DVS Edition Citation

Tedesco, S, Crowe, C, Ryan, A, Sica, M, Scheurer, S, Clifford, A. M., Brown, K. N. & O`Flynn, B. (2020). Motion sensors-based machine learning approach for the identification of anterior cruciate ligament gait patterns in on-the-field activities in rugby players. Sensors, 20 (11), 3029. Zugriff am 22.01.2021 unter https://doi.org/10.3390/s20113029

APA (7th ed.) Citation

Tedesco, S., Crowe, C., Ryan, A., Sica, M., Scheurer, S., Clifford, A. M., . . . O`Flynn, B. (2020). Motion sensors-based machine learning approach for the identification of anterior cruciate ligament gait patterns in on-the-field activities in rugby players. Sensors, 20(11), 3029.

Chicago Style (17th ed.) Citation

Tedesco, S., C. Crowe, A. Ryan, M. Sica, S. Scheurer, A. M. Clifford, K. N. Brown, and B. O`Flynn. "Motion Sensors-based Machine Learning Approach for the Identification of Anterior Cruciate Ligament Gait Patterns in On-the-field Activities in Rugby Players." Sensors 20, no. 11 (2020): 3029.

MLA (9th ed.) Citation

Tedesco, S., et al. "Motion Sensors-based Machine Learning Approach for the Identification of Anterior Cruciate Ligament Gait Patterns in On-the-field Activities in Rugby Players." Sensors, vol. 20, no. 11, 2020, p. 3029.