Injectable Conducting Hydrogels for Use in Neuroprosthetic intervention

Rosa Ghatee, University of Rhode Island

Abstract

Neuroprosthetic interventions are strategies aimed at treating a wide range of neurological disorders, long-term neuroprosthetic treatments traditionally require the implantation of hard metallic electrodes that must sustain their electrical connection with neural tissues for prolonged periods of time. However, surgical introduction of these electrodes and their mechanical mismatch with neural tissues results in inflammation, which disrupts their electrical interface. Our aim was to develop soft, injectable, and conducting hydrogel-based electrode materials and characterize their sustained mechanical and electrical properties before and after sterilization and injection. These gels were made from poly (3-4, ethylenedioxythiophene) (PEDOT) (a conductive polymer) and poly (acrylic acid) (PAAc) and were polymerized at subfreezing temperatures to generate soft 3D macroporous structures. These porous hydrogels exhibited enhances mechanical properties. When optimized, gels exhibited softness consistent with neural tissues (<100 >kPa), excellent toughness (>2 kJ/m3), and excellent strain-at-failure (survived >90% compression without failure). Additionally, these gels’ mechanical properties could be tuned by altering their compositions, though their conductivity remained almost constant and independent of gels composition at about 1 S/cm. This conductivity was much higher than neural tissues making them well-suited for stimulating the sensing in neuroprosthetic applications. Finally, because of their optimized mechanical properties, these gels were highly compressible, exhibited further enhanced electrical properties when compressed, and were capable of surviving injection through 16-gauge needles.^

Subject Area

Biomedical engineering

Recommended Citation

Rosa Ghatee, "Injectable Conducting Hydrogels for Use in Neuroprosthetic intervention" (2015). Dissertations and Master's Theses (Campus Access). Paper AAI1604910.
http://digitalcommons.uri.edu/dissertations/AAI1604910

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