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A Cyber Expert System for Auto-Tuning Powered Prosthesis Impedance Control Parameters

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Abstract

Typically impedance control parameters (e.g., stiffness and damping) in powered lower limb prostheses are fine-tuned by human experts (HMEs), which is time and resource intensive. Automated tuning procedures would make powered prostheses more practical for clinical use. In this study, we developed a novel cyber expert system (CES) that encoded HME tuning decisions as computer rules to auto-tune control parameters for a powered knee (passive ankle) prosthesis. The tuning performance of CES was preliminarily quantified on two able-bodied subjects and two transfemoral amputees. After CES and HME tuning, we observed normative prosthetic knee kinematics and improved or slightly improved gait symmetry and step width within each subject. Compared to HME, the CES tuning procedure required less time and no human intervention. Hence, using CES for auto-tuning prosthesis control was a sound concept, promising to enhance the practical value of powered prosthetic legs. However, the tuning goals of CES might not fully capture those of the HME. This was because we observed that HME tuning reduced trunk sway, while CES sometimes led to slightly increased trunk motion. Additional research is still needed to identify more appropriate tuning objectives for powered prosthetic legs to improve amputees’ walking function.

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Abbreviations

k :

Stiffness

θ E :

Equilibrium position

C :

Damping coefficient

θ p :

Prosthesis knee joint angle

\(\dot{\theta }_{\text{p}}\) :

Prosthesis knee joint angular velocity

θ peak :

Peak knee angle

T dura :

Gait phase duration

\(\dot{\theta }_{\text{peak}}\) :

Peak angular velocity

m :

Membership function value

D :

Rule degree

N:

Negative

P:

Positive

CES:

Cyber expert system

HME:

Human expert

CV:

Coefficient of variation

DF:

Statistical degrees of freedom

GRF:

Ground reaction force

IC:

Impedance control

IDS:

Initial double support

PKP:

Powered knee prosthesis

RMS:

Root-mean-square

SI:

Symmetry index

SS:

Single support

SWE:

Swing extension

SWF:

Swing flexion

TDS:

Terminal double support

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Acknowledgments

The authors would like to thank Derek Frankena and Stephen Harper of Atlantic Prosthetics and Orthotics and Michael Astilla of Bio-Tech Prosthetics and Orthotics for fitting our study participants with prosthetic adaptors and sockets. We also thank William Boatwright for assisting with data collection and Andrea Brandt, Dr. Jon Stallings, and Dr. Consuelo Arellano for assisting with statistical analysis. This work was partly funded by a seed grant from the UNC/NCSU Rehabilitation Engineering Core, and by the National Science Foundation (NSF #1361549, 1406750, and 1527202).

Conflict of interest

No benefits in any form have been or will be received from a commercial party related directly or indirectly to the subject of this manuscript.

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Authors and Affiliations

  1. UNC/NCSU Joint Department of Biomedical Engineering, North Carolina State University, 4402D Engineering Building III, Raleigh, NC, 27695, USA

    He Huang, Dustin L. Crouch, Ming Liu, Gregory S. Sawicki & Ding Wang

  2. UNC/NCSU Joint Department of Biomedical Engineering, University of North Carolina at Chapel Hill, 150A MacNider Hall, Chapel Hill, NC, 27599, USA

    He Huang, Dustin L. Crouch, Ming Liu, Gregory S. Sawicki & Ding Wang

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  1. He Huang
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  2. Dustin L. Crouch
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Correspondence to He Huang.

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Associate Editor Michael Torry oversaw the review of this article.

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Huang, H., Crouch, D.L., Liu, M. et al. A Cyber Expert System for Auto-Tuning Powered Prosthesis Impedance Control Parameters. Ann Biomed Eng 44, 1613–1624 (2016). https://doi.org/10.1007/s10439-015-1464-7

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  • DOI: https://doi.org/10.1007/s10439-015-1464-7

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