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SmartDampener: An Open Source Platform for Sport Analytics in Tennis

Published: 09 September 2024 Publication History

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.

Supplemental Material

MP4 File - SmartDampener Demo Video
Video demonstration of SmartDampener tennis stroke analytics.

References

[1]
2007. Nike+iPod, Apple. https://www.apple.com/ca/ipod/nike/run.html.
[2]
2017. ICM20948 datasheet. https://invensense.tdk.com/wp-content/uploads/2016/06/DS-000189-ICM-20948-v1.3.pdf.
[3]
2018. Tennis 101: The 6 Basic Strokes Explained Step-by-Step - Pat Cash Tennis. https://www.patcash.co.uk/2018/03/the-6-basic-strokes-in-tennis-explained/.
[4]
2019. Tennis racket specifications explained. https://tennishead.net/tennis-racket-specifications-explained/.
[5]
2020. Lighter or Heavier - Which Tennis Racquet You Should Choose? https://www.racquets4u.com/blog/post/lighter-or-heavier-which-tennis-racquet-to-choose/https://www.racquets4u.com/blog/post/lighter-or-heavier-which-tennis-racquet-to-choose/.
[6]
2020. Multilayer piezoelectric actuators. https://content.kemet.com/datasheets/KEM_P0101_AE.pdf.
[7]
2020. RTP Shocksorb Dampener. https://www.rtptennis.com/.
[8]
2020. Vibrating Mini Motor Disc. https://www.adafrait.com/product/1201?gad_source=1&gclid=Cj0KCQjwlZixBhCoARIsAIC745DCKALhxlOpW_cm2HDl1NPaDuR1prupL9dGRl9918N3xWbVwRpEzfoaAu0qEALw_wcB.
[9]
2021. AirTag Teardown: Yeah, This Tracks. https://www.ifixit.com/News/50145/airtag-teardown-part-one-yeah-this-tracks.
[10]
2022. NRF52832. https://www.nordicsemi.com/products/nrf52832.
[11]
2022. Tennis Racquet Weight, Balance Swingweight Explained. https://tenniscompanion.org/tennis-racquet-weight-and-balance/.
[12]
2023. AccuTennis. https://accutennis.com/.
[13]
2023. Babolat. https://www.babolat.com/us.
[14]
2023. Courtmatics. http://www.courtmatics.com/product.html.
[15]
2023. Demo. https://streamable.com/co98oj.
[16]
2023. Hawk eye innovations. https://www.hawkeyeinnovations.com/.
[17]
2023. Head. https://www.head.com/en_US/sensor.
[18]
2023. The Importance of Proper Tennis Form / Technique. https://www.tennismindgame.com/tennis-form.html.
[19]
2023. PlaySight. https://playsight.com/.
[20]
2023. Qlipp. https://www.eedesignit.com/the-tennis-sensor-thats-making-a-racket/.
[21]
2023. Sony Smart Tennis Sensor Review. http://tennis-technology.com/sony-smart-tennis-sensor/.
[22]
2023. Spivo Reviews. https://spivotennis.com/en-us/pages/reviews.
[23]
2023. SwingVision. https://swing.tennis/.
[24]
2023. Wearable Devices in Sports Market Analysis. https://www.mordorintelligence.com/industry-reports/wearable-devices-in- sports-market.
[25]
2023. Zepp. https://sensor-support.zepp.com/en/.
[26]
Adafruit. 2021. Bluefruit nRF52 Feather Learning Guide. https://learn.adafruit.com/bluefruit-nrf52-feather-learning-guide.
[27]
Adafruit. 2021. ICM20X. https://github.com/adafruit/Adafruit_ICM20X.
[28]
Akash Anand et al. 2017. Wearable motion sensor based analysis of swing sports. In IEEE ICMLA.
[29]
Android Developer 2021. Profile battery usage with Batterystats and Battery Historian. https://developer.android.com/topic/performance/power/setup-battery-historian.
[30]
Jacob S Arlotti et al. 2022. Benefits of IMU-based Wearables in Sports Medicine: Narrative Review. IJKSS (2022).
[31]
Junjie Bai et al. 2019. ONNX: Open Neural Network Exchange. https://github.com/onnx/onnx.
[32]
G. Bradski. 2000. The OpenCV Library. Dr. Dobb's Journal of Software Tools (2000).
[33]
Howard Brody. 1979. Physics of the tennis racket. American Journal of physics (1979).
[34]
Howard Brody. 1981. Physics of the tennis racket II: The"sweet spot". American Journal of Physics (1981).
[35]
Brzostowski et al. 2018. Data fusion in ubiquitous sports training: Methodology and application. Wireless Communications and Mobile Computing (2018).
[36]
Lars Büthe et al. 2016. A wearable sensing system for timing analysis in tennis. In IEEE BSN.
[37]
Jordan Calandre et al. 2021. Extraction and analysis of 3D kinematic parameters of Table Tennis ball from a single camera. In ICPR.
[38]
Olivia Cant et al. 2020. Validation of ball spin estimates in tennis from multi-camera tracking data. Journal of Sports Sciences (2020).
[39]
Ciarán Ó Conaire et al. 2009. Tennissense: A platform for extracting semantic information from multi-camera tennis data. In DSP.
[40]
Rod Cross. 1997. The dead spot of a tennis racket. American Journal of Physics (1997).
[41]
Yu Ding et al. 2020. Application of Internet of Things and virtual reality technology in college physical education. IEEE Access (2020).
[42]
José María Giménez-Egido et al. 2020. Using smart sensors to monitor physical activity and technical-tactical actions in junior tennis players. International journal of environmental research and public health (2020).
[43]
Mahanth Gowda et al. 2017. Bringing {IoT} to sports analytics. In NSDI.
[44]
Yu-Chuan Huang et al. 2019. Tracknet: A deep learning network for tracking high-speed and tiny objects in sports applications. In IEEE AVSS.
[45]
Alvin Jacob et al. 2016. Implementation of IMU sensor for elbow movement measurement of badminton players. In IEEE ROMA.
[46]
