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Cited 24 time in webofscience Cited 24 time in scopus
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Durable and Fatigue-Resistant Soft Peripheral Neuroprosthetics for In Vivo Bidirectional Signaling

Authors
Seo, H.[Seo, H.]Han, S.I.[Han, S.I.]Song, K.-I.[Song, K.-I.]HWAN, S. D.[HWAN, SEONG DU]Lee, K.[Lee, K.]Kim, S.H.[Kim, S.H.]Park, T.[Park, T.]Koo, J.H.[Koo, J.H.]Shin, M.[Shin, M.]Baac, H.W.[Baac, H.W.]Park, O.K.[Park, O.K.]Oh, S.J.[Oh, S.J.]Han, H.-S.[Han, H.-S.]Jeon, H.[Jeon, H.]Kim, Y.-C.[Kim, Y.-C.]Kim, D.-H.[Kim, D.-H.]Hyeon, T.[Hyeon, T.]Son, D.[Son, D.]
Issue Date
May-2021
Publisher
John Wiley and Sons Inc
Keywords
conducting nanocomposites; fatigue-resistant nanocomposites; in vivo bidirectional signaling; soft peripheral neuroprosthetics
Citation
Advanced Materials, v.33, no.20
Indexed
SCIE
SCOPUS
Journal Title
Advanced Materials
Volume
33
Number
20
URI
https://scholarworks.bwise.kr/skku/handle/2021.sw.skku/1539
DOI
10.1002/adma.202007346
ISSN
0935-9648
Abstract
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. © 2021 Wiley-VCH GmbH
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