Internal Model Control to Characterize Human Handwriting Motion
Ines Chihi,
Afef Abdelkrim, and Mohamed Benrejeb
National School of Engineers of Tunisia, Tunis El Manar University, Tunisia
Abstract: 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.
Keywords: Human handwriting
process; IMC; the muscular activities; direct and inverse handwriting models;
velocity of the pen-tip; RLS algorithm.
Received
January 6, 2015; accepted September 22, 2015