Affiliation:
1. The Pennsylvania State University, USA
Abstract
In this paper, we introduce SmartDampener, an open-source tennis analytics platform that redefines the traditional understanding of vibration dampeners. Traditional vibration dampeners favored by both amateur and professional tennis players are utilized primarily to diminish vibration transmission and enhance racket stability. However, our platform uniquely merges wireless sensing technologies into a device that resembles a conventional vibration dampener, thereby offering a range of tennis performance metrics including ball speed, impact location, and stroke type. The design of SmartDampener adheres to the familiar form of this accessory, ensuring that (i) it is readily accepted by users and robust under real-play conditions such as ball-hitting, (ii) it has minimal impact on player performance, (iii) it is capable of providing a wide range of analytical insights, and (iv) it is extensible to other sports. Existing computer vision systems for tennis sensing such as Hawk-eye and PlaySight, rely on hardware that costs millions of US dollars to deploy with complex setup procedures and is susceptible to lighting environment. Wearable devices and other tennis sensing accessories, such as Zepp Tennis sensor and TennisEye, using intrusive mounting locations, hinder user experience and impede player performance. In contrast, SmartDampener, a low-cost and compact tennis sensing device, notable for its socially accepted, lightweight and scalable design, seamlessly melds into the form of a vibration dampener. SmartDampener exploits opportunities in SoC and form factor design of conventional dampeners to integrate the sensing units and micro-controllers on a two-layer flexible PCB, that is bent and enclosed inside a dampener case made of 3D printing TPU material, while maintaining the vibration dampening feature and further being enhanced by its extended battery life and the inclusion of wireless communication features. The overall cost is $9.42, with a dimension of 21.4 mm × 27.5 mm × 9.7 mm (W × L × H) and a weight of 6.1 g and 5.8 hours of battery life. In proof of SmartDampener's performance in tennis analytics, we present various tennis analytic applications that exploit the capability of SmartDampener in capturing the correlations across string vibration, and racket motion, including the estimation of ball speed with a median error of 3.59 mph, estimation of ball impact location with accuracy of 3.03 cm, and classification of six tennis strokes with accuracy of 96.75%. Finally, extensive usability studies with 15 tennis players indicate high levels of social acceptance of form factor design for the SmartDampener dampener in comparison with alternative form factors, as well as its capability of sensing and analyzing tennis stroke in an accurate and robust manner. We believe this platform will enable exciting applications in other sports like badminton, fitness tracking, and injury prevention.
Funder
National Science Foundation
Publisher
Association for Computing Machinery (ACM)
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