Internal Model Control to Characterize Human Handwriting Motion

The main purpose of this paper is to consider the human handwriting process as an Internal Model Control structure (IMC). The proposed approach allows characterizing the biological process from two muscles activities of the forearm, named ElectroMyoGraphy signals (EMG). For this, an experimental approach was used to record the coordinates of a pen-tip moving on (x,y) plane and EMG signals during the handwriting act. In this sense direct and inverse handwriting models are proposed to establish the relationship between the muscles activities of the forearm and the velocity of the pen-tip. Recursive Least Squares algorithm (RLS) is used to estimate the parameters of both models (direct and inverse). Simulations show good agreement between the proposed approach results and the recorded data.