Abstract
In this paper a fuzzy model for control of bionic hand in real-time is proposed. The control process involves interpretation and analysis of surface electromyography signal (sEMG) acquired from patients with amputees. The work considers the use of force sensing resistor to achieve better control of the artificial hand. The classical type-1 Mamdani fuzzy control model is considered for this application. The conducted experiments show comparable results with respect to applied assumptions that give the confidence to implement the proposed concept into real-time control process.
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Acknowledgments
This work was supported by the statutory funds of the Department of Computational Intelligence, Faculty of Computer Science and Managament, Wroclaw University of Science and Technology and partially by EC under FP7, Coordination and Support Action, Grant Agreement Number 316097, ENGINE European Research Centre of Network Intelligence for Innovation Enhancement (http://engine.pwr.edu.pl/). All computer experiments were carried out using computer equipment sponsored by ENGINE project. Additionally, the authors would like to thank the Wroclaw City Council, for the opportunity to work with the Neuro-Rehabilitation Center for the Treatment of Spinal Cord Injuries ‘Akson’, under the ‘Mozart’ city programme 2014/2015.
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Tabakov, M., Fonal, K., Abd-Alhameed, R.A., Qahwaji, R. (2016). Fuzzy Bionic Hand Control in Real-Time Based on Electromyography Signal Analysis. In: Nguyen, NT., Iliadis, L., Manolopoulos, Y., Trawiński, B. (eds) Computational Collective Intelligence. ICCCI 2016. Lecture Notes in Computer Science(), vol 9875. Springer, Cham. https://doi.org/10.1007/978-3-319-45243-2_27
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