Liu, P.-L, Chang, C.-C, Kao, H.-Y & Hsiao, C.-Y. (2022). Artificial neural network can improve the accuracy of a markerless skeletal model in L5/S1 position estimation during symmetric lifting. Journal of Biomechanics, 130 , 110844. Zugriff am 29.03.2022 unter https://doi.org/10.1016/j.jbiomech.2021.110844
APA-Zitierstil (7. Ausg.)Liu, P., Chang, C., Kao, H., & Hsiao, C. (2022). Artificial neural network can improve the accuracy of a markerless skeletal model in L5/S1 position estimation during symmetric lifting. Journal of Biomechanics, 130, 110844.
Chicago-Zitierstil (17. Ausg.)Liu, P.-L, C.-C Chang, H.-Y Kao, und C.-Y Hsiao. "Artificial Neural Network Can Improve the Accuracy of a Markerless Skeletal Model in L5/S1 Position Estimation During Symmetric Lifting." Journal of Biomechanics 130 (2022): 110844.
MLA-Zitierstil (9. Ausg.)Liu, P.-L, et al. "Artificial Neural Network Can Improve the Accuracy of a Markerless Skeletal Model in L5/S1 Position Estimation During Symmetric Lifting." Journal of Biomechanics, vol. 130, 2022, p. 110844.