Digital Technology Empowers the Optimization of Martial Arts Teaching and Training: A Study on Movement Correction and Training Effect Evaluation Based on Motion Capture Technology
Main Article Content
Abstract
Traditional martial arts teaching lacks refined diagnosis and quantitative intervention for motor skills, limiting objective movement evaluation and personalized training. This study proposes a quantitative assessment and correction framework for martial arts movements based on inertial motion capture technology, where wireless sensing and multimodal motion perception provide reliable support for high-precision human movement analysis. A data acquisition system employing 17 IMU sensors is established, and a multidimensional evaluation model incorporating posture stability, joint angle, trajectory straightness, and completion rate is developed for typical movements including the bow stance punch and whirlwind kick. Through real-time visual feedback and an 8-week controlled teaching experiment, the proposed system demonstrates effective movement correction and training optimization. Experimental results show that pelvic sway during the bow stance punch is reduced by 35.0%, while the body rotation completion rate during the whirlwind kick reaches 95.6%, indicating significant improvements in movement accuracy and objective training evaluation. The proposed framework provides an effective digital solution for intelligent motion analysis and electromagnetic sensing-enabled sports training applications.
Downloads
Article Details
This work is licensed under a Creative Commons Attribution 4.0 International License.
Authors who publish with this journal agree to the following terms:
- Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons Attribution License that allows others to share the work with an acknowledgement of the work's authorship and initial publication in this journal.
- Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgement of its initial publication in this journal.
- Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work (See The Effect of Open Access).
References
M. S. Nazeer, R. Imran, M. Amin, et al., “An intelligent algorithm for evaluating martial arts teaching skills based on complex picture fuzzy Dombi aggregation operator,” Journal of Innovative Research in Mathematical and Computa tional Sciences, vol. 3, no. 2, pp. 44-70, 2024, doi: 10.62270/jirmcs.v3i2.38.
Huang Hai, Chen Jun, and Wang Dongliang, “Research on the Reform of Wushu Teaching Model in Universities from the Perspective of Deep Learning,” Wushu Research, vol. 10, no. 4, pp. 61-63+114, 2025.
T. My P, “Introducing traditional vietnamese martial arts into teaching in universities,” Cadernos de Educação Tecnologia e Sociedade, vol. 18, no. 4, pp. 1615-1627., 2025.
Y. Jia, M. Theeboom, Z. Dong, et al., “Teaching Chinese martial arts to youngsters: Approaches and experiences of wushu coaches in Europe: English,” Archives of Budo, vol. 18, no. 1, pp. 353-361, 2022.
G. Zhou and Z. Xie, “Smart sports immersive martial arts teaching mode analysis,” IC-ITECHS, vol. 5, no. 1, pp. 458-464, 2024, doi: 10.32664/ic-itechs.v5i1.1616.
M. Santos, J. Martin, E. Mhico Sigua, et al., “Effects of Online Teaching on Perceived Physical Competence and Cultural Appreciation of the Philippine Martial Arts “Arnis”,” Ido Movement for Culture. Journal of Martial Arts Anthropology, vol. 22, no. 5, pp. 48-54. Yan Shifang, Wu Shanghang, Cao Chuanbao. Research on Optimizing the Teaching Quality of Wushu through the, 2022.
NSCA-AP System, “Wushu Research,” 2025; 10(11): 85-87+148.
Wu Shen and Yao Qiong, “A Study on the Path of Upholding the Orthodox and Innovating Wushu Teaching in Colleges and Universities in the New Era,” Wushu Research, vol. 10, no. 7, pp. 89-91. Jia Q, Wang Y, Gu P. Study on the Integration of Chinese Martial Arts Bing Dao in the Online+ Offline Teaching Model, 2025.
at College Sports Education, “Journal of Electrical Systems,” 2024; 20(2): 725-730, doi: 10.52783/jes.1226.
M. C. Wibowo, S. Nugroho, and A. Wibowo, “The use of motion capture technology in 3D animation,” International Journal of Computing and Digital Systems, vol. 15, no. 1, pp. 975-987, 2024, doi: 10.12785/ijcds//150169.
U. Lugrís, M. Pérez-Soto, F. Michaud, et al., “Human motion capture, reconstruction, and musculoskeletal analysis in real time,” Multibody System Dynamics, vol. 60, no. 1, pp. 3-25, 2024, doi: 10.1007/s11044-023-09938-0.
B. Van Hooren, N. Pecasse, K. Meijer, et al., “The accuracy of markerless motion capture combined with computer vision techniques for measuring running kinematics,” Scandinavian Journal of Medicine & Science in Sports, vol. 33, no. 6, pp. 966-978, 2023, doi: 10.1111/sms.14319.
G. Zhou and Z. Xie, “Smart sports immersive martial arts teaching mode analysis,” IC-ITECHS, vol. 5, no. 1, pp. 458-464, 2024, doi: 10.32664/ic-itechs.v5i1.1616.
S. Qiu, H. Zhao, N. Jiang, et al., “Sensor network oriented human motion capture via wearable intelligent system,” International Journal of Intelligent Systems, vol. 37, no. 2, pp. 1646-1673, 2022, doi: 10.1002/int.22689.
X. Yi, Y. Zhou, M. Habermann, et al., “Egolocate: Real-time motion capture, localization, and mapping with sparse bodymounted sensors,” ACM Transactions on Graphics (TOG), vol. 42, no. 4, pp. 1-17, 2023, doi: 10.1145/3592099.