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

Jose Lujan, Patrick E. Crago

Research output: Contribution to journalArticle

20 Citations (Scopus)

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 2009
Externally publishedYes

Fingerprint

Muscle
Neural prostheses
Controllers
Experiments
Redundancy
Fatigue of materials
Electrodes

Keywords

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

ASJC Scopus subject areas

  • Biomedical Engineering

Cite this

Automated optimal coordination of multiple-DOF neuromuscular actions in feedforward neuroprostheses. / Lujan, Jose; Crago, Patrick E.

In: IEEE Transactions on Biomedical Engineering, Vol. 56, No. 1, 01.2009, p. 179-187.

Research output: Contribution to journalArticle

@article{719910913e9f4d79b90ed18137b43635,
title = "Automated optimal coordination of multiple-DOF neuromuscular actions in feedforward neuroprostheses",
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.",
keywords = "Artificial neural networks (ANNs), Coupled DOFs feedforward control, Neuroprostheses",
author = "Jose Lujan and Crago, {Patrick E.}",
year = "2009",
month = "1",
doi = "10.1109/TBME.2008.2002159",
language = "English (US)",
volume = "56",
pages = "179--187",
journal = "IEEE Transactions on Biomedical Engineering",
issn = "0018-9294",
publisher = "IEEE Computer Society",
number = "1",

}

TY - JOUR

T1 - Automated optimal coordination of multiple-DOF neuromuscular actions in feedforward neuroprostheses

AU - Lujan, Jose

AU - Crago, Patrick E.

PY - 2009/1

Y1 - 2009/1

N2 - 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.

AB - 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.

KW - Artificial neural networks (ANNs)

KW - Coupled DOFs feedforward control

KW - Neuroprostheses

UR - http://www.scopus.com/inward/record.url?scp=60549088770&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=60549088770&partnerID=8YFLogxK

U2 - 10.1109/TBME.2008.2002159

DO - 10.1109/TBME.2008.2002159

M3 - Article

VL - 56

SP - 179

EP - 187

JO - IEEE Transactions on Biomedical Engineering

JF - IEEE Transactions on Biomedical Engineering

SN - 0018-9294

IS - 1

ER -