Edge computing-based big data privacy preservation in motion trajectory prediction for martial arts training

[1] Liu, J., Huang, G., Hyyppä, J., Li, J., Gong, X., & Jiang, X. (2023). A survey on location and motion tracking technologies, methodologies and applications in precision sports. Expert Systems with Applications, 120492. Search in Google Scholar

[2] Claudino, J. G., Capanema, D. D. O., de Souza, T. V., Serrão, J. C., Machado Pereira, A. C., & Nassis, G. P. (2019). Current approaches to the use of artificial intelligence for injury risk assessment and performance prediction in team sports: a systematic review. Sports medicine-open, 5, 1-12. Search in Google Scholar

[3] de Moraes Fernandes, F., Wichi, R. B., da Silva, V. F., Ladeira, A. P. X., & Ervilha, U. F. (2017). Biomechanical methods applied in martial arts studies. Journal of Morphological Sciences, 28(3), 0-0. Search in Google Scholar

[4] Andreucci, C. A. (2020). Gyms and Martial Arts School after COVID-19: When to come back to train?. Advances in Physical Education, 10(2), 114-120. Search in Google Scholar

[5] Chow, T. H., Lee, B. Y., Ang, A. B. F., Cheung, V. Y. K., Ho, M. M. C., & Takemura, S. (2018). The effect of Chinese martial arts Tai Chi Chuan on prevention of osteoporosis: A systematic review. Journal of orthopaedic translation, 12, 74-84. Search in Google Scholar

[6] Maltsev, G. S., Zekrin, F. K., & Zekrin, A. F. (2020). Modern trends in martial arts training process planning. Teoriya i praktika fiz. kultury, (3), 12-14. Search in Google Scholar

[7] Sandford, G. T., & Gill, P. R. (2019). Martial arts masters identify the essential components of training. Physical Education and Sport Pedagogy, 24(1), 31-42. Search in Google Scholar

[8] Plush, M. G., Guppy, S. N., Nosaka, K., & Barley, O. R. (2022). Exploring the physical and physiological characteristics relevant to mixed martial arts. Strength & Conditioning Journal, 44(2), 52-60. Search in Google Scholar

[9] Kovalchik, S. A. (2023). Player tracking data in sports. Annual Review of Statistics and Its Application, 10, 677-697. Search in Google Scholar

[10] Lei, Q., Du, J. X., Zhang, H. B., Ye, S., & Chen, D. S. (2019). A survey of vision-based human action evaluation methods. Sensors, 19(19), 4129. Search in Google Scholar

[11] Yong Li, Xiao Song, Yuchun Tu & Ming Liu.(2024).GAPBAS: Genetic algorithm-based privacy budget allocation strategy in differential privacy K-means clustering algorithm.Computers & Security103697-. Search in Google Scholar

[12] Zihao Shen,Yuyang Zhang,Hui Wang,Peiqian Liu,Kun Liu & Yanmei Shen.(2024).BiGRU-DP: Improved differential privacy protection method for trajectory data publishing.Expert Systems With Applications(PB),124264-. Search in Google Scholar

[13] YanYan, Pengbin Yan, Adnan Mahmood, FeiXu & Quan Z. Sheng. (2024). Towards achieving geo‐ indistinguishability for 3D GPS location: A 3D Laplace mechanism approach.Concurrency and Computation: Practice and Experience(14), Search in Google Scholar

[14] Liu Ying,Liu Wanke,Zhang Xiaohong,Liang Yantao,Tao Xianlu & Ma Liye.(2024).An improved GNSS ambiguity best integer equivariant estimation method with Laplacian distribution for urban low-cost RTK positioning.Satellite Navigation(1), Search in Google Scholar

[15] Waseem Waheed, Guang Deng & Bo Liu.(2020).Discrete Laplacian Operator and Its Applications in Signal Processing.IEEE Access89692-89707. Search in Google Scholar