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Multi-model approach to characterize human handwriting motion

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Abstract

This paper deals with characterization and modelling of human handwriting motion from two forearm muscle activity signals, called electromyography signals (EMG). In this work, an experimental approach was used to record the coordinates of a pen tip moving on the (x, y) plane and EMG signals during the handwriting act. The main purpose is to design a new mathematical model which characterizes this biological process. Based on a multi-model approach, this system was originally developed to generate letters and geometric forms written by different writers. A Recursive Least Squares algorithm is used to estimate the parameters of each sub-model of the multi-model basis. Simulations show good agreement between predicted results and the recorded data.

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Acknowledgments

The authors wish to thank Professor Rentschler (LMU, Munich) for constructive criticism.

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Authors and Affiliations

  1. Laboratory of Research in Automation (LA.R.A), National School of Engineers of Tunis, Tunis El Manar University, BP 37, Le Belvédère, 1002, Tunis, Tunisia

    I. Chihi, A. Abdelkrim & M. Benrejeb

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  1. I. Chihi
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  2. A. Abdelkrim
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  3. M. Benrejeb
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Correspondence to I. Chihi.

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Chihi, I., Abdelkrim, A. & Benrejeb, M. Multi-model approach to characterize human handwriting motion. Biol Cybern 110, 17–30 (2016). https://doi.org/10.1007/s00422-015-0670-6

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  • DOI: https://doi.org/10.1007/s00422-015-0670-6

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