Learning human reach-to-grasp strategies: Towards EMG-based control of robotic arm-hand systems

Minas V. Liarokapis, Panagiotis Artemiadis, Pantelis T. Katsiaris, Kostas J. Kyriakopoulos, Elias S. Manolakos

Research output: Chapter in Book/Report/Conference proceedingConference contribution

39 Scopus citations

Abstract

Reaching and grasping of objects in an everyday-life environment seems so simple for humans, though so complicated from an engineering point of view. Humans use a variety of strategies for reaching and grasping anything from the simplest to the most complicated objects, achieving high dexterity and efficiency. This seemingly simple process of reach-to-grasp relies on the complex coordination of the musculoskeletal system of the upper limbs. In this paper, we study the muscular co-activation patterns during a variety of reach-to-grasp motions, and we introduce a learning scheme that can discriminate between different strategies. This scheme can then classify reach-to-grasp strategies based on the muscular co-activations. We consider the arm and hand as a whole system, therefore we use surface ElectroMyoGraphic (sEMG) recordings from muscles of both the upper arm and the forearm. The proposed scheme is tested in extensive paradigms proving its efficiency, while it can be used as a switching mechanism for task-specific motion and force estimation models, improving EMG-based control of robotic arm-hand systems.

Original languageEnglish (US)
Title of host publication2012 IEEE International Conference on Robotics and Automation, ICRA 2012
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages2287-2292
Number of pages6
ISBN (Print)9781467314039
DOIs
StatePublished - Jan 1 2012
Event 2012 IEEE International Conference on Robotics and Automation, ICRA 2012 - Saint Paul, MN, United States
Duration: May 14 2012May 18 2012

Publication series

NameProceedings - IEEE International Conference on Robotics and Automation
ISSN (Print)1050-4729

Conference

Conference 2012 IEEE International Conference on Robotics and Automation, ICRA 2012
CountryUnited States
CitySaint Paul, MN
Period5/14/125/18/12

Keywords

  • Boxplot Zones
  • Classification
  • ElectroMyoGraphy (EMG)
  • Learning Scheme
  • Muscular Co-Activation Patterns
  • Random Forests
  • Synergistic Profiles

ASJC Scopus subject areas

  • Software
  • Control and Systems Engineering
  • Artificial Intelligence
  • Electrical and Electronic Engineering

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    Liarokapis, M. V., Artemiadis, P., Katsiaris, P. T., Kyriakopoulos, K. J., & Manolakos, E. S. (2012). Learning human reach-to-grasp strategies: Towards EMG-based control of robotic arm-hand systems. In 2012 IEEE International Conference on Robotics and Automation, ICRA 2012 (pp. 2287-2292). [6225047] (Proceedings - IEEE International Conference on Robotics and Automation). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICRA.2012.6225047