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Wearable Liquid Metal Composite with Skin-Adhesive Chitosan–Alginate–Chitosan Hydrogel for Stable Electromyogram Signal Monitoring

In wearable bioelectronics, various studies have focused on enhancing prosthetic control accuracy by improving the quality of physiological signals. The fabrication of conductive composites through the addition of metal fillers is one way to achieve stretchability, conductivity, and biocompatibility...

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Detalles Bibliográficos
Autores principales: Kim, Jaehyon, Kim, Yewon, Lee, Jaebeom, Shin, Mikyung, Son, Donghee
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10536051/
https://www.ncbi.nlm.nih.gov/pubmed/37765548
http://dx.doi.org/10.3390/polym15183692
Descripción
Sumario:In wearable bioelectronics, various studies have focused on enhancing prosthetic control accuracy by improving the quality of physiological signals. The fabrication of conductive composites through the addition of metal fillers is one way to achieve stretchability, conductivity, and biocompatibility. However, it is difficult to measure stable biological signals using these soft electronics during physical activities because of the slipping issues of the devices, which results in the inaccurate placement of the device at the target part of the body. To address these limitations, it is necessary to reduce the stiffness of the conductive materials and enhance the adhesion between the device and the skin. In this study, we measured the electromyography (EMG) signals by applying a three-layered hydrogel structure composed of chitosan–alginate–chitosan (CAC) to a stretchable electrode fabricated using a composite of styrene–ethylene–butylene–styrene and eutectic gallium-indium. We observed stