The raise of collaborative robotics has allowed to create new spaces where robots and humans work in proximity. Consequently, to predict human movements and his/her final intention becomes crucial to anticipate robot next move, preserving safety and increasing efficiency. In this paper we propose a human-arm prediction algorithm that allows to infer if the human operator is moving towards the robot to intentionally interact with it. The human hand position is tracked by an RGB-D camera online. By combining the Minimum Jerk model with Semi-Adaptable Neural Networks we obtain a reliable prediction of the human hand trajectory and final target in a short amount of time. The proposed algorithm was tested in a multi-movements scenario with FANUC LR Mate 200iD/7L industrial robot.