SEMG-based estimation of human stiffness: Towards impedance-controlled rehabilitation
Castellini C, Arquer A, Artigas J (2014)
Publication Type: Conference contribution
Publication year: 2014
Publisher: IEEE Computer Society
Pages Range: 604-609
Conference Proceedings Title: Proceedings of the IEEE RAS and EMBS International Conference on Biomedical Robotics and Biomechatronics
Event location: Sao Paulo
ISBN: 9781479931262
DOI: 10.1109/biorob.2014.6913844
Abstract
In rehabilitation robotics, surface electromyography (sEMG) is extensively used as a human-machine interface, mainly for prosthetic/orthotic control purposes. The technique has been proved to be a highly accurate way of detecting a human subject's intended position, force and torque configurations. Widely applied in the clinics, it is gaining even more momentum as polyarticulated, ever-more dexterous selfpowered rehabilitation artifacts appear on the market. In this paper we present a preliminary result about the usage of the same technique to estimate a human subject's hand stiffness in the presence of force-feedback. A novel force feedback control concept based on the modulation of the robot arm stiffness according to the estimated hand stiffness is presented. Thus, the robot arm is set to mimic the stiffness properties of the subject that is controlling the arm, in real time. Six intact subjects were immersed in a simple teleoperation task, in which force feedback was present; the hand stiffness was measured via force perturbation at the master's manipulandum and associated with the sEMG signals. This live estimation of stiffness was then used to control the impedance of the slave. Experimental results show that this system leads to high positional precision but high contact forces when the estimated stiffness is high, and vice-versa. The system has potential applications in impedance control of rehabilitation devices such as, e.g., upper / lower limb prostheses, self-powered orthoses and exoskeleta, leading to an ever-better integration with patients.
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Germany (DE)How to cite
APA:
Castellini, C., Arquer, A., & Artigas, J. (2014). SEMG-based estimation of human stiffness: Towards impedance-controlled rehabilitation. In Raffaella Carloni, Lorenzo Masia, Jose Maria Sabater-Navarro, Marko Ackermann, Sunil Agrawal, Arash Ajoudani, Panagiotis Artemiadis, Matteo Bianchi, Antonio Padilha Lanari Bo, Maura Casadio, Kevin Cleary, Ashish Deshpande, Domenico Formica, Matteo Fumagalli, Nicolas Garcia-Aracil, Sasha Blue Godfrey, Islam S.M. Khalil, Olivier Lambercy, Rui C. V. Loureiro, Leonardo Mattos, Victor Munoz, Hyung-Soon Park, Luis Eduardo Rodriguez Cheu, Roque Saltaren, Adriano A. G. Siqueira, Valentina Squeri, Arno H.A. Stienen, Nikolaos Tsagarakis, Herman Van der Kooij, Bram Vanderborght, Nicola Vitiello, Jose Zariffa, Loredana Zollo (Eds.), Proceedings of the IEEE RAS and EMBS International Conference on Biomedical Robotics and Biomechatronics (pp. 604-609). Sao Paulo, BR: IEEE Computer Society.
MLA:
Castellini, Claudio, Albert Arquer, and Jordi Artigas. "SEMG-based estimation of human stiffness: Towards impedance-controlled rehabilitation." Proceedings of the 5th IEEE RAS and EMBS International Conference on Biomedical Robotics and Biomechatronics, BioRob 2014, Sao Paulo Ed. Raffaella Carloni, Lorenzo Masia, Jose Maria Sabater-Navarro, Marko Ackermann, Sunil Agrawal, Arash Ajoudani, Panagiotis Artemiadis, Matteo Bianchi, Antonio Padilha Lanari Bo, Maura Casadio, Kevin Cleary, Ashish Deshpande, Domenico Formica, Matteo Fumagalli, Nicolas Garcia-Aracil, Sasha Blue Godfrey, Islam S.M. Khalil, Olivier Lambercy, Rui C. V. Loureiro, Leonardo Mattos, Victor Munoz, Hyung-Soon Park, Luis Eduardo Rodriguez Cheu, Roque Saltaren, Adriano A. G. Siqueira, Valentina Squeri, Arno H.A. Stienen, Nikolaos Tsagarakis, Herman Van der Kooij, Bram Vanderborght, Nicola Vitiello, Jose Zariffa, Loredana Zollo, IEEE Computer Society, 2014. 604-609.
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