Explore the vast range of titles available.

Accurate estimation of the center of mass is necessary for evaluating balance control during quiet standing. However, no practical center of mass estimation method exists because of problems with estimation accuracy and theoretical validity in previous studies that used force platforms or inertial sensors. This study aimed to develop a method for estimating the center of mass displacement and velocity based on equations of motion describing the standing human body. This method uses a force platform under the feet and an inertial sensor on the head and is applicable when the support surface moves horizontally. We compared the center of mass estimation accuracy of the proposed method with those of other methods in previous studies using estimates from the optical motion capture system as the true value. The results indicate that the present method has high accuracy in quiet standing, ankle motion, hip motion, and support surface swaying in anteroposterior and mediolateral directions. The present method could help researchers and clinicians to develop more accurate and effective balance evaluation methods.

Measuring the ground reaction forces (GRF) underlying sprint acceleration is important to understanding the performance of such a common task. Until recently direct measurements of GRF during sprinting were limited to a few steps per trial, but a simple method (SM) was developed to estimate GRF across an entire acceleration. The SM utilizes displacement- or velocity-time data and basic computations applied to the runner’s center of mass and was validated against compiled force plate (FP) measurements; however, this validation used multiple-trials to generate a single acceleration profile, and consequently fatigue and error may have introduced noise into the analyses. In this study, we replicated the original validation by comparing the main sprint kinetics and force-velocity-power variables (e.g. GRF and its horizontal and vertical components, mechanical power output, ratio of horizontal component to resultant GRF) between synchronized FP data from a single sprinting acceleration and SM data derived from running velocity measured with a 100 Hz laser. These analyses were made possible thanks to a newly developed 50-m FP system providing seamless GRF data during a single sprint acceleration. Sixteen trained male sprinters performed two all-out 60-m sprints. We observed good agreement between the two methods for kinetic variables (e.g. grand average bias of 4.71%, range 0.696 ± 0.540–8.26 ± 5.51%), and high inter-trial reliability (grand average standard error of measurement of 2.50% for FP and 2.36% for the SM). This replication study clearly shows that when implemented correctly, this method accurately estimates sprint acceleration kinetics.

Nowadays, it becomes of paramount societal importance to support many frail-prone groups in our society (elderly, patients with neurodegenerative diseases, etc.) to remain socially and physically active, maintain their quality of life, and avoid their loss of autonomy. Once older people enter the prefrail stage, they are already likely to experience falls whose consequences may accelerate the deterioration of their quality of life (injuries, fear of falling, reduction of physical activity). In that context, detecting frailty and high risk of fall at an early stage is the first line of defense against the detrimental consequences of fall. The second line of defense would be to develop original protocols to detect future fallers before any fall occur. This paper briefly summarizes the current advancements and perspectives that may arise from the combination of affordable and easy-to-use non-wearable systems (force platforms, 3D tracking motion systems), wearable systems (accelerometers, gyroscopes, inertial measurement units-IMUs) with appropriate machine learning analytics, as well as the efforts to address these challenges.

The purpose of the present study was (i) to explore the reliability of the most commonly used countermovement jump (CMJ) metrics, and (ii) to reduce a large pool of metrics with acceptable levels of reliability via principal component analysis to the significant factors capable of providing distinctive aspects of CMJ performance. Seventy-nine physically active participants (thirty-seven females and forty-two males) performed three maximal CMJs while standing on a force platform. Each participant visited the laboratory on two occasions, separated by 24–48 h. The most reliable variables were performance variables (CV = 4.2–11.1%), followed by kinetic variables (CV = 1.6–93.4%), and finally kinematic variables (CV = 1.9–37.4%). From the 45 CMJ computed metrics, only 24 demonstrated acceptable levels of reliability (CV ≤ 10%). These variables were included in the principal component analysis and loaded a total of four factors, explaining 91% of the CMJ variance: performance component (variables responsible for overall jump performance), eccentric component (variables related to the breaking phase), concentric component (variables related to the upward phase), and jump strategy component (variables influencing the jumping style). Overall, the findings revealed important implications for sports scientists and practitioners regarding the CMJ-derived metrics that should be considered to gain a comprehensive insight into the biomechanical parameters related to CMJ performance.

