Durable and Fatigue-Resistant Soft Peripheral Neuroprosthetics for In Vivo Bidirectional Signaling

Détails bibliographiques
Publié dans:	Advanced materials (Deerfield Beach, Fla.). - 1998. - 33(2021), 20 vom: 02. Mai, Seite e2007346
Auteur principal:	Seo, Hyunseon (Auteur)
Autres auteurs:	Han, Sang Ihn, Song, Kang-Il, Seong, Duhwan, Lee, Kyungwoo, Kim, Sun Hong, Park, Taesung, Koo, Ja Hoon, Shin, Mikyung, Baac, Hyoung Won, Park, Ok Kyu, Oh, Soong Ju, Han, Hyung-Seop, Jeon, Hojeong, Kim, Yu-Chan, Kim, Dae-Hyeong, Hyeon, Taeghwan, Son, Donghee
Format:	Article en ligne
Langue:	English
Publié:	2021
Accès à la collection:	Advanced materials (Deerfield Beach, Fla.)
Sujets:	Journal Article conducting nanocomposites fatigue-resistant nanocomposites in vivo bidirectional signaling soft peripheral neuroprosthetics Gold 7440-57-5 Silver 3M4G523W1G Polymers

Description
Résumé:	© 2021 Wiley-VCH GmbH. Soft neuroprosthetics that monitor signals from sensory neurons and deliver motor information can potentially replace damaged nerves. However, achieving long-term stability of devices interfacing peripheral nerves is challenging, since dynamic mechanical deformations in peripheral nerves cause material degradation in devices. Here, a durable and fatigue-resistant soft neuroprosthetic device is reported for bidirectional signaling on peripheral nerves. The neuroprosthetic device is made of a nanocomposite of gold nanoshell (AuNS)-coated silver (Ag) flakes dispersed in a tough, stretchable, and self-healing polymer (SHP). The dynamic self-healing property of the nanocomposite allows the percolation network of AuNS-coated flakes to rebuild after degradation. Therefore, its degraded electrical and mechanical performance by repetitive, irregular, and intense deformations at the device-nerve interface can be spontaneously self-recovered. When the device is implanted on a rat sciatic nerve, stable bidirectional signaling is obtained for over 5 weeks. Neural signals collected from a live walking rat using these neuroprosthetics are analyzed by a deep neural network to predict the joint position precisely. This result demonstrates that durable soft neuroprosthetics can facilitate collection and analysis of large-sized in vivo data for solving challenges in neurological disorders
Description:	Date Completed 24.07.2024 Date Revised 24.07.2024 published: Print-Electronic Citation Status MEDLINE
ISSN:	1521-4095
DOI:	10.1002/adma.202007346