Conformable Electrode Arrays for Wearable Neuroprostheses.

carbon black elastomer electrode array functional electrical stimulation hand function

Journal

Sensors (Basel, Switzerland)
ISSN: 1424-8220
Titre abrégé: Sensors (Basel)
Pays: Switzerland
ID NLM: 101204366

Informations de publication

Date de publication:
09 Mar 2023
Historique:
received: 06 02 2023
revised: 03 03 2023
accepted: 07 03 2023
medline: 31 3 2023
entrez: 30 3 2023
pubmed: 31 3 2023
Statut: epublish

Résumé

Wearable electrode arrays can selectively stimulate muscle groups by modulating their shape, size, and position over a targeted region. They can potentially revolutionize personalized rehabilitation by being noninvasive and allowing easy donning and doffing. Nevertheless, users should feel comfortable using such arrays, as they are typically worn for an extended time period. Additionally, to deliver safe and selective stimulation, these arrays must be tailored to a user's physiology. Fabricating customizable electrode arrays needs a rapid and economical technique that accommodates scalability. By leveraging a multilayer screen-printing technique, this study aims to develop personalizable electrode arrays by embedding conductive materials into silicone-based elastomers. Accordingly, the conductivity of a silicone-based elastomer was altered by adding carbonaceous material. The 1:8 and 1:9 weight ratio percentages of carbon black (CB) to elastomer achieved conductivities between 0.0021-0.0030 S cm

Identifiants

pubmed: 36991692
pii: s23062982
doi: 10.3390/s23062982
pmc: PMC10054495
pii:
doi:

Substances chimiques

Elastomers 0
Silicone Elastomers 0

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Références

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Auteurs

Narrendar RaviChandran (N)

Medical Devices and Technologies Group, Department of Mechanical and Mechatronics Engineering, The University of Auckland, Auckland 1010, New Zealand.
Singapore Eye Research Institute, Singapore 169856, Singapore.

Mei Ying Teo (MY)

Smart Materials and Microtechnologies Group, Department of Mechanical and Mechatronics Engineering, The University of Auckland, Auckland 1010, New Zealand.

Andrew McDaid (A)

Medical Devices and Technologies Group, Department of Mechanical and Mechatronics Engineering, The University of Auckland, Auckland 1010, New Zealand.

Kean Aw (K)

Smart Materials and Microtechnologies Group, Department of Mechanical and Mechatronics Engineering, The University of Auckland, Auckland 1010, New Zealand.

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Classifications MeSH