Characterization of Electromyography Signals of the Forearm Muscles from Pen-Tip Coordinates, using RELS Algorithm
Ines Chihi1, Afef Abdelkrim2, Mohamed Benrejeb3

1Dr. Ines CHIHI, Laboratoire de Recherche en Automatique ”LA.R.A”, Ecole Nationale d’Ingénieurs de Tunis, BP 37, Le Belvédère 1002 Tunis, Tunisie.
2Prof. Afef ABDELKRIM, Laboratoire de Recherche en Automatique ”LA.R.A”, Ecole Nationale d’Ingénieurs de Tunis, BP 37, Le Belvédère 1002 Tunis, Tunisie.
3Prof. Mohamed BENREJEB, Laboratoire de Recherche en Automatique ”LA.R.A”, Ecole Nationale d’Ingénieurs de Tunis, BP 37, Le Belvédère 1002 Tunis, Tunisie.
Manuscript received on March 11, 2013. | Revised Manuscript Received on March 12, 2013. | Manuscript published on March 25, 2013. | PP: 20-22 | Volume-1 Issue-5, March 2013. | Retrieval Number: E0235031513/2013©BEIESP
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© The Authors. Published By: Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)

Abstract: Used in several domains (biotechnology engineering, medical diagnosis, etc.), the reconstitution of ElectroMyoGraphic signals (EMG) is the main contribution of this paper. We propose a linear mathematical structure to generate Integrated ElectroMyoGraphic signals IEMG of the forearm muscles from the coordinates of handwritten traces. The identification of this structure is based on Recursive Extended Least Square algorithm (RELS).
Keywords: Coordinates of handwritten traces, Extended Least Square algorithm, forearm muscles, Integrated Electro Myo Graphic signals.