Wearable Audio and IMU Based Shot Detection in Racquet Sports

TL;DR

This paper introduces a real-time, fusion-based shot detection system for table tennis using wearable sensors, achieving high accuracy and enabling advanced sports analytics.

Contribution

It presents the first fusion of IMU and audio sensors in wearables for shot detection in table tennis, with a novel synchronization methodology.

Findings

Achieved 95.6% shot detection accuracy.

Demonstrated real-time, computationally inexpensive system.

Laid groundwork for advanced sports analytics in wearables.

Abstract

Wearables like smartwatches which are embedded with sensors and powerful processors, provide a strong platform for development of analytics solutions in sports domain. To analyze players' games, while motion sensor based shot detection has been extensively studied in sports like Tennis, Golf, Baseball; Table Tennis and Badminton are relatively less explored due to possible less intense hand motion during shots. In our paper, we propose a novel, computationally inexpensive and real-time system for shot detection in table tennis, based on fusion of Inertial Measurement Unit (IMU) and audio sensor data embedded in a wrist-worn wearable. The system builds upon our presented methodology for synchronizing IMU and audio sensor input in time using detected shots and achieves 95.6% accuracy. To our knowledge, it is the first fusion-based solution for sports analysis in wearables. Shot detectors for other racquet sports as well as further analytics to provide features like shot classification, rally analysis and recommendations, can easily be built over our proposed solution.