Handwriting Velocity Modeling by Artificial Neural Networks
Description
The handwriting is a physical demonstration of a
complex cognitive process learnt by man since his childhood. People
with disabilities or suffering from various neurological diseases are
facing so many difficulties resulting from problems located at the
muscle stimuli (EMG) or signals from the brain (EEG) and which
arise at the stage of writing. The handwriting velocity of the same
writer or different writers varies according to different criteria: age,
attitude, mood, writing surface, etc. Therefore, it is interesting to
reconstruct an experimental basis records taking, as primary
reference, the writing speed for different writers which would allow
studying the global system during handwriting process. This paper
deals with a new approach of the handwriting system modeling based
on the velocity criterion through the concepts of artificial neural
networks, precisely the Radial Basis Functions (RBF) neural
networks. The obtained simulation results show a satisfactory
agreement between responses of the developed neural model and the
experimental data for various letters and forms then the efficiency of
the proposed approaches.
Files
9999920.pdf
Files
(190.3 kB)
| Name | Size | Download all |
|---|---|---|
|
md5:671ac9b45748f17030c5c12690cc58f8
|
190.3 kB | Preview Download |
Additional details
References
- D. Van Der Gon, J. P. Thuring and J. Strackee, "A handwriting simulator," Physics in Medical Biology, pp. 407-414, 1962.
- J. S. MacDonald, "Experimental studies of handwriting signals," Ph. D. Dissertation, Mass. Inst. Tech. Cambridge, 1964..
- M. Yasuhara, "Experimental studies of handwriting process," Rep. Univ. Electro- Comm. Japan, 25-2, pp. 233-254, 1975.
- S. Edelman and T. Flash, "A model of handwriting, Biological Cybernetics," vol. 57, pp. 25-36, 1987.
- M. Sano, T. Kosaku and Y. Murata, "Modeling of Human Handwriting Motion by Electromyographic Signals on Forearm Muscles," CCCT'03. Orlando- Florida, 2003.
- M. Benrejeb, A. El Abed-Abdelkrim and M. Sano, "Sur l'étude du processus d'écriture à la main. Approches classiques et non conventionnelles," Revue e-STA, vol. 3, No. 1, Premier trimestre 2006, (in French).
- A. Abdelkrim, "Contribution à la modélisation du processus d'écriture à la main par approches relevant du calcul évolutif," Thèse de Doctorat, ENIT. Tunis, 2005, (in French).
- A. Abdelkrim, M. Benrejeb and M. Sano, "PAW handwriting neural system," International Conference on Communication, Computer and Power (ICCCP'01), IEEE/IEE Conference, Muscat, pp. 207-211, Feb. 2001.
- M.A. Slim, A. Abdelkrim and M. Benrejeb, "Handwriting process modelling by artificial neural networks," International Journal of Computer Information Systems and Industrial Management Applications (IJCISIM), Vol. 5, pp. 297-307, 2013. [10] R. Plamondon, "A kinematics theory of rapid human movements. Part I : Movement representation and Generation," Biological Cybernetics, Vol. 72, pp. 295-307, 1995. [11] R. Plamondon, "A kinematics theory of rapid human movements. Part II : Movement time and control," Biological Cybernetics, Vol. 72, pp. 309- 320, 1995. [12] M. A. Alimi, "Contribution au développement d'une théorie de génération de mouvements simples et rapides. Application au manuscrit," Thèse de Doctorat, Université de Montréal, Canada,1995, (in French). [13] J. V. Basmajian and C. J. De Luca, "Muscles alive: their function revealed by electromyography," Baltimore: Williams & Wilkins, 1985. [14] C. J. De Luca, "Myoelectrical manifestations of localized muscular fatigue in humans," Crit. Rev. Biomed. Eng., 11(4), pp. 251-279, 1985. [15] R. Merletti, A. Rainoldi and D. Farina, "Surface electromyography for noninvasive characterization of muscle," Execs. Sport. Sci. Rev., 29(1), pp. 20-25, 2001. [16] F. De Coulon, "théorie et traitement des signaux," Presses Polytechniques Romandes, vol.6, de Lausane, 1984, (in French). [17] R. Plamondon, "What does differential geometry tell us about handwriting generation?, " Proc. of the Third International Symposium on Handwriting and Computer Applications, Montréal, pp. 11-13, 1987. [18] Z. R. Yang, "A Novel Radial Basis Function Neural Network for Discriminant Analysis," IEEE Trans. on Neural Networks, vol. 17, Issue: 3, pp. 604-612, May 2006. [19] P. Borne, M. Benrejeb and J. Haggège, Les réseaux de neurones. Présentation et application. Ed. Technip, Paris, 2007, (in French). [20] J. Moody and P. J. Antsaklis, "The dependence identification neural network construction algorithm," IEEE Trans. on Neural Networks, vol. 7, pp. 3-15, 1996. [21] A. Sifaoui, A. Abdelkrim, S. Alouane and M. Benrejeb, "On new RBF neural network construction algorithm for classification," In Proceedings of the Studies in Informatics and Control, SIC, vol. 18, No. 2, pp.103- 110, 2009. [22] M.A. Slim, A. Abdelkrim and M. Benrejeb, "RBF neural networks for handwriting process modelling". In Proceedings of the Third International Conference on Soft Computing and Pattern Recognition (SoCPaR2011), IEEE Conference, pp. 384-389, Dalian, China, 2011.