Skip to main content Accessibility help
×
Home
Hostname: page-component-684899dbb8-4btjb Total loading time: 0.32 Render date: 2022-05-26T00:48:09.224Z Has data issue: true Feature Flags: { "shouldUseShareProductTool": true, "shouldUseHypothesis": true, "isUnsiloEnabled": true, "useRatesEcommerce": false, "useNewApi": true }

Article contents

A Hybrid 3D Printing and Robotic-assisted Embedding Approach for Design and Fabrication of Nerve Cuffs with Integrated Locking Mechanisms

Published online by Cambridge University Press:  23 April 2018

Yuxin Tong
Affiliation:
Department of Industrial and Systems Engineering, Virginia Tech, Blacksburg, VA24061, USA
Jamie M. Murbach
Affiliation:
Department of Biomedical Engineering, University of Florida, Gainesville, FL32611, USA
Vivek Subramanian
Affiliation:
Department of Materials Science and Engineering, University of Delaware, Newark, DE19716, USA
Shrirang Chhatre
Affiliation:
Department of Materials Science and Engineering, University of Delaware, Newark, DE19716, USA
Francisco Delgado
Affiliation:
Department of Biomedical Engineering, University of Florida, Gainesville, FL32611, USA
David C. Martin
Affiliation:
Department of Materials Science and Engineering, University of Delaware, Newark, DE19716, USA
Kevin J. Otto
Affiliation:
Department of Biomedical Engineering, University of Florida, Gainesville, FL32611, USA Department of Neuroscience, University of Florida, Gainesville, FL32611, USA
Mario Romero-Ortega
Affiliation:
Department of Bioengineering, University of Texas at Dallas, Richardson, TX75080, USA
Blake N. Johnson*
Affiliation:
Department of Industrial and Systems Engineering, Virginia Tech, Blacksburg, VA24061, USA Department of Chemical Engineering, Virginia Tech, Blacksburg, VA24061, USA
*
*(Email: bnj@vt.edu)
Get access

Abstract

The ability to interface electronic materials with the peripheral nervous system is required for stimulation and monitoring of neural signals. Thus, the design and engineering of robust neural interfaces that maintain material-tissue contact in the presence of material or tissue micromotion offer the potential to conduct novel measurements and develop future therapies that require chronic interface with the peripheral nervous system. However, such remains an open challenge given the constraints of existing materials sets and manufacturing approaches for design and fabrication of neural interfaces. Here, we investigated the potential to leverage a rapid prototyping approach for the design and fabrication of nerve cuffs that contain supporting features to mechanically stabilize the interaction between cuff electrodes and peripheral nerve. A hybrid 3D printing and robotic-embedding (i.e., pick-and-place) system was used to design and fabricate silicone nerve cuffs (800 µm diameter) containing conforming platinum (Pt) electrodes. We demonstrate that the electrical impedance of the cuff electrodes can be reduced by deposition of the conducting polymer poly(3,4-ethylenedioxythiophene) polystyrene sulfonate (PEDOT:PSS) on cuff electrodes via a post-processing electropolymerization technique. The computer-aided design and manufacturing approach was also used to design and integrate supporting features to the cuff that mechanically stabilize the interface between the cuff electrodes and the peripheral nerve. Both ‘self-locking’ and suture-assisted locking mechanisms are demonstrated based on the principle of making geometric alterations to the cuff opening via 3D printing. Ultimately, this work shows 3D printing offers considerable opportunity to integrate supporting features, and potentially even novel electronic materials, into nerve cuffs that can support the design and engineering of next generation neural interfaces.

