Backpacks are commonly worn by many people for multiple purposes. This study investigated the effects of habitual wearing of backpacks on lower limb kinematics and kinetics. Fourteen participants were recruited for analysis. All participants performed four randomly assigned scenarios, including running and walking at speeds of 3.5 and 1.5m/s, respectively, with and without load carriage. The motion analysis system and force plate were used to investigate the lower limb kinematics and kinetics. A paired sample t-test was performed for statistical measurement with a significance level of α.05. The results indicated that active force, breaking force, impact peak, loading rate, active peak, maximum braking, hip flexion, and hip range of motion were substantially higher under load carriage conditions than under walking condition, however, time to peak was lower. Conversely, during load carriage running, active force, braking impulse, time to peak, ankle plantarflexion, and ankle range of motion were all higher than those during running. Carrying a backpack weighing 10 of the body weight induced different foot strike patterns at both speeds; during load carriage walking, the hip tended to flex more; whereas, during load carriage running, the ankle tended to flex more. In conclusion, human body seems to adopt different gait strategies during load carriage walking and running. That is, the hip strategy is used during walking, while the ankle strategy is used during running.

Introduction: In recent years, E-sports has emerged as a global competitive sports discipline. However, research in the field of exercise science regarding this burgeoning area remains relatively limited. Within this context, an in-depth exploration of E-sports from an exercise science perspective not only aids in optimizing players’ training and performance but also contributes important theoretical and practical value to the advancement of exercise science. This study investigated the physiological changes in E-sports athletes by measuring Heart Rate Variability (HRV).Methods: A total of 40 male college students (mean age 21.2 ± 2.4 years, mean height 171.8 ± 7.9 cm, and mean weight 70.2 ± 11.5 kg) were recruited. Heart rate data were collected before, during, and after gaming using SCOSCHE heart rate armbands. HRV Analysis 1.1 software was employed to convert heart rate changes into HRV parameters. First, a normality test was conducted to determine the data distribution. Since the data did not meet the assumption of normality, the Friedman test was used to compare pre-, during-, and post-gaming heart rate data. Post hoc comparisons were performed using the Wilcoxon signed-rank test with Bonferroni correction. The significance level was set at α = 0.05.Results: The results showed that E-sports gaming significantly affected autonomic nervous system activity. Specifically, pre-game mean heart rate (Mean HR) and low-frequency (LF) power were significantly lower than those measured during and after gaming (p < 0.05), while pre-game mean RR interval (Mean RR) was significantly longer (p < 0.05). Furthermore, pre-game HRV indices [e.g., Standard Deviation of NN intervals (SDNN), Root Mean Square of Successive Differences (RMSSD), Number of NN intervals differing by more than 50 ms (NN50), Percentage of NN50 (pNN50)] and high-frequency (HF) power and LF/HF Ratio were significantly higher than those recorded during and after gaming (p < 0.05).Conclusion: E-sports gaming imposes stress and fatigue on HRV-related parameters, heightening sympathetic activity and suppressing parasympathetic function. Although certain indicators exhibited a trend toward recovery during the post-gaming rest period, complete recovery appears to require a longer duration. These findings confirm the utility of HRV as an essential tool for monitoring athletes’ physiological status and underscore the need for effective recovery strategies to mitigate the long-term impact of gaming-related stress.

In-group heterogeneity is often neglected during investigations of motor development patterns in children. Moreover, the variation in motor development patterns over time has seldom been examined. In this work, 1884 three-year-old preschoolers were selected from a panel study conducted in Taiwan called the National Longitudinal Study of Child Development and Care. A confirmatory factor analysis was applied to analyze the construct validity of the assessments of motor development used for these children. A latent profile analysis and latent transition analysis (LTA) were sequentially applied to clarify their motor development patterns at the ages of three and four years and their transitions between these two ages. The following findings were obtained: (1) The motor development assessment had good validity. (2) Considerable heterogeneity regarding motor development in preschoolers was observed, in which four and three subgroups displaying distinct levels of mastery with respect to their gross and fine motor skills were identified at the ages of three and four years, respectively. (3) From age three to age four, a large proportion of the preschoolers exhibited improvements or retentions in both gross and fine motor skills, whereas some of the preschoolers were classified into subgroups displaying “gross motor retention and fine motor progression,” “gross motor progression and fine motor retention,” “gross motor retention and fine motor regression,” and “gross motor regression and fine motor progression.” Few preschoolers exhibited “general motor regression.” The present results suggest that there were considerable heterogeneous groups in the motor development in preschoolers in the middle of early childhood, and this phenomenon has rarely been addressed in former studies. The LTA results implied that effective interventions should be given sequentially to preschoolers in subgroups whose motor development presented regression and retention tendencies.