The official material used in table tennis balls was changed from celluloid to plastic, a material free of celluloid, in 2014. The purpose of this study was to understand the differences and similarities in the two types of ball materials by comparing their behavior upon collision with a table. The behavior of the balls before and after collision with a table, at various initial speeds ranging from 15 to 115 km/h, was captured using high-speed cameras. Velocities and spin rates before collision and velocities after collision were computed to calculate the coefficients of restitution and friction. Based on the computed variables, the post-collision trajectories of both balls were calculated by integrating the equation of motion of the ball for simulated service, smash and drive conditions with respect to time. The coefficients of restitution were higher for the plastic balls than the celluloid ones when the initial vertical velocities were higher. The coefficients of friction were higher for plastic balls when the initial horizontal contact point velocities were slower. Because of the differences in the material characteristics, the plastic ball trajectories of services with backspin and drives with great topspin were expected to be different from those of celluloid balls. Since the extent of differences between the two ball types varied depending on the initial conditions, testing at various initial conditions was suggested for comparing and understanding the characteristics of the balls.

Flight time is widely used to calculate jump height because of its simple and inexpensive application. However, this method is known to give different results than the calculation from vertical velocity at takeoff. The purpose of this study is to quantify the effect of postural changes between takeoff and landing on the jump height from flight time. Twenty-seven participants performed three vertical jumps with arm swing. Three-dimensional coordinates of anatomical landmarks and the ground reaction force were analyzed. Two methods of calculating jump height were used: (1) the vertical velocity of the whole-body center of mass (COM_wb) at takeoff and (2) flight time. The jump height from flight time was overestimated by 0.025 m compared to the jump height from the takeoff velocity (p < 0.05) due to the lower COM_wb height at landing by −0.053 m (p < 0.05). The postural changes in foot, shank, and arm segments mainly contributed to decreasing the COM_wb height (−0.025, −0.014, and −0.017 m, respectively). The flight time method is reliable and had low intra-participant variability, but it cannot be recommended for a vertical jump when comparing with others (such as at tryouts) because of the potential “cheating” effect of differences in landing posture.

Understanding multi-agent cooperative behavior is challenging in various scientific and engineering domains. In some cases, such as team sports, many cooperative behaviors can be visually categorized and labeled manually by experts. However, these actions which are manually categorized with the same label based on its function have low spatiotemporal similarity. In other words, it is difficult to find similar and different structures of the motions with the same and different labels, respectively. Here, we propose an automatic recognition system for strategic cooperative plays, which are the minimal, basic, and diverse plays in a ball game. Using player’s moving distance, geometric information, and distances among players, the proposed method accurately discriminated not only the cooperative plays in a primary area, i.e., near the ball, but also those distant from a primary area. We also propose a method to classify more detailed types of cooperative plays in various situations. The proposed framework, which sheds light on inconspicuous players to play important roles, could have a potential to detect well-defined and labeled cooperative behaviors.

Typical anticipatory postural adjustments (APAs) in forward gait or step initiation tasks to prepare for possible disturbances caused by prime voluntary movements and to accelerate the body forward have been previously reported. However, it is not clear how wide the variations in step directions are differentiated and controlled in non-forward step initiation tasks during the APA phase. The main goal of this study is to explain the directional control mechanisms by investigating the APA of step initiation tasks in forward, diagonal, lateral, and posterior directions. The center of pressure (COP) trajectories and related muscle (soleus, tibialis anterior, and gluteus medius of both lower limbs) activities during the APA of step initiation tasks in nine different directions were analyzed in six healthy young males. Posterior shifts of COP during APA decreased as the direction became more lateral (0° to 90°). For posterior step initiations, COP moved anteriorly from the initial position to accelerate the center of mass of the whole body (COM) backward. Lateral shifts of COP toward the stepping foot during APA decreased as the stepping direction became more lateral (from 0° to 45° and from 180° to 113°) while it plateaued to about zero in the direction from 45° to 113°. Both anteroposterior and lateral displacements of COP in APA were nonlinearly modulated to each direction, but they were linearly related to the anteroposterior and mediolateral component of the velocities of COM at the take-off of the stance foot. Thus, the scaling of APA, reflected in the anteroposterior and lateral displacements of COP and the temporal sequence of selected muscle activities, was based on the anteroposterior and mediolateral components of the take-off velocity of COM that ultimately controls the direction of steps.

This study experimentally investigated the factors affecting the time a table tennis ball with topspin takes to reach the opponent. Six skilled young players and one coach performed topspin forehand strokes under the observation of three high-speed cameras. As the distribution of the participants’ measurements was uneven, additional data were collected using a launching machine that could control the ball speed and spin. To verify the effect of the spin rate on speed decay by drag, the translational speed was measured at 0.15 s after passing the baseline (23 m/s); the balls with topspin ≥110 rps, close to participants’ average (117 ± 29 rps) were 1.4 m/s faster than those with topspin ≤80 rps. The horizontal ball speed changed in the range of −3.1 to 2.6 m/s owing to table bounce. At topspins ≥110 rps the ball reached a point 1 m past the end line (estimated receiving position) 27 ± 5 ms faster than at topspins ≤80 rps, for the same initial speed. The relationship between spin rate and travel time was non-linear with boundaries at 80 and 110 rps. Therefore, maintaining a spin rate of ≥ 110 rps along with a high initial speed is an effective strategy for reducing the opponent’s preparation time.

Effective analysis of skills requires high-quality, multi-modal datasets, especially in the field of artificial intelligence. However, creating such datasets for extreme sports, such as alpine skiing, can be challenging due to environmental constraints. Optical and wearable sensors may not perform optimally under diverse lighting, weather, and terrain conditions. To address these challenges, we present a comprehensive skiing/snowboarding dataset using a professional motor-based simulator. Using the realistic simulator, it is easy to obtain different types of data with a small domain gap between real-world data. Common data for skill analysis are collected, including camera images, 3D body pose, sole pressure, and leg electromyography, from athletes of different levels. Another key aspect is the comparison of cross-modal baselines, highlighting the versatility of the data across modalities. In addition, a real-world pilot test is conducted to assess the practical applicability and data robustness.