Type
Articles
Copyright
Copyright © Materials Research Society 2018 

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Murphy, S. V. and Atala, A., Nat. Biotech. 32, 773785 (2014).CrossRefGoogle Scholar
Kong, Y. L., Gupta, M. K., Johnson, B. N., and McAlpine, M. C., Nano Today 11, 330350 (2016).CrossRefGoogle Scholar
Macdonald, E., Salas, R., Espalin, D., Perez, M., Aguilera, E., Muse, D. and Wicker, R. B., IEEE Access 2, 234242 (2014).CrossRefGoogle Scholar
Johnson, B. N., Lancaster, K. Z., Zhen, G., He, J., Gupta, M. K., Kong, Y. L., Engel, E. A., Krick, K. D., Ju, A., Meng, F., Enquist, L. W., Jia, X., and McAlpine, M. C., Adv. Funct. Mater. 25, 62056217 (2015).CrossRefGoogle Scholar
Johnson, B. N., Lancaster, K. Z., Hogue, I. B., Meng, F., Kong, Y. L., Enquist, L. W., and McAlpine, M. C., Lab Chip 16, 13931400 (2016).CrossRefGoogle Scholar
Singh, M., Tong, Y., Webster, K., Cesewski, E., Haring, A. P., Laheri, S., Carswell, B., O’Brien, T. J., Aardema, C. H., Senger, R. S., Robertson, J. L., and Johnson, B. N., Lab Chip 17, 25612571 (2017).CrossRefGoogle Scholar
Haring, A. P., Sontheimer, H., and Johnson, B. N., Stem Cell Rev. Rep., 13, 381406 (2017).CrossRefGoogle Scholar
Haring, A. P., Khan, A. U., Liu, G., and Johnson, B. N., Adv. Opt. Mater. 5, 1700367 (2017).CrossRefGoogle Scholar
Gupta, M. K., Meng, F., Johnson, B. N., Kong, Y. L., Tian, L., Yeh, Y.-W., Masters, N., Singamaneni, S., and McAlpine, M. C., Nano Lett. 15, 53215329 (2015).CrossRefGoogle Scholar
Kang, H.-W., Lee, S. J., Ko, I. K., Kengla, C., Yoo, J. J., and Atala, A., Nat. Biotech. 34, 312319 (2016).CrossRefGoogle Scholar
Kong, Y. L., Tamargo, I., Kim, H., Johnson, B. N., Gupta, M. K., Koh, T.-W., Chin, H.-A., Steingart, D. A., Rand, B. P., and McAlpine, M. C., Nano Lett. 14, 70177023 (2014).CrossRefGoogle Scholar
Johnson, B. N. and Jia, X., Neural Regen. Res. 11, 15681569 (2016).CrossRefGoogle Scholar
Pateman, C. J., Harding, A. J., Glen, A., Taylor, C. S., Christmas, C. R., Robinson, P. P., Rimmer, S., Boissonade, F. M., Claeyssens, F., and Haycock, J. W., Biomaterials 49, 7789 (2015).CrossRefGoogle Scholar
Lozano, R., Stevens, L., Thompson, B. C., Gilmore, K. J., Gorkin Iii, R., Stewart, E. M., in het Panhuis, M., Romero-Ortega, M., and Wallace, G. G., Biomaterials 67, 264273 (2015).CrossRefGoogle Scholar
Ludwig, K. A., Uram, J. D., Yang, J., Martin, D. C., and Kipke, D. R., J. Neural Eng. 3, 5970 (2006).CrossRefGoogle Scholar
Cui, X. and Martin, D. C., Sens. Actuators B 89, 92102 (2003).CrossRefGoogle Scholar
Wilks, S. J., Woolley, A. J., Ouyang, L., Martin, D.C., and Otto, K. J., Conf. Proc. IEEE Eng. Med. Biol. Soc., 5412-5415 (2011).Google Scholar

Save article to Kindle

To save this article to your Kindle, first ensure coreplatform@cambridge.org is added to your Approved Personal Document E-mail List under your Personal Document Settings on the Manage Your Content and Devices page of your Amazon account. Then enter the ‘name’ part of your Kindle email address below. Find out more about saving to your Kindle.

Note you can select to save to either the @free.kindle.com or @kindle.com variations. ‘@free.kindle.com’ emails are free but can only be saved to your device when it is connected to wi-fi. ‘@kindle.com’ emails can be delivered even when you are not connected to wi-fi, but note that service fees apply.

Find out more about the Kindle Personal Document Service.

A Hybrid 3D Printing and Robotic-assisted Embedding Approach for Design and Fabrication of Nerve Cuffs with Integrated Locking Mechanisms
Available formats
×

Save article to Dropbox

To save this article to your Dropbox account, please select one or more formats and confirm that you agree to abide by our usage policies. If this is the first time you used this feature, you will be asked to authorise Cambridge Core to connect with your Dropbox account. Find out more about saving content to Dropbox.

A Hybrid 3D Printing and Robotic-assisted Embedding Approach for Design and Fabrication of Nerve Cuffs with Integrated Locking Mechanisms
Available formats
×

Save article to Google Drive

To save this article to your Google Drive account, please select one or more formats and confirm that you agree to abide by our usage policies. If this is the first time you used this feature, you will be asked to authorise Cambridge Core to connect with your Google Drive account. Find out more about saving content to Google Drive.

A Hybrid 3D Printing and Robotic-assisted Embedding Approach for Design and Fabrication of Nerve Cuffs with Integrated Locking Mechanisms
Available formats
×
×

Reply to: Submit a response

Please enter your response.

Your details

Please enter a valid email address.

Conflicting interests

Do you have any conflicting interests? *