The main objective of this project consists of the prediction of muscle activations of one subject, through the application of the principal component analysis on another subject. The process starts with the signal processing and filtering of kinematics and EMG signals from both subjects, subsecuently, the principal components are obtained by using the kinematics and EMG data from the first subject. The next step is to obtain the new muscle activations from the second subject, by scalling the principal components with the kinematics from the first subject as a reference. Finally, the whole MATLAB code is translated into python to simulate in OpenSim the kinematics of a human muscle-driven model. The results are focused mainly on the comparison between the muscle activations calculated during this project and the original muscle activations from the second subject and on the analysis of the principal components and scale factors calculated to obtain the muscle activations. The idea is that in a near future, this analysis could be applied to perform a study of the movement deficiencies of a subject that suffers from some kind of mobility impairement without having to measure the EMG signals, with the intention of finding the optimal treatment to improve its rehabilitation.