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Flat foot, or pes planus, is a common deformity marked by the collapse of the medial longitudinal arch, potentially affecting gait mechanics and joint loading. Traditional diagnostic methods such as radiography and footprint analysis have limitations, encouraging the use of biomechanical tools for more objective assessment. This study investigated gait differences between individuals with and without flatfoot using an integrated optical motion capture and force plate system. Twenty adults aged 18–59 years participated, including five clinically diagnosed with flatfoot and fifteen with normal arches, all within a normal BMI range. Reflective markers were attached following a modified Helen Hayes set, and gait trials were recorded at 240 Hz using eight cameras synchronized with a force plate. Kinematic parameters, particularly knee joint range of motion, and kinetic parameters including center of pressure trajectories were extracted and compared statistically by t-test with significance 95%. Results showed no statistically significant differences between the two groups (p-value ˃ 0.4), although the flatfoot group demonstrated slightly reduced knee ROM and minor COP variations. These findings suggest that mild flatfoot can be compensated by proximal joint adjustments, resulting in gait patterns similar to those with normal feet during level walking. Despite the limited sample size, the study demonstrated the feasibility of combining motion capture and force plate analysis for flatfoot assessment and highlighted the need for further research with larger cohorts and more challenging gait tasks.

The purpose of this study was to determine the effect of sampling frequency on the 90–90° (90-degrees hip and knee flexion) isometric hamstring assessment. Thirty-three elite female soccer players (age: 18.7 ± 3.7 years; height: 158.3 ± 5.9 cm; body mass: 62.8 ± 5.5 kg) performed three unilateral trials on a single occasion of the 90–90° isometric hamstring assessment. Force-time data were collected using force plates at 1000 Hz and down sampled to 500-, 250-, and 100 Hz. Peak force (N), force (N) at 100- and 200 ms and average rate of force development (aRFD) (N/s) over a 100- and 200 ms epoch were calculated. A repeated measures of analysis of variance and effect size was used to compare means. Excellent absolute and good relative reliability was observed for peak force across all sampling frequencies. Force at 100- and 200 ms and aRFD over 100 ms and 200 ms resulted poor-moderate relative reliability and poor-excellent absolute reliability. No significant trivial differences were observed for peak force between sampling frequencies ( P  > 0.05, Cohen’s d  = 0.02–0.12). A significant difference ( P  < 0.001) was identified in 500, 250 and 100 Hz, with small-moderate and small-large increases in force at set time points and aRFD, respectively, in comparison to 1000 Hz ( d  = 0.21–2.00). Higher sampling frequencies (> 500 Hz) reduces the reliability of time dependent force characteristics, with minimal effect on peak force. Regular monitoring of peak force can be performed with higher sampling frequencies, but lower sampling frequencies would be beneficial to collect reliable rapid-force generating measures.

Insects exhibit excellent maneuvers such as running and flying despite their small bodies; therefore, their locomotion mechanism is expected to provide a design guideline for micromachines. Numerical simulations have been performed to elucidate this mechanism, whereby it is important to develop a model that is physically identical to the target insect’s parts to reproduce kinematic dynamics. In particular, in flight, the shape and mass of wings, which flap at high frequencies, are significant parameters. However, small insects such as fruit flies have small, thin, and light wings; thus, their mass cannot be easily measured. In this study, we proposed a high-resolution and simple force plate to measure the mass of each part of a tiny insect. The device consists of a circular plate supported by flat spiral springs made of polyimide film, and a laser displacement meter that detects the displacement of the center of the plate. The simple plate fabrication process requires only a couple of minutes. A fabricated force plate with a sub-N/m spring constant achieved a resolution of less than 2 µg. As a demonstration, the wing mass of the fruit flies was measured. The experimental results suggest that the wings accounted for approximately 0.4% of the body mass.