In this paper, the solution method for foot arch index (FAI) based on plantar force measurement was proposed. The entire pelma (EP) was divided into three partitions: posterior heel (HP), lateral side of the sole (SL) and medial side of the sole (SM) according to the three-point support mechanics mechanism of the foot and ankle. A distributed force platform was established to obtain the mean positions of the center of pressure (CoP) trajectories on SL, SM, HP, and EP, which were defined as A, B, C, and O, respectively. Based on the principle that the arch height influences the distance from point O to the boundary of triangle ABC, the area ratio of triangle BOC to triangle ABC was defined as FAI. Arch height index (AHI) measurement of thirty participants by combined calipers was compared with FAI measurement of their right feet. The arches were classified based on AHI, and ANOVA was performed. The Pearson correlation coefficient between the FAI method and the AHI method is 0.79 (p＜0.0001). The Bland-Altman analysis showed good agreement. ANOVA indicated FAI was statistically significant (F = 18.81,p＜0.001), and there were statistical differences between groups. These results suggest that the proposed distributed force measurement method can provide support surface boundary (triangle ABC) information related to point O.

Background: Flywheel resistance training has gained popularity due to its ability to induce eccentric overload and improve strength and power. This study examined the acute effects of low- (0.025 kg·m2) versus high-inertia (0.10 kg·m2) flywheel deadlifts, matched for force impulse, on the countermovement jump (CMJ) performance, reactive strength index (RSI) during drop jumps (DJs), and rating of perceived exertion (RPE). Methods: Sixteen trained participants (twelve men, and four women) performed three conditions in a randomized, counterbalanced order: low-inertia (LOW), high-inertia (HIGH), and control (CTRL). In the LOW and HIGH conditions, we used force plates to measure and equalize the force impulse in the two conditions (HIGH: 20182 ± 2275 N∙s vs. LOW: 20076 ± 2526 N∙s; p > 0.05), by calculating the number of deadlift repetitions required to achieve it (HIGH: 5 repetitions and LOW: 9.8 ± 0.4 repetitions). The RSI and CMJ performance were measured pre-exercise, immediately post-exercise, and at 3, 6, 9, and 12 min post-exercise. Results: Both the RSI and CMJ performance improved equally after LOW and HIGH flywheel deadlifts compared to baseline and CTRL (p < 0.01). Specifically, the RSI increased from baseline at 3 to 12 min in both conditions (LOW: 12.8 ± 14.9% to 15.4 ± 14.8%, HIGH: 12.1 ± 17.0% to 12.2 ± 11.7%, p < 0.01), while the CMJ increased from 3 to 9 min in LOW (4.3 ± 3.2% to 4.6 ± 4.7%, p < 0.01) and from 6 to 9 min in HIGH (3.8 ± 4.2% to 4.2 ± 4.9%, p < 0.05). No significant differences were observed between LOW and HIGH conditions (p > 0.05), suggesting similar effectiveness of both inertial loads for enhancing performance. The RPE increased similarly after both conditions from baseline to immediately post-conditioning (LOW: from 2.2 ± 1.2 to 5.8 ± 1.4, HIGH: from 1.5 ± 1.0 to 6.1 ± 1.5, p < 0.01) and decreased by the end of the session, although values remained higher than baseline (LOW: 4.1 ± 1.4, p < 0.01, HIGH: 4.5 ± 2.0, p < 0.01). Conclusions: These findings highlight the potential of flywheel deadlift exercise as an effective method to potentiate explosive performance of the lower limbs, regardless of inertia, provided that the total force impulse is equal.

