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Punch Force Classification using K Means and a Data Logging System

Authors

  • Lilik Anifah Department of Electrical Engineering, Faculty of Engineering, Universitas Negeri Surabaya, Indonesia
  • Nurhayati Department of Electrical Engineering, Faculty of Engineering, Universitas Negeri Surabaya, Indonesia
  • Puput Wanarti Rusimamto Department of Electrical Engineering, Faculty of Engineering, Universitas Negeri Surabaya, Indonesia
  • Muhamad Syarifuddien Zuhrie Department of Electrical Engineering, Faculty of Engineering, Universitas Negeri Surabaya, Indonesia
  • Haryanto Department of Electrical Engineering, Faculty of Engineering, Universitas Negeri Surabaya, Indonesia
Volume: 15 | Issue: 1 | Pages: 19337-19342 | February 2025 | https://doi.org/10.48084/etasr.9321

Abstract

Much research has been conducted worldwide on the recognition and monitoring of punches in martial art sports during the training process. The performance of the punching movements can be accurately analyzed based on the collected data. The current study aims to classify the punches on a punching bag using K Means based on a data logging system. Its stages are hardware design, hardware implementation, hardware testing, learning, and testing. The FSR 402 sensor was used to measure the punching force. GY6500 MPU6500 was also utilized to identify and measure the reaction force of these punches. The data were collected utilizing K Means and were subsequently tested. The results revealed that the system exhibited good performance, proven by its accuracy of 93.6%, precision of 0.933, recall of 0.934, and F1 score of 0.934. Based on these results, it seems that the classification of right and left punch forces can be efficiently carried out. This system can help users analyze the punching bag training process, and thus improve their performance.

Keywords:

k means, punching, data logger, classification

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How to Cite

[1]
Anifah, L., Nurhayati, ., Rusimamto, P.W., Zuhrie, M.S. and Haryanto, . 2025. Punch Force Classification using K Means and a Data Logging System. Engineering, Technology & Applied Science Research. 15, 1 (Feb. 2025), 19337–19342. DOI:https://doi.org/10.48084/etasr.9321.

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