Whole body vibration (WBV) has been suggested to improve athletes’ neuromuscular strength and power. This study investigated the effect of single WBV stimulation on volleyball-specific performance. The participants were 20 elite male volleyball players who performed a 1-min warm-up exercise on a vibration platform at a frequency of 30 Hz and peak-to-peak displacement of 2 mm. After the warm-up exercise, the participants performed a blocking agility test (BAT), 10-m sprinting test, agility T-test, and counter movement jump test. We compared the participants’ performance at four time points (Pretest, Post 0, Post 1, and Post 2). The results revealed that the participants’ BAT performance and maximum rate of force development improved significantly 1 min after the vibration stimulation (p < 0.01). The WBV (frequency of 30-Hz, peak-to-peak displacement of 2 mm) intervention significantly improved the volleyball-specific defensive performance and speed strength of the participants. Accordingly, by undergoing WBV as a form of warm-up exercise, the technique and physical fitness of volleyball players can be improved.

The agility T-test and countermovement jump test have long been used to examine the agility of athletes. However, for some sports, newer systems of evaluation are being designed for specific movements. The goal of this study was to design a blocking agility system and apply it to analyzing the efficiency of 6 weeks of plyometric training on volleyball players. A total of 26 male volleyball players in Taiwan participated in the study. The participants were divided into a plyometric training group and a control group. The agility T-test, countermovement jump test, and blocking agility test were used to examine the influence of plyometric training on the blocking agility of volleyball players. A single-factor analysis of covariance was applied to obtain the variables for the two groups. There was no significant difference between the groups on the agility T-test. On the countermovement jump test and blocking agility test, the plyometric training group performed significantly better than the control group. Also, the power values of blocking agility were higher than 90%, which demonstrated very good validity. The results of this study indicate that appropriate plyometric training can increase the rate of force development for vertical jumps and significantly enhance the combined agility of volleyball players in terms of lateral-movement speed and quickness, which enable players to rapidly perform blocking actions.

No abstract

The purpose of this research was to study the effects of a whole-body vibration (WBV) warm-up for improving fencers' performance on variables derived from a lunge reaction test, the 10-meter sprint, and the countermovement jump. We compared fencer performances at four time intervals: (a) preintervention, (b) immediately postintervention, (c) 1-minute postintervention, and (d) 2-minute postintervention. Study participants were 16 male fencers. The vibration frequency was 30 Hz, and its amplitude was two mm. After each WBV session, participants significantly improved their performance on all measures at both one and two minutes after the intervention. Specifically, lunge reaction tests scores improved by 5.50% and 7.34%, respectively, relative to preintevention testing ( p < .01), peak power output improved by 4.94% and 11.52%, respectively ( p < .05), and maximum rate of force development improved by 13.41% and 18.38%, respectively ( p < .01). Acute WBV (frequency = 30 Hz, peak-to-peak amplitude of two mm) induced neuromuscular activation and improved lunge reaction scores, agility, and power.

Background Using wearable inertial sensors to accurately estimate energy expenditure (EE) during an athletic training process is important. Due to the characteristics of inertial sensors, however, the positions in which they are worn can produce signals of different natures. To understand and solve this issue, this study used the heart rate reserve (HRR) as a compensation factor to modify the traditional empirical equation of the accelerometer EE sensor and examine the possibility of improving the estimation of energy expenditure for sensors worn in different positions. Methods Indirect calorimetry was used as the criterion measure (CM) to measure the EE of 90 healthy adults on a treadmill (five speeds: 4.8, 6.4, 8.0, 9.7, and 11.3 km/h). The measurement was simultaneously performed with the ActiGraph GT9X-Link (placed on the wrist and waist) with the Polar H10 Heart Rate Monitor. Results At the same exercise intensity, the EE measurements of the GT9X on the wrist and waist had significant differences from those of the CM (p < 0.05). By using multiple regression analysis—utilizing values from vector magnitudes (VM), body weight (BW) and HRR parameters—accuracy of EE estimation was greatly improved compared to traditional equation. Modified models explained a greater proportion of variance (R2) (wrist: 0.802; waist: 0.805) and demonstrated a good ICC (wrist: 0.863, waist: 0.889) compared to Freedson’s VM3 Combination equation (R2: wrist: 0.384, waist: 0.783; ICC: wrist: 0.073, waist: 0.868). Conclusions The EE estimation equation combining the VM of accelerometer measurements, BW and HRR greatly enhanced the accuracy of EE estimation based on data from accelerometers worn in different positions, particularly from those on the wrist.