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Discrete Dynamics in Nature and Society
Volume 2016 (2016), Article ID 6897030, 11 pages
Research Article

A Discrete-Time Algorithm for Stiffness Extraction from sEMG and Its Application in Antidisturbance Teleoperation

1State Key Laboratory of Robotics and Systems, Harbin Institute of Technology, Harbin 150001, China
2Zienkiewicz Centre for Computational Engineering, Swansea University, Swansea SA1 8EN, UK
3Department of Computer Science and Engineering, The Chinese University of Hong Kong, Hong Kong

Received 5 October 2015; Revised 10 January 2016; Accepted 11 January 2016

Academic Editor: Alicia Cordero

Copyright © 2016 Peidong Liang et al. 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.


We have developed a new discrete-time algorithm of stiffness extraction from muscle surface electromyography (sEMG) collected from human operator’s arms and have applied it for antidisturbance control in robot teleoperation. The variation of arm stiffness is estimated from sEMG signals and transferred to a telerobot under variable impedance control to imitate human motor control behaviours, particularly for disturbance attenuation. In comparison to the estimation of stiffness from sEMG, the proposed algorithm is able to reduce the nonlinear residual error effect and to enhance robustness and to simplify stiffness calibration. In order to extract a smoothing stiffness enveloping from sEMG signals, two enveloping methods are employed in this paper, namely, fast linear enveloping based on low pass filtering and moving average and amplitude monocomponent and frequency modulating (AM-FM) method. Both methods have been incorporated into the proposed stiffness variance estimation algorithm and are extensively tested. The test results show that stiffness variation extraction based on the two methods is sensitive and robust to attenuation disturbance. It could potentially be applied for teleoperation in the presence of hazardous surroundings or human robot physical cooperation scenarios.