Abstract
Autonomic nerves are typically only hundreds of microns in diameter near their organ targets and these carry all of the sympathetic and parasympathetic control signals. We present a cuff-less microneedle array specifically designed to potentially map small autonomic nerves. The focus of this paper is the design and fabrication of an ultra-miniaturized silicon needle array on a silicone substrate. We demonstrate arrays having 25 to 100 microneedles. Each needle has a 1-micron tip and dual-taper shaft. We demonstrate an ability to control the tip shape, angle, and shaft angle which is important for balancing sharpness and stiffness. These high-density arrays also include a special backside anchor embedded in silicone for stability in the elastic substrate, yet the array freely wraps over a 300-μm nerve. Another critical method presented here is a surgical technique for inserting and securing an array without a cuff (as small as 0.3 mm wide and 1.2 mm long) by photochemical bonding of collagen/Rose Bengal adhesive agents to epineurium. Future work will focus on device functionalization and histological characterization in a rat vagus model.
Original language | English |
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Title of host publication | 9th International IEEE EMBS Conference on Neural Engineering, NER 2019 |
Publisher | IEEE Computer Society |
Pages | 827-830 |
Number of pages | 4 |
ISBN (Electronic) | 9781538679210 |
DOIs | |
Publication status | Published - 2019 May 16 |
Event | 9th International IEEE EMBS Conference on Neural Engineering, NER 2019 - San Francisco, United States Duration: 2019 Mar 20 → 2019 Mar 23 |
Publication series
Name | International IEEE/EMBS Conference on Neural Engineering, NER |
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Volume | 2019-March |
ISSN (Print) | 1948-3546 |
ISSN (Electronic) | 1948-3554 |
Conference
Conference | 9th International IEEE EMBS Conference on Neural Engineering, NER 2019 |
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Country/Territory | United States |
City | San Francisco |
Period | 19/3/20 → 19/3/23 |
Bibliographical note
Funding Information:Research supported by NIH SPARC, Award OT2OD024907 D. Yan (yando@umich.edu), D. Ratze, S. Huang, S. Parizi, M. Kushner (mjkush@umich.edu), E. Yoon (esyoon@umich.edu), J. Seymour (seymourj@umich.edu) are with the University of Michigan Department of Electrical Engineering & Computer Science, Ann Arbor, MI, 48109 USA
Publisher Copyright:
© 2019 IEEE.
All Science Journal Classification (ASJC) codes
- Artificial Intelligence
- Mechanical Engineering