C D Johnson and M P McHugh. 2006. Performance demands of professional male tennis players. British Journal of Sports Medicine 40, 8 (2006), 696--699. https://doi.org/10.1136/bjsm.2005.021253 arXiv:https://bjsm.bmj.com/content/40/8/696.full.pdf
[47]
Aida Kamišalić et al. 2018. Sensors and functionalities of non-invasive wrist-wearable devices: A review. Sensors (2018).
[48]
Marko Kos et al. 2016. Tennis stroke detection and classification using miniature wearable IMU device. In IWSSIP.
[49]
Johannes Landlinger et al. 2011. Differences in ball speed and accuracy of tennis groundstrokes between elite and highperformance players. European Journal of Sport Science (10 2011). https://doi.org/10.1080/17461391.2011.566363
[50]
SuKyoung Lee et al. 2017. Motion anlaysis in lower extremity joints during ski carving turns using wearble inertial sensors and plantar pressure sensors. In IEEE SMC.
[51]
Huimin Liu et al. 2020. Virtual reality racket sports: Virtual drills for exercise and training. In IEEE ISMAR.
[52]
Stuart A McErlain-Naylor et al. 2020. Effect of racket-shuttlecock impact location on shot outcome for badminton smashes by elite players. Journal of sports sciences (2020).
[53]
Miha Mlakar, et al. 2017. Analyzing tennis game through sensor data with machine learning and multi-objective optimization. In UbiComp.
[54]
Vinyes Mora et al. 2017. Deep learning for domain-specific action recognition in tennis. In CVPR workshops.
[55]
Borja Muniz-Pardos et al. 2018. Integration of wearable sensors into the evaluation of running economy and foot mechanics in elite runners. Current sports medicine reports (2018).
[56]
Ellen O'Reilly et al. 2001. 'They Ought to Enjoy Physical Activity, You Know?': Struggling with Fun in Physical Education. Sport, education and society (2001).
[57]
NEIL Owens et al. 2003. Hawk-eye tennis system. In 2003 international conference on visual information engineering VIE 2003.
[58]
Adam Paszke et al. 2019. PyTorch: An Imperative Style, High-Performance Deep Learning Library. In NeurIPS.
[59]
F. Pedregosa et al. 2011. Scikit-learn: Machine Learning in Python. Journal of Machine Learning Research 12 (2011), 2825--2830.
[60]
Weiping Pei et al. 2017. An embedded 6-axis sensor based recognition for tennis stroke. In IEEE ICCE.
[61]
Qazi et al. 2015. Automated ball tracking in tennis videos. In ICIIP.
[62]
Reno et al. 2018. Convolutional neural networks based ball detection in tennis games. In CVPR workshops.
[63]
Manish Sharma et al. 2017. Wearable motion sensor based phasic analysis of tennis serve for performance feedback. In IEEE ICASSP.
[64]
Yu-Tza Tsai et al. 2021. Unity game engine: Interactive software design using digital glove for virtual reality baseball pitch training. Microsystem Technologies (2021).
[65]
Guido Van Rossum and Fred L. Drake. 2009. Python 3 Reference Manual. CreateSpace, Scotts Valley, CA.
[66]
Zhelong Wang, Ming Guo, and Cong Zhao. 2016. Badminton stroke recognition based on body sensor networks. IEEE Transactions on Human-Machine Systems (2016).
[67]
Xinyu Wei et al. 2013. Predicting shot locations in tennis using spatiotemporal data. In IEEE DICTA.
[68]
Xinyu Wei et al. 2013. Sweet-spot: Using spatiotemporal data to discover and predict shots in tennis. In 7th Annual MIT Sloan Sports Analytics Conference, Boston, MA.
[69]
Graham J. Weir and Peter Norman McGavin. 2008. The coefficient of restitution for the idealized impact of a spherical, nano-scale particle on a rigid plane. Proceedings of the Royal Society A: Mathematical, Physical and Engineering Sciences 464 (2008), 1295 - 1307. https://api.semanticscholar.org/CorpusID:122562612
[70]
David Whiteside et al. 2017. Monitoring hitting load in tennis using inertial sensors and machine learning. IJSPP (2017).
[71]
Wikipedia contributors. 2024. Momentum --- Wikipedia, The Free Encyclopedia. https://en.wikipedia.org/w/index.php?title=Momentum&oldid=1197280395.
[72]
Fei Yan et al. 2005. A tennis ball tracking algorithm for automatic annotation of tennis match. In British machine vision conference.
[73]
Disheng Yang et al. 2017. TennisMaster: An IMU-based online serve performance evaluation system. In ACM AH.
[74]
Hongyang Zhao et al. 2019. TennisEye: tennis ball speed estimation using a racket-mounted motion sensor. In IPSN.
[75]
Hao Zhou et al. 2023. One Ring to Rule Them All: An Open Source Smartring Platform for Finger Motion Analytics and Healthcare Applications. IEEE/ACM IoTDI (2023).

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      cover image Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies
      Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies  Volume 8, Issue 3
      August 2024
      1782 pages
      EISSN:2474-9567
      DOI:10.1145/3695755
      Issue’s Table of Contents
      Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

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      Publication History

      Published: 09 September 2024
      Published in IMWUT Volume 8, Issue 3

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      Author Tags

      1. IoT
      2. Sport Analytics
      3. Wearable Computing
      4. Wireless Sensing

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