Department for Automation, Biocybernetics and Robotics





Control of rhythmic robotic movements through synchronization with human muscle activity

Petrič T., Gams A., Tomšič M., Žlajpah L., Control of rhythmic robotic movements through synchronization with human muscle activity, 2011 IEEE International Conference on Robotics and Automation, ICRA 2011, May 9-13, 2011, Shanghai, China, Proceedings, 2011, str. 2172-2177.

Bibtex
@INPROCEEDINGS{Petric2011,
author={Petri\v{c}, T. and Gams, A. and Tomsi\v{c}, M. and \v{Z}lajpah, L.},
booktitle={Robotics and Automation (ICRA), 2011 IEEE International Conference on}, title={Control of rhythmic robotic movements through synchronization with human muscle activity},
year={2011},
month={may},
volume={},
number={},
pages={2172 -2177},
doi={10.1109/ICRA.2011.5979936},
ISSN={1050-4729},}

Abstract (English)

We address the problem of extracting the fundamental frequency of an arbitrary periodic or quasi-periodic signal for application in robotic tasks. We focus on controlling periodic robotic movement by extracting the frequency of human movement by using surface electromyography (EMG), a technique by which muscle action potentials are gathered by electrodes placed on the skin. However, since the EMG signal is quasi-periodic with a lot of frequency components and noise, it is difficult to determine the frequency and phase of the measured limb motion. We propose to use nonlinear dynamical systems capable of extracting the frequency and the phase from an unknown periodic signal with an arbitrary waveform. The method uses a whole Fourier series representation in a feedback loop. It is capable of extracting the frequency and the phase of an unknown periodic signal in real-time, without any additional signal processing or preprocessing. Combining this method with an output dynamic system based on dynamic movement primitives, which generate the desired trajectory, allows synchronization between human muscles actions and some other system actions like robot motion or electrical neuromuscular stimulator activation.


Keywords
  • EMG signal
  • Fourier series representation
  • Arbitrary periodic signal
  • Electrical neuromuscular stimulator activation
  • Feedback loop
  • Frequency determination
  • Frequency extraction
  • Human muscle activity
  • Limb motion measurement
  • Muscle action potentials
  • Nonlinear dynamical system
  • Periodic robotic movement control
  • Phase determination
  • Quasiperiodic signal
  • Rhythmic robotic movement control
  • Skin
  • Surface electromyography
  • Fourier series
  • Electromyography
  • Feedback
  • Human-robot interaction
  • Motion control
  • Mmotion measurement
  • Nonlinear dynamical systems

 

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PDF version of the publication
ICRA_TP_2011.pdf, (723 kb)