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Bio-potential Neural Activation of Artificial Muscles

Stanford University, Palo Alto, CA, USA

L. Donald Partridge

University of New Mexico, Albuquerque, NM, USA

Mohsen Shahinpoor

University of New Mexico, Artificial Muscle Research Institute (AMRI), Albuquerque, NM, USA, shah{at}unm.edu

Electrical activation of non-biological artificial muscles, such as biocompatible polymeric synthetic artificial muscles, by means of action potential produced by a biological nerve, may become important for people with muscular atrophy or dystrophy or general muscular weakness and deficiency, in the near future. This short article reports on how to stimulate and activate a non-biological muscle such as an ionic polymeric metal composite (IPMC) electro-active artificial muscle with the biological action potential generated by a mammalian nerve such as a mouse sciatic nerve. The investigation further describes the settings to generate optimal movement and force in artificial muscle due to the application of a nerve action potential. The investigation uses the action potential produced by the sciatic nerve of a mouse to generate a voltage, which is subsequently amplified and applied to a sample of an electro-active ionic polymeric artificial muscle to cause it to bend, flex, and deform. The sciatic nerve, in this investigation, is stimulated by a separate signal to cause it to generate an action potential in the range of a few millivolts, which is captured by the platinum electrodes attached to the nerve. These electrodes carry the action potential voltage to an amplifier to amplify it to a few volts and subsequently are input to the ionic polymeric artificial muscle sample to cause it to flex and deform. Different frequencies of stimulation are tried to optimize the motion and force generated by the sciatic nerve action potential in the polymeric artificial muscles.

Key Words: bio-potential • polarization waves • neural activation • ionic polymeric artificial muscles • IPMC

This version was published on February 1, 2007

Journal of Intelligent Material Systems and Structures, Vol. 18, No. 2, 103-109 (2007)
DOI: 10.1177/1045389X06063346


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