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Lightron: A Wearable Sensor System that Provides Light Feedback to Improve Punching Accuracy for Boxing Novices

Published: 08 October 2023 Publication History
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  • Abstract

    This work presents ‘Lightron’, a wearable sensor system designed for boxing training assistance, improving punching accuracy for novices. This system combines accelerometers, stretch sensors, and flex sensors to detect the user’s movements, providing LED light feedback to the user. This adjustable design ensures a tight fit of the device to the body, allowing the sensor to collect accurate arm movement data without impeding training movements. A simple neural network is used to enable real-time motion detection and analysis, which can run on low-cost embedded devices. Contrary to merely using accelerometers on the wrist, Lightron collects motion data from the elbow and shoulder, enhancing the precision of punch accuracy assessment. Primary user studies conducted among boxing amateurs have shown that using Lightron in boxing training increases the performance of amateur players both in single and periodic training sessions, demonstrating its potential utility in the sports training domain.

    References

    [1]
    Daniel Dinu and Julien Louis. 2020. Biomechanical analysis of the cross, hook, and uppercut in junior vs. elite boxers: implications for training and talent identification. Frontiers in Sports and Active Living 2 (2020), 598861.
    [2]
    Daniel Dinu, Benjamin Millot, Jean Slawinski, and Julien Louis. 2020. An examination of the biomechanics of the cross, hook and uppercut between two elite boxing groups. In Proceedings, Vol. 49. MDPI, 61.
    [3]
    Yurie Kondo, Shima Okada, Moemi Saito, Takahide Tanaka, and Kanaru Fumimoto. 2022. Development of Boxing Glove Type Sensation Device for Exercise Induction and Continuation. In 2022 IEEE 11th Global Conference on Consumer Electronics (GCCE). IEEE, 509–510.
    [4]
    Irineu Loturco, Fabio Y Nakamura, Guilherme G Artioli, Ronaldo Kobal, Katia Kitamura, Cesar C Cal Abad, Igor F Cruz, Felipe Romano, Lucas A Pereira, and Emerson Franchini. 2016. Strength and power qualities are highly associated with punching impact in elite amateur boxers. The Journal of Strength & Conditioning Research 30, 1 (2016), 109–116.
    [5]
    Konstantinos Sosopoulos and Michael Tareke Woldu. 2021. IoT smart athletics: Boxing glove sensors implementing machine learning for an integrated training solution.
    [6]
    Abhishek K Tiwari, Ashutosh S Pandey, Mandeep S Dhillon, and Subham Badhyal. 2020. Design and Development of a Device for Performance Analysis and Injury Prevention in Boxing. Journal of Postgraduate Medicine, Education and Research 54, 4 (2020), 231–5.

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    1. Lightron: A Wearable Sensor System that Provides Light Feedback to Improve Punching Accuracy for Boxing Novices

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      cover image ACM Conferences
      UbiComp/ISWC '23 Adjunct: Adjunct Proceedings of the 2023 ACM International Joint Conference on Pervasive and Ubiquitous Computing & the 2023 ACM International Symposium on Wearable Computing
      October 2023
      822 pages
      ISBN:9798400702006
      DOI:10.1145/3594739
      Permission to make digital or hard copies of part or all 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 third-party components of this work must be honored. For all other uses, contact the Owner/Author.

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      New York, NY, United States

      Publication History

      Published: 08 October 2023

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      Author Tags

      1. activity classification
      2. human-computer-interaction
      3. neural networks
      4. user evaluation
      5. wearable computing

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      • Poster
      • Research
      • Refereed limited

      Funding Sources

      • Young Elite Scientists Sponsorship Program
      • Beijing Key Lab of Networked Multimedia
      • Natural Science Foundation of China (NSFC)
      • Tsinghua University Initiative Scientific Research Program

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      UbiComp/ISWC '23

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      Overall Acceptance Rate 764 of 2,912 submissions, 26%

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      UBICOMP '24

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