Abstract
Problem statement: Handwriting movement is one of the most complex activities of human motions. It’s a blend of kinesthetic, cognitive, perceptual and motor components. The study of this biological process shows that a bell-shaped velocity profiles are generally observed in the handwriting motion. We, therefore, assume that the handwriting speed has an important role in control and generation of this human process and that the control nervous system might take this information into account to reconstruct the pen-tip trace. The Electromyography (EMG) signals measured on the skin surface of a writing forearm contain the adequate information to present the motor commands of the handwriting process. Approach: In this study, an identification technique, based on Recursive Least Square algorithm (RLS), is proposed to identify the pen-tip movement in human handwriting process, by using input and output data which present EMG signals and velocities according to x and y coordinates. Results: The proposed approach of handwriting identification indicates that the pen-tip movement can be reconstruct from EMG signals of forearm muscles. The obtained results show better concordance with the experimental data than results obtained from other approach elaborated in the literature. Conclusion: The proposed handwriting model shows generally, good agreement with the real pen-tip movement. This method should be refined in monowriter and multiwriter case and independently of the size or the direction of the writing shape.
Highlights
The recognation of humain handwriting has attracted the attention of many investigators (Shalabi et al, 2005; Al-Omari et al, 2009), but the modeling of this complex biological process has attracted the interest of fewer researches
Bd,i(q) = Irreducible polynomial of shift operator q−1, defined by [q−1d(k) = d(k − 1)], which corresponds to the i-th Integrated EMG (IEMG) signal
The bell shapes shown in the handwriting velocity profile can contain information about the kind of the pen-tip movement
Summary
The recognation of humain handwriting has attracted the attention of many investigators (Shalabi et al, 2005; Al-Omari et al, 2009), but the modeling of this complex biological process has attracted the interest of fewer researches. The global generalized handwriting model, proposed in (Benrejeb et al, 2006), proved that the pen-tip position is detected by the means of the eyes and transmitted to the brain to be analyzed and compared with the desired position. Handwriting speed has attracted the attention of other investigators who considered it as a means of distinguishing between the writing of one person and that of another. They proved that the handwriting speed is a fundamental characteristic for modeling the handwriting system. Other models based on the velocity profile were presented in (Plamondon, 1995a; 1995b)
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