Sensors 2013, 13(2), 2613-2630; doi:10.3390/s130202613

A Neuro-Fuzzy System for Characterization of Arm Movements

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Received: 13 December 2012; in revised form: 15 February 2013 / Accepted: 16 February 2013 / Published: 21 February 2013
(This article belongs to the Section Physical Sensors)
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Abstract: The myoelectric signal reflects the electrical activity of skeletal muscles and contains information about the structure and function of the muscles which make different parts of the body move. Advances in engineering have extended electromyography beyond the traditional diagnostic applications to also include applications in diverse areas such as rehabilitation, movement analysis and myoelectric control of prosthesis. This paper aims to study and develop a system that uses myoelectric signals, acquired by surface electrodes, to characterize certain movements of the human arm. To recognize certain hand-arm segment movements, was developed an algorithm for pattern recognition technique based on neuro-fuzzy, representing the core of this research. This algorithm has as input the preprocessed myoelectric signal, to disclosed specific characteristics of the signal, and as output the performed movement. The average accuracy obtained was 86% to 7 distinct movements in tests of long duration (about three hours).
Keywords: biomedical instrumentation; surface electromyography (sEMG); arm movements; neuro-fuzzy system
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MDPI and ACS Style

Balbinot, A.; Favieiro, G. A Neuro-Fuzzy System for Characterization of Arm Movements. Sensors 2013, 13, 2613-2630.

AMA Style

Balbinot A, Favieiro G. A Neuro-Fuzzy System for Characterization of Arm Movements. Sensors. 2013; 13(2):2613-2630.

Chicago/Turabian Style

Balbinot, Alexandre; Favieiro, Gabriela. 2013. "A Neuro-Fuzzy System for Characterization of Arm Movements." Sensors 13, no. 2: 2613-2630.

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