Microforce plates are indispensable tools for quantitatively evaluating the behavior of small objects such as tiny insects or microdroplets. The two main measurement principles for microforce plates are: the formation of strain gauges on the beam that supports the plate and the measurement of the deformation of the plate using an external displacement meter. The latter method is characterized by its ease of fabrication and durability as strain concentration is not required. To enhance the sensitivity of the latter type of force plates with a planar structure, thinner plates are generally desired. However, brittle material force plates that are both thin and large and can be fabricated easily have not yet been developed. In this study, a force plate consisting of a thin glass plate with a planar spiral spring structure and a laser displacement meter placed under the plate center is proposed. The plate deforms downward when a force is exerted vertically on its surface, resulting in the determination of the applied force using Hooke’s law. The force plate structure is easily fabricated by laser processing combined with the microelectromechanical system (MEMS) process. The fabricated force plate has a radius and thickness of 10 mm and 25 µm, respectively, with four supporting spiral beams of sub-millimeter width. A fabricated force plate featuring a sub-N/m spring constant achieves a resolution of approximately 0.01 µN.

Inverse dynamic analysis is a technique used during gait analysis to estimate intersegmental forces and net joint moments. Inverse dynamic calculations are susceptible to various forms of error. One such error is force plate drift, often produced by humidity condensing within the input connectors and electronics, causing an undesired change in output over time. This can be particularly concerning for movement laboratories where inverse dynamics are considered in clinical decision-making processes. Manufacturers will provide tolerance levels for drift. However, levels of acceptable drift are rarely considered from a clinical perspective. Therefore, this study aims to establish clinically acceptable limits of force plate drift error, induced by applying systematic errors to force plate channels, on predicted lower limb joint moments during gait. Gait data of 10 children with typical development were analysed and induced errors of 0.5 N, 1 N, 1.5 N, 3 N, 6 N and 12 N were incrementally applied to the horizontal and vertical force channels. Data were recalculated for each increment and mean profiles compared to an error free mean (±1SD) band. Error was deemed clinically significant when moments fell outside the mean (±1SD) band. Induced error at 6 N and above was sufficient to cause a clinically significant change. Sagittal and coronal plane moments at the hip were most affected, followed by the knee and then the ankle. While manufacturer guidelines for acceptable drift are usually well below 6 N, care is needed when using force plates over several minutes or more as drift may eventually exceed clinically acceptable limits.

It is unclear whether postural sway characteristics could be used as diagnostic biomarkers for autism spectrum disorder (ASD). The purpose of this study was to develop and validate an automated identification of postural control patterns in children with ASD using a machine learning approach. 50 children aged 5–12 years old were recruited and assigned into two groups: ASD (n = 25) and typically developing groups (n = 25). Participants were instructed to stand barefoot on two feet and maintain a stationary stance for 20 s during two conditions: (1) eyes open and (2) eyes closed. The center of pressure (COP) data were collected using a force plate. COP variables were computed, including linear displacement, total distance, sway area, and complexity. Six supervised machine learning classifiers were trained to classify the ASD postural control based on these COP variables. All machine learning classifiers successfully identified ASD postural control patterns based on the COP features with high accuracy rates (>0.800). The naïve Bayes method was the optimal means to identify ASD postural control with the highest accuracy rate (0.900), specificity (1.000), precision (1.000), F1 score (0.898) and satisfactory sensitivity (0.826). By increasing the sample size and analyzing more data/features of postural control, a better classification performance would be expected. The use of computer-aided machine learning to assess COP data is efficient, accurate, with minimum human intervention and thus, could benefit the diagnosis of ASD.

