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.
|Title of host publication||9th International IEEE EMBS Conference on Neural Engineering, NER 2019|
|Publisher||IEEE Computer Society|
|Number of pages||4|
|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
|Name||International IEEE/EMBS Conference on Neural Engineering, NER|
|Conference||9th International IEEE EMBS Conference on Neural Engineering, NER 2019|
|Period||19/3/20 → 19/3/23|
Bibliographical noteFunding Information:
Research supported by NIH SPARC, Award OT2OD024907 D. Yan (firstname.lastname@example.org), D. Ratze, S. Huang, S. Parizi, M. Kushner (email@example.com), E. Yoon (firstname.lastname@example.org), J. Seymour (email@example.com) are with the University of Michigan Department of Electrical Engineering & Computer Science, Ann Arbor, MI, 48109 USA
© 2019 IEEE.
All Science Journal Classification (ASJC) codes
- Artificial Intelligence
- Mechanical Engineering