Bogaert, S, Davis, J, Van Rossom, S. & Vanwanseele, B. (2022). Impact of gender and feature set on machine-learning-based prediction of lower-limb overuse injuries using a single trunk-mounted accelerometer. Sensors, 22 (8), 2860. Zugriff am 02.05.2022 unter https://doi.org/10.3390/s22082860
APA-Zitierstil (7. Ausg.)Bogaert, S., Davis, J., Van Rossom, S., & Vanwanseele, B. (2022). Impact of gender and feature set on machine-learning-based prediction of lower-limb overuse injuries using a single trunk-mounted accelerometer. Sensors, 22(8), 2860.
Chicago-Zitierstil (17. Ausg.)Bogaert, S., J. Davis, S. Van Rossom, und B. Vanwanseele. "Impact of Gender and Feature Set on Machine-learning-based Prediction of Lower-limb Overuse Injuries Using a Single Trunk-mounted Accelerometer." Sensors 22, no. 8 (2022): 2860.
MLA-Zitierstil (9. Ausg.)Bogaert, S., et al. "Impact of Gender and Feature Set on Machine-learning-based Prediction of Lower-limb Overuse Injuries Using a Single Trunk-mounted Accelerometer." Sensors, vol. 22, no. 8, 2022, p. 2860.