole system is a wearable device that can evaluate human balance ability by measuring pressure distribution on the ground. In this study, a novel protocol (data preparation and model training) for estimating the 3-axis CG trajectory from vertical plantar pressures was proposed and its performance was evaluated. Input and target data were obtained through gait experiments conducted on 15 adult and 15 elderly males using a self-made insole prototype and optical motion capture system. One gait cycle was divided into four semantic phases. Features specified for each phase were extracted and the CG trajectory was predicted using a bi-directional long short-term memory (Bi-LSTM) network. The performance of the proposed CG prediction model was evaluated by a comparative study with four prediction models having no gait phase segmentation. The CG trajectory calculated with the optoelectronic system was used as a golden standard. The relative root mean square error of the proposed model on the 3-axis of anterior/posterior, medial/lateral, and proximal/distal showed the best prediction performance, with 2.12%, 12.97%, and 12.47%. Biomechanical analysis of two healthy male groups was conducted. A statistically significant difference between CG trajectories of the two groups was shown in the proposed model. Large CG sway of the medial/lateral axis trajectory and CG fall of the proximal/distal axis trajectory is shown in the old group. The protocol proposed in this study is a basic step to have gait analysis in daily life. It is expected to be utilized as a key element for clinical applications.

Automatic Classification of Barefoot and Shod Populations Based on the Foot Metrics and Plantar Pressure Patterns

The human being’s locomotion under the barefoot condition enables normal foot function and lower limb biomechanical performance from a biological evolution perspective. No study has demonstrated the specific differences between habitually barefoot and shod cohorts based on foot morphology and dynamic plantar pressure during walking and running. The present study aimed to assess and classify foot metrics and dynamic plantar pressure patterns of barefoot and shod people via machine learning algorithms. One hundred and forty-six age-matched barefoot (n = 78) and shod (n = 68) participants were recruited for this study. Gaussian Naïve Bayes were selected to identify foot morphology differences between unshod and shod cohorts. The support vector machine (SVM) classifiers based on the principal component analysis (PCA) feature extraction and recursive feature elimination (RFE) feature selection methods were utilized to separate and classify the barefoot and shod populations via walking and running plantar pressure parameters. Peak pressure in the M1-M5 regions during running was significantly higher for the shod participants, increasing 34.8, 37.3, 29.2, 31.7, and 40.1%, respectively. The test accuracy of the Gaussian Naïve Bayes model achieved an accuracy of 93%. The mean 10-fold cross-validation scores were 0.98 and 0.96 for the RFE- and PCA-based SVM models, and both feature extract-based and feature select-based SVM models achieved an accuracy of 95%. The foot shape, especially the forefoot region, was shown to be a valuable classifier of shod and unshod groups. Dynamic pressure patterns during running contribute most to the identification of the two cohorts, especially the forefoot region.

Understanding Foot Loading and Balance Behavior of Children with Motor Sensory Processing Disorder

Sensory processing disorder (SPD) could influence the neuromuscular response and adjustment to external sensory discrimination and lead to disruptions in daily locomotion. The objective of the current study was to compare plantar loadings and foot balance during walking, running and turning activities in SPD children in order to reveal the behavioral strategy of movement and balance control. Six SPD children and six age-match healthy controls participated in the test using a FootScan plantar pressure plate. The time-varying parameters of forces, center of pressure and foot balance index were analyzed using an open-source one-dimensional Statistical Parametric Mapping (SPM1d) package. No difference was found in foot balance and plantar loadings during walking, while limited supination–pronation motion was observed in the SPD children during running and turning. The plantar forces were mainly located in the midfoot region while less toe activity was found as well. Findings should be noted that SPD children had limited supination–pronation movement for shock attenuation in the foot complex and reduced ankle pronation to assist push-off and toe gripping movements. Understanding the behavior of plantar loading strategy and balance control during walking, running and turning activities may provide clinical implications for the rehabilitation and training of daily tasks.

Unique foot posture in Neanderthals reflects their body mass and high mechanical stress

Neanderthal foot bone proportions and morphology are mostly indistinguishable from those of Homo sapiens, with the exception of several distinct Neanderthal features in the talus. The biomechanical implications of these distinct talar features remain contentious, fueling debate around the adaptive meaning of this distinctiveness. With the aim of clarifying this controversy, we test phylogenetic and behavioral factors as possible contributors, comparing tali of 10 Neanderthals and 81 H. sapiens (Upper Paleolithic and Holocene hunter-gatherers, agriculturalists, and postindustrial group) along with the Clark Howell talus (Omo, Ethiopia). Variation in external talar structures was assessed through geometric morphometric methods, while bone volume fraction and degree of anisotropy were quantified in a subsample (n = 45). Finally, covariation between point clouds of site-specific trabecular variables and surface landmark coordinates was assessed. Our results show that although Neanderthal talar external and internal morphologies were distinct from those of H. sapiens groups, shape did not significantly covary with either bone volume fraction or degree of anisotropy, suggesting limited covariation between external and internal talar structures. Neanderthal external talar morphology reflects ancestral retentions, along with various adaptations to high levels of mobility correlated to their presumably unshod hunter-gatherer lifestyle. This pairs with their high site-specific trabecular bone volume fraction and anisotropy, suggesting intense and consistently oriented locomotor loading, respectively. Relative to H.sapiens, Neanderthals exhibit differences in the talocrural joint that are potentially attributable to cultural and locomotor behavior dissimilarity, a talonavicular joint that mixes ancestral and functional traits, and a derived subtalar joint that suggests a predisposition for a pronated foot during stance phase. Overall, Neanderthal talar variation is attributable to mobility strategy and phylogenesis, while H. sapiens talar variation results from the same factors plus footwear. Our results suggest that greater Neanderthal body mass and/or higher mechanical stress uniquely led to their habitually pronated foot posture.

