Finite element modeling of electromagnetic signal propagation in a phantom arm

Improving the control of artificial arms remains a considerable challenge. It may be possible to graft remaining peripheral nerves in an amputated limb to spare muscles in or near the residual limb and use these nerve-muscle grafts as additional myoelectric control signals. This would allow simultan...

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Bibliographic Details
Published in:IEEE transactions on neural systems and rehabilitation engineering 2001-12, Vol.9 (4), p.346-354
Main Authors: Kuiken, T.A., Stoykov, N.S., Popovic, M., Lowery, M., Taflove, A.
Format: Article
Language:English
Subjects:
Amputation
Arm
Arm - physiology
Artificial Limbs
Body Surface Potential Mapping - methods
Computer Simulation
Crosstalk
Electric Conductivity
Electric potential
Electromagnetic Fields
Electromagnetic modeling
Electromagnetic propagation
Electromyography
Electromyography - methods
Finite Element Analysis
Finite element methods
Humans
Imaging phantoms
Models, Biological
Muscle, Skeletal - physiology
Muscles
Neuromuscular Junction - physiopathology
Prostheses
Reproducibility of Results
Studies
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Summary:Improving the control of artificial arms remains a considerable challenge. It may be possible to graft remaining peripheral nerves in an amputated limb to spare muscles in or near the residual limb and use these nerve-muscle grafts as additional myoelectric control signals. This would allow simultaneous control of multiple degrees of freedom (DOF) and could greatly improve the control of artificial limbs. For this technique to be successful, the electromyography (EMG) signals from the nerve-muscle grafts would need to be independent of each other with minimal crosstalk. To study EMG signal propagation and quantify crosstalk, finite element (FE) models were developed in a phantom-arm model. The models were validated with experimental data collected by applying sinusoidal excitations to a phantom-arm model and recording the surface electric potential distribution. There was a very high correlation (r>0.99) between the FEM data and the experimental data, with the error in signal magnitude generally less than 5%. Simulations were then performed using muscle dielectric properties with static, complex, and full electromagnetic solvers. The results indicate that significant displacement currents can develop (>50% of total current) and that the fall-off of surface signal power varies with how the signal source is modeled.
ISSN:1534-4320
1558-0210
DOI:10.1109/7333.1000114