This study aimed to explore the kinematic characteristics of males using various foot landing strategies. The participants were fifteen male students from Physical Education College, Huaibei (non-professional runners, who did not have a fixed running landing strategy mode) (mean height = 178.20 cm; mean weight = 67.60 kg; mean age = 19.40 years). In this experiment, the running model of different foot landing strategies (forefoot strike, FFS and rearfoot strike, RFS) were analyzed using two high-speed cameras captured simultaneously at a sampling rate of 100 Hz. According to the results, the runners with better sports performance have shorter contact time, longer flight time, lower duty factor, larger stride angle, faster V COG, greater A COG, and knee and ankle angles which were crucial kinematics factors to enhance the running. Therefore, this study recommends that coaches or researchers can use photography to analyze novice runners who do not have a fixed landing pattern when running with RFS, the characteristics of running style was closely related to the flight times, and running with FFS was closely related to the stride angle.

The primary objective of this study was to determine the effects of vitamin D levels on peripheral pulse wave velocity (pPWV) following acute maximal exercise in healthy young adults. Fifty male healthy adults from National Chung Cheng University participated in the study. Participants were divided into the 25-hydroxyvitamin D (25(OH)D) sufficiency group (n = 28, 25(OH)D ≥ 50 nmol/L) and deficiency group (n = 22, 25(OH)D < 50 nmol/L). The acute maximal exercise was performed using an incremental cycling test to exhaustion. Additionally, the pPWV and blood pressure were obtained at rest and 0, 15, 30, 45, 60 min after acute maximal exercise. The results show that 25(OH)D deficiency group had higher pPWV at post-exercise (5.34 ± 0.71 vs. 4.79 ± 0.81 m/s, p < 0.05), post-exercise 15 min (5.13 ± 0.53 vs. 4.48 ± 0.66 m/s, p < 0.05) and post-exercise 30 min (5.26 ± 0.84 vs. 4.78 ± 0.50 m/s, p < 0.05) than the sufficiency group. Furthermore, there was a significant inverse correlation between 25(OH)D levels and pPWV following acute maximal exercise. Our study demonstrated that low vitamin D status relates to the poor response of pPWV following maximal exercise in healthy young men. Vitamin D deficiency may increase the risk of incident cardiovascular events after acute exhaustive exercise, even in healthy and active adults.

A runner’s duty factor (DF) is defined as the ratio of ground contact time (GCT) to stride time. Fast runners tend to have short GCTs as well as a small DF. In the current method of DF measurement, the runner needs to run on a treadmill and use a high-speed motion capture camera for video recording to examine manually when the runner’s foot touches and leaves the ground. This method is labor costly, slow, and inefficient. To ease the DF measurement, we proposed a novel method by designing a special wearable sensor system, the Tag, can collect the acceleration of runners and compute DFs automatically. The Tag can be installed on the head, waist, or ankle to obtain the acceleration of runners for DF calculation. However, different runners will generate significantly varying characteristics of acceleration as their body shapes and running habits may not be similar. Therefore, a machine learning algorithm was introduced to overcome this issue. The proposed system was evaluated on 27 runners with different running professions, genders, heights, and weights. Results indicate that by using acceleration data measured from the runner’s head and training data based on the runner’s profession category, the proposed design can accurately measure the DF, with a mean absolute error of 5%. To facilitate the development of this domain, this study features the first open-source wearable sensor design for this application. New sensing components and data processing algorithms may be introduced to enhance the performance and open additional possibilities to apply this technology in this area.

This study investigates the effects of speed and incline on spatiotemporal parameters (SPT) and performance-related parameters (PRT) in male and female recreational runners from the perspective of biomechanics. It aims to uncover the underlying biomechanical mechanisms governing human running motion under different conditions. 37 healthy adults (18 males and 19 females) who regularly performed running exercises were recruited as research participants. The speed test included five speeds (8, 9, 10, 11, 12 km/h), each for 1 min with 1-min rest intervals (9 min total). The incline test was at 10 km/h with inclines of 3%, 6%, 9%, and 12%, each for 1 min with 1-min rest intervals (7 min total). Video was captured at 240 fps, with sampling times of 45 s to 1 min. A mixed-design two-way ANOVA assessed the effects of speed on spatiotemporal and technique variables with gender interactions. From a biomechanical standpoint, changes in speed can significantly impact the runners’ stride length and stride frequency. Faster speeds typically require greater muscular force generation and coordination, which in turn can affect the spatiotemporal characteristics of running. The results showed that there were significant differences between genders and speeds in PRT, but no significant differences in SPT. This could be attributed to the varying physiological and biomechanical characteristics between males and females. Males generally possess greater muscle mass and strength, which may allow them to generate more power at higher speeds, resulting in different performance-related parameter values. There were no significant differences between genders and slopes in SPT and PRT. These findings corroborate previous studies and provide a deeper understanding of SPT and PRT characteristics in male and female runners. Future research should explore differences across various populations and include downhill running to understand gender differences in running performance fully. Downhill running involves different biomechanical challenges, such as increased knee flexion and eccentric muscle contractions, which may lead to distinct performance differences between genders. By expanding the scope of research in this way, we can gain a more comprehensive understanding of the biomechanics of human running.

Marathons have recently become popular sporting activities. Due to the competitive nature of marathons, organizers often use automatic timing systems to ensure fairness and impartiality. However, for small- and medium-sized marathon organizers, the existing timing systems are too costly to deploy, so human supervision and timing are still often used. This study proposes an automatic timing system for marathons based on Bluetooth-Low-Energy (BLE) with multiple antennas. Compared to similar studies, this design has higher timing stability. By comparing the characteristics of the received signal strength (RSS) received from multiple antennas, our system can determine when the runner passes the checkpoint. This study uses deep learning algorithms to deal with noisy RSS from multiple antennas. During the evaluation, 20 runners participated in experiments at four locations, demonstrating the scalability of the proposed system. The results showed that the accurate detection of the timing for marathon runners was 96.8%, which could be further increased to 100% if a one-second timing error is acceptable.