Force Estimation in Multiple Degrees of Freedom From Intramuscular Emg Via Muscle Synergies

Authors

  • Bahareh Atoufi Institute of Biomedical Engineering, University of New Brunswick
  • Ernest Nlandu Kamavuako Center for Sensory-Motor Interaction, Department of Health Science and Technology, Aalborg University
  • Bernard Hudgins Institute of Biomedical Engineering, University of New Brunswick
  • Kevin Englehart Institute of Biomedical Engineering, University of New Brunswick

Abstract

Force estimation is an important factor in proportional control of prosthetic arms. Muscle synergies seem to be relevant for force estimation since they are patterns of co- activations of muscles during actions. This study investigates the use of muscle synergies extracted from intramuscular electromyography (EMG) for estimating force during multiple degrees of freedom (DOF) voluntary contraction. For this purpose, muscle synergies of the contractions were extracted from six superficial forearm muscles from four able- bodied subjects. Also, the isometric force produced by the wrist during these contractions were recorded along multiple axes each responsible for one DOF. The neural inputs were then fed to an Artificial Neural Network (ANN) to estimate the force. The results show a significant correlation between the estimated and measured force. 

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Published

2013-05-21

How to Cite

[1]
B. Atoufi, E. N. Kamavuako, B. Hudgins, and K. Englehart, “Force Estimation in Multiple Degrees of Freedom From Intramuscular Emg Via Muscle Synergies”, CMBES Proc., vol. 36, no. 1, May 2013.

Issue

Vol. 36 (2013)

Section

Academic