Automated optimal coordination of multiple-degree-of-freedom neuromuscular actions in feedforward neuroprostheses

IEEE Trans Biomed Eng, 2009 · DOI: 10.1109/TBME.2008.2002159 · Published: January 1, 2009

Simple Explanation

The study introduces a new method for designing controllers for neural prostheses that control multiple muscles and joints. This method measures the properties of the muscle system and optimizes stimulation patterns to meet coactivation criteria. The method was tested experimentally by controlling thumb forces in two directions using three muscles in able-bodied individuals and a patient with spinal cord injury. The results showed good control of isometric force with low errors. The tests demonstrated the ability to satisfy both control and coactivation criteria in multiple muscle systems, applicable to various systems and electrodes.

Study Duration

Not specified

Participants

10 able-bodied individuals and one patient with spinal cord injury

Evidence Level

Not specified

Key Findings

1
Good control of isometric force was achieved in both degrees of freedom, with RMS errors less than 10% of the force range in seven experiments.
2
Statistically significant correlations were found between the actual and target forces in all ten experiments.
3
Systematic bias and slope errors were observed in a few experiments, potentially due to neuromuscular fatigue.

Research Summary

This paper describes a new method for designing feedforward controllers for multiple-muscle, multiple-degree-of-freedom, motor system neural prostheses. We tested the method experimentally in ten able-bodied individuals and one patient with spinal cord injury. 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, and which is applicable to a wide range of neuromechanical systems and stimulation electrodes.

Practical Implications

Improved Neuroprosthetic Control

The developed controller offers independent control of multiple degrees of freedom, potentially enhancing the flexibility of restored function in individuals with paralysis.

Optimization of Muscle Coactivation

The method optimizes muscle stimulation patterns to minimize coactivation, which can reduce muscle fatigue and improve the efficiency of neuroprosthetic systems.

General Applicability

The design approach is general and applicable to a wide range of neuromechanical systems and stimulation electrodes, making it adaptable to various clinical applications.

Study Limitations

1
Neuromuscular fatigue can introduce systematic bias and slope errors in some experiments.
2
The current study was limited to steady-state control, which may not be suitable for applications requiring dynamic control.
3
Feedforward control is limited by an inability to compensate for unpredictable internal or external perturbations.

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