The countermovement jump (CMJ) is an important test in rugby league (RL), and the force plate is the recommended assessment device, as it permits the calculation of several variables that explain jump strategy, alongside jump height. The purpose of this study was to produce normative CMJ data and objective benchmarks for professional RL forwards and backs. Normative data for jump height, modified reactive strength index, and jump momentum are provided for 121 professional RL players (66 forwards and 55 backs) who completed CMJ testing on a portable force plate during preseason training. Standardized T-scores (scaled from 0 to 100) were calculated from the respective positional group mean and standard deviation to create CMJ performance bands that were combined with a qualitative description (ranging from extremely poor to excellent) and a traffic light system to facilitate data interpretation and objective benchmark setting by RL practitioners. The jump height and modified reactive strength index benchmarks were larger for the lighter backs, whereas the jump momentum benchmarks were larger for the heavier forwards. The presented novel approach to compiling and presenting normative data and objective benchmarks may also be applied to other data (i.e., from other tests or devices) and populations.

Traditional gait measurement systems are often limited by factors such as cost, complexity, prolonged setup times, and requirements for specialized training and expertise. Wearable pressure- and motion-sensing insoles have opened new possibilities for accessible gait analysis in real-life conditions. This study evaluated the equivalence of FeetMe insole measurements of gait parameters to those of a laboratory gold standard, optoelectronic motion capture system coupled to force platforms (MoCap/FP). Gait and posture parameters were assessed in 37 healthy adults by FeetMe insoles and by MoCap/FP system simultaneously. Means and variances were compared, and inter-device agreement was assessed for each parameter. Between-device equivalence was demonstrated for all parameters assessed (two one-sided t tests: P  < .001). For static parameters, six of 13 variables presented excellent interclass correlation coefficients (ICCs ≥ 0.90) and three had good ICCs (≥ 0.75 to < 0.90). Moreover, 10 of 11 spatiotemporal parameters showed excellent accuracy (ICCs ≥ 0.90), and three of four kinetic parameters showed moderate-to-good accuracy (ICCs between 0.78 and 0.89). In summary, FeetMe can be considered as a valid gait measurement tool compared to the high precision MoCap/FP system and could be used in clinical practice to assess a wide range of gait and posture parameters, overcoming some limitations of traditional systems.

The objective of this study was to validate PLATES for assessing unipodal balance in the field, for example, to monitor ankle instabilities in athletes or patients. PLATES is a pair of lightweight, connected force platforms that measure only vertical forces. In 14 healthy women, we measured ground reaction forces during Single Leg Balance and Single Leg Landing tests, first under laboratory conditions (with PLATES and with a 6-DOF reference force platform), then during a second test session in the field (with PLATES). We found that for these simple unipodal balance tests, PLATES was reliable in the laboratory and in the field: PLATES gives results comparable with those of a reference force platform with 6-DOF for the key variables in the tests (i.e., Mean Velocity of the Center of Pressure and Time to Stabilization). We conclude that health professionals, physical trainers, and researchers can use PLATES to conduct Single Leg Balance and Single Leg Landing tests in the laboratory and in the field.

Single-leg standing is a conventional balance evaluation method used in medicine. Although the center of mass (COM) displacement should be evaluated to determine balance quality, no practical COM estimation methods have been developed for single-leg standing. This study aimed to estimate the COM displacement in the anteroposterior and mediolateral directions during single-leg standing using practical measurements. We used a force platform and three inertial measurement units to estimate the COM displacement based on rigid-link models in the sagittal and frontal planes. The rigid-link models were composed of the stance leg, upper body, and non-stance leg. Seven healthy male subjects participated in the experiment to validate the estimation accuracy. The COM estimation accuracy was verified by comparison with measurements obtained using an optical motion capture system. The root mean square error of this method was 1.18 mm in the sagittal plane and 1.26 mm in the frontal plane. This technique will contribute to the detailed evaluation of individual balance abilities in the medical and sports fields.