Effects of Fatigue Running on Joint Mechanics in Female Runners: A Prediction Study Based on a Partial Least Squares Algorithm

Background: Joint mechanics are permanently changed using different intensities and running durations. These variations in intensity and duration also influence fatigue during prolonged running. Little is known about the potential interactions between fatigue and joint mechanics in female recreational runners. Thus, the purpose of this study was to describe and examine kinematic and joint mechanical parameters when female recreational runners are subject to fatigue as a result of running.

Method: Fifty female recreational runners maintained running on a treadmill to induce fatigue conditions. Joint mechanics, sagittal joint angle, moment, and power were recorded pre- and immediately post fatigue treadmill running.

Result: Moderate reductions in absolute positive ankle power, total ankle energy dissipation, dorsiflexion at initial contact, max dorsiflexion angle, and range of motion of the joint ankle were collected after fatigue following prolonged fatigue running. Knee joint mechanics, joint angle, and joint power remained unchanged after prolonged fatigue running. Nevertheless, with the decreased ankle joint work, negative knee power increased. At the hip joint, the extension angle was significantly decreased. The range motion of the hip joint, hip positive work and hip positive power were increased during the post-prolonged fatigue running.

Conclusion: This study found no proximal shift in knee joint mechanics in amateur female runners following prolonged fatigue running. The joint work redistribution was associated with running fatigue changes. As for long-distance running, runners should include muscle strength training to avoid the occurrence of running-related injuries.

Dynamic foot morphology explained through 4D scanning and shape modeling

A detailed understanding of foot morphology can enable the design of more comfortable and better fitting footwear. However, foot morphology varies widely within the population, and changes dynamically as the foot is loaded during stance. This study presents a parametric statistical shape model from 4D foot scans to capture both the inter- and intra-individual variability in foot morphology. Thirty subjects walked on a treadmill while 4D scans of their right foot were taken at 90 frames-per second during stance phase. Each subject's height, weight, foot length, foot width, arch length, and sex were also recorded. The 4D scans were all registered to a common high-quality foot scan, and a principal component analysis was done on all processed 4D scans. Elastic-net linear regression models were built to predict the principal component scores, which were then inverse transformed into 4D scans. The best performing model was selected with leave-one-out cross-validation. The chosen model predicts foot morphology across stance phase with a root-mean-square error of 5.2 ± 2.0 mm and a mean Hausdorff distance of 25.5 ± 13.4 mm. This study shows that statistical shape modeling can be used to predict dynamic changes in foot morphology across the population. The model can be used to investigate and improve foot-footwear interaction, allowing for better fitting and more comfortable footwear.

Relationship between Firefighter Physical Fitness and Special Ability Performance: Predictive Research Based on Machine Learning Algorithms

Firefighters require a high level of physical fitness to meet the demands of their job. The correlations and contributions of individual physical health parameters to the tasks of firefighting would enable firefighters to focus on the effects of specific physical conditions during their physical training programs. Therefore, the purpose of the present study was to identify the relationships between various physical health parameters (weight, maximum oxygen uptake, body fat percentage, upper body muscular power and lower body muscular power) and performance on simulated firefighting ability tasks, which included a set of seven tasks (rope climb, run 200 m round trip with load, 60 m carrying a ladder, climb stairs with load, evacuation of 400 m with supplies, run 5 km with an air respirator, run 100 m with the water hose). Through use of a partial least-squares regression (PLSR) algorithm to analyze the linear correlation, we revealed the change in various training performances of specific ability tests with physical fitness parameters. The present study demonstrated significant relationships among physical health parameters and performance on simulated firefighting ability tasks, which also represent that those parameters contributed significantly to the model’s predictive power and were suitable predictors of the simulated firefighting tasks score.

Longitudinal Analysis of Plantar Pressures with Wear of a Running Shoe

Running shoes typically have a lifespan of 300–1000 km, and the plantar pressure pattern during running may change as the shoe wears. So, the aim of this study was to determine the variation of plantar pressures with shoe wear, and the runner’s subjective sensation. Maximun Plantar Pressures (MMP) were measured from 33 male recreational runners at three times during a training season (beginning, 350 km, and 700 km) using the Biofoot/IBV^® in-shoe system (Biofoot/IBV^®, Valencia, Spain). All the runners wore the same shoes (New Balance^® 738, Boston, MA, USA) during this period, and performed similar training. The zones supporting most pressure at all three study times were the medial (inner) column of the foot and the forefoot. There was a significant increase in pressure on the midfoot over the course of the training season (from 387.8 to 590 kPa, p = 0.003). The runners who felt the worst cushioning under the midfoot were those who had the highest peak pressures in that area (p = 0.002). The New Balance^® 738 running shoe effectively maintains the plantar pressure pattern after 700 km of use under all the zones studied except the midfoot, probably due to material fatigue or deficits of the specific cushioning systems in that area.