Parkinson’s disease (PD) is associated with characteristic gait impairment, motivating objective screening methods based on biomechanical signals. This study presents a lightweight, physics-informed framework for PD gait screening using ground reaction force (GRF) signals acquired from force plates, together with a prototype acquisition-and-analysis system for practical screening workflows. Continuous GRF recordings are segmented into complete gait cycles, from which bilateral physics-informed features are constructed, including normalized force, dynamics-derived acceleration and velocity, and friction-related descriptors. The resulting feature tensor is then standardized and used as input to a Feature-Grouped Gated Fusion Network (FGGF-Net). The proposed model separately encodes force–acceleration features and velocity–ratio features using low-order nonlinear and linear pathways, respectively, and integrates them via gated fusion with a residual baseline pathway. Under subject-wise five-fold cross-validation, FGGF-Net achieves strong subject-level performance, reaching 94.8% accuracy, 92.9% F1-score, and 0.974 AUC, while consistently outperforming representative baselines. Ablation studies further verify the effectiveness of feature grouping and gated fusion. In addition, the trained model remains compact (1.09 M parameters, 4.16 MB) and supports millisecond-level CPU inference, making the proposed framework promising for practical force-plate screening workflows.

The rapid evolution of technology has led to a proliferation of wearable devices. These devices have a wide range of applications in hospital health care, health monitoring, and sports. In sports science, it is possible to assess an athlete’s neuromuscular function via explosive power in the legs, and the most common test for this is the counter-movement jump (CMJ). Traditionally, to assess the explosive power of an athlete’s legs, researchers ask the athlete to stand on a force plate and perform a CMJ several times. From this, seven variables are calculated using the force-time curve measured by the force plate, and then these variables are interpreted by sports professionals to evaluate the goodness of the CMJ. However, a force plate is expensive and difficult to transport. Taking this into account, this paper designs a machine learning-based model to predict CMJ performance variables via an economical and wearable device with inertial measurement units (IMUs). The experimental results demonstrate that the proposed method is capable of predicting most performance variables of CMJ with an acceptable rate of error. Finally, we also implement a real-time performance variable measurement system to demonstrate the applicability of the proposed method.

The aim of the study was to identify changes in the mechanism of postural control among ballroom dancers between standing solo and standing with a partner during specific standard dance positions. Specifically, the study attempted to determine whether the male partner plays a stabilising role in the dance couple. A total of seven competitive dance couples participated in the study. The experimental procedure comprised four dance positions characteristic of international standard dances: standard, starting, chasse and contra check. The dance positions were staged twice – while standing solo and while standing with a partner. The assumption of the assessed position was preceded by a dance phase after which the participants were instructed to freeze on a force plate and hold the position for 30 s. To examine whether subjects standing solo or with partners had greater rambling (RM) or trembling (TR) components in their dance postural profile, the ratios of RM to the center of foot pressure (COP) and TR to COP were computed for velocity. No significant differences were observed in the velocity of COP between standing solo and standing with a partner (p > 0.05). However, during the standard and starting positions, female and male dancers standing solo were characterised by higher values of the velocity of RM/COP ratio and lower values of the velocity of TR/COP ratio than those standing with a partner (p < 0.05). According to the theory behind the RM and TR decomposition, an increase in TR components could indicate a higher reliance on spinal reflexes, which would suggest greater automaticity.

Balance is a complex, sensorimotor task requiring an individual to maintain the center of gravity within the base of support. Quantifying balance in a reliable and valid manner is essential to evaluating disease progression, aging complications, and injuries in clinical and research settings. Typically, researchers use force plates to track motion of the center of gravity during a variety of tasks. However, limiting factors such as cost, portability, and availability have hindered postural stability evaluation in these settings. This study compared the “gold standard” for assessing postural stability (i.e., the laboratory-grade force plate) to a more affordable and portable assessment tool (i.e., BTrackS balance plate) in healthy young adults. Correlations and Bland-Altman plots between the center of pressure outcome measures derived from these two instruments were produced. Based on the results of this study, the measures attained from the portable balance plate objectively quantified postural stability with high validity on both rigid and compliant surfaces, demonstrated by thirty-five out of thirty-eight observed postural stability metrics in both surface conditions with a correlation of 0.98 or greater. The low cost, portable system performed similarly to the lab-grade force plate indicating the potential for practitioners and researchers to use the BTrackS balance plate as an alternative to the more expensive force plate option for assessing postural stability, whether in the lab setting or in the field.