Using Smart Sensors to Monitor Physical Activity and Technical–Tactical Actions in Junior Tennis Players

Abstract

The use of smart devices to obtain real-time data has notably increased in the context of training. These technological tools provide data which monitor the external load and technical–tactical actions related to psychological and physical health in junior tennis players. The purpose of this paper is to monitor technical–tactical actions and physical activity during a current tennis competition in the Green stage using a Zepp Tennis Smart Sensor 2. The participants were 20 junior tennis players (under 10 years of age), with an average age of 9.46 years. The total number of strokes (n= 21,477) during 75 matches was analyzed. The study variables were the following aspects: (a) number of strokes, (b) ball impact in the sweet spot; (c) racket speed; (d) ball spin; (e) calories burned; and (f) match time. The current system of competition, based on knockout, does not meet the World Health Organization’s recommendations for daily physical activity time. Players mainly used flat forehands with a lack of variability in technical–tactical actions which did not meet the current learning opportunity criteria of comprehensive methodologies. The competition system in under-11 tennis should be adapted to the players’ characteristics by improving the variability and quantity of practice.

Remote Evaluation System of Tennis Batting Action Standard Based on Acceleration Sensor

“…Moreover, compared with previous methods, our method based on a bracelet embedded with an acceleration sensor is cost-effective, more energy-efficient, not influenced by the lighting environment, and easier to set up. Compared with five related studies that used systems such as IMU gyroscopes [15], Zepp Tennis Smart Sensor 2 [16], Brzostowski K.'s system [17], TenniVis [19], and Tac-Simur [20], our system performance is more stable and has stronger practical applicability. Moreover, our system strictly protects the user's privacy when uploading the user's data remotely.…”

“…We performed an analysis of evaluation results and system performance test that included signal smoothing performance and real-time response in Section 3. In the process of real-time response test of system performance, we compared with five related studies that used the system such as IMU gyroscopes [15], Zepp Tennis Smart Sensor 2 [16], Brzostowski K.'s system [17], TenniVis [19], and Tac-Simur [20]. e results demonstrated the superiority of our system.…”

“…IMU [15] can detect meaningful differences in angular velocity during tennis groundstrokes to evaluate the tennis batting action standard; however, its measure was not standard. A research used Zepp Tennis Smart Sensor 2 [16] to monitor technical-tactical actions and physical activity during a current tennis competition in the green stage; however, it also had a larger latency. A methodology based on data fusion for sports training [17] has been presented, and a system was developed to assess the performance of a tennis player so as to improve their strokes technique and overall performance (i.e., we call it Brzostowski K.'s system to compare with our system), but it required a large amount of data to train the model, and data collection was difficult.…”

Wound Healing: From Passive to Smart Dressings

“…[ 224,225 ] Several sportswear producing companies have explored new technologies to utilize a dressing's intelligence to monitor athletics’ abilities on the court. [ 226 ] Monitoring athletes performance during the competition or training has been difficult in the past, but thanks to the embedded microsensors in sportswear, these smart clothing can monitor the most important physiological parameters for athletes including breathing patterns, heartbeat, blood pressure, the composition of body fluids (sweat, urine, etc.) [ 227 ] For instance, to monitor the heartbeat of athletes during training, as an important parameter for evaluating athlete's physical readiness, Perego et al.…”

Análisis de las variables técnico-tácticas relacionas con el último golpe del punto en el tenis de alto rendimiento

“…La calidad del dato se comprobó a través de los coeficientes de Tau de Kendall, Pearson y Spearman y los niveles aptos de fiabilidad intra e inter observador (Anguera, 2003) mediante el coeficiente Kappa de Cohen (Cohen, 1968). Durante la tercera fase se llevó a cabo el visionado de los partidos mediante el programa de análisis de vídeo Kinovea 8.15 para Windows, utilizándose la herramienta "perspective grid" para delimitar las áreas de bote y golpeo (Giménez-Egido et al, 2020). Así mismo se registró el dato de manera simultánea en una hoja de observación diseñada para tal fin con el software Microsoft Excel versión 2010 para Windows.…”