Automated optimal coordination of multiple-DOF neuromuscular actions in feedforward neuroprostheses

J. Luis Lujan, Patrick E. Crago

Research output: Contribution to journalArticle

20 Scopus citations

Abstract

This paper describes a new method for designing feedforward controllers for multiple-muscle, multiple-DOF, motor system neural prostheses. The design process is based on experimental measurement of the forward input/output properties of the neuromechanical system and numerical optimization of stimulation patterns to meet muscle coactivation criteria, thus resolving the muscle redundancy (i.e., overcontrol) and the coupled DOF problems inherent in neuromechanical systems. We designed feedforward controllers to control the isometric forces at the tip of the thumb in two directions during stimulation of three thumb muscles as a model system. We tested the method experimentally in ten able-bodied individuals and one patient with spinal cord injury. Good control of isometric force in both DOFs was observed, with rms errors less than 10% of the force range in seven experiments and statistically significant correlations between the actual and target forces in all ten experiments. Systematic bias and slope errors were observed in a few experiments, likely due to the neuromuscular fatigue. Overall, the tests demonstrated the ability of a general design approach to satisfy both control and coactivation criteria in multiple-muscle, multiple-axis neuromechanical systems, which is applicable to a wide range of neuromechanical systems and stimulation electrodes.

Original languageEnglish (US)
Pages (from-to)179-187
Number of pages9
JournalIEEE Transactions on Biomedical Engineering
Volume56
Issue number1
DOIs
StatePublished - Jan 1 2009

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Keywords

  • Artificial neural networks (ANNs)
  • Coupled DOFs feedforward control
  • Neuroprostheses

ASJC Scopus subject areas

  • Biomedical Engineering

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