Accuracy of badminton swing action recognition based on fractional time network

Article type: Research Article

Authors: Shi, Bo^{; *} | Lv, Bin^{; *}

Affiliations: School of Recreation and Community Sport, Capital University of Physical Education and Sports, Beijing, China

Correspondence: [*] Corresponding authors. Bo Shi and Bin Lv, School of Recreation and Community Sport, Capital University of Physical Education and Sports, Beijing, China. E-mail: lvbin678@163.com.

Abstract: To improve the recognition accuracy of badminton players’ swing movements, this study proposes a single inertial sensor based method for badminton swing movement recognition. This article proposes a badminton racket-mounted data gathering system with a single inertial sensor and proposes a real-time motion data flow-based window segmentation technique to capture motion data. On this basis, a two-layer classifier recognition model based on C4.5 Decision Tree (C4.5 T) algorithm and Random Forest (RF) method is constructed to recognize swing technical actions. Using the C4.5 T to identify the swing style of athletes; The RF method is used to recognize the swing technical action. The final experiment showed that the method studied achieved a recognition accuracy of 95.36% for six common swing movements. The proposed model has good application prospects in the recognition of badminton swing movements. However, due to the limitations of the experimental conditions, the recognition effect of this method on more complex swing movements needs to be further verified.

Keywords: Single inertial sensor, the swinging movement of badminton, action recognition, random forest

DOI: 10.3233/JIFS-231409

Journal: Journal of Intelligent & Fuzzy Systems, vol. 45, no. 2, pp. 2409-2418, 2023