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Development and Evaluation of 3D-Printed Dry Microneedle Electrodes for Surface Electromyography
Date Issued
2020-10
Date Available
2021-04-14T11:29:52Z
Abstract
Surface electromyography (sEMG) allows for direct measurement of electrical muscle activity with use in fundamental research and many applications in health and sport. However, conventional surface electrode technology can suffer from poor signal quality, requires careful skin preparation, and is commonly not suited for long-term recording. These drawbacks have challenged translation of sEMG to clinical applications. In this paper, dry 3D-printed microneedle electrodes (MNEs) are proposed to overcome some of the limitations of conventional electrodes. Employing a direct-metal-laser-sintering (DMLS) 3D printing process, a two-step fabrication method is developed to produce sharp medical-grade stainless steel MNEs. The developed MNEs are compared to needle-free versions and to standard wet Ag/AgCl electrodes. Functional testing is conducted to analyze the electrode–skin impedance in healthy human volunteers and sEMG data are recorded from the biceps brachii muscle. Results show that microneedle electrodes display a greatly reduced (≈63%) electrode–skin contact impedance with respect to needle-free electrodes and record sEMG at a signal-to-noise ratio comparable to clinical-grade wet Ag/AgCl electrodes over a period of up to 6 h. Overall, a fabrication method and electrode type are presented which yield high-quality sEMG signals when evaluated in humans, highlighting the potential of MNEs as a platform for biosignal recording.
Sponsorship
European Commission Horizon 2020
Irish Research Council
Other Sponsorship
National University of Ireland Travel Studentship
Type of Material
Journal Article
Publisher
Wiley
Journal
Advanced Materials Technologies
Volume
5
Issue
10
Copyright (Published Version)
2020 Wiley
Language
English
Status of Item
Peer reviewed
ISSN
2365-709X
This item is made available under a Creative Commons License
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Name
3D Printed Dry MN Electrodes for Surface EMG_ final.docx
Size
5.94 MB
Format
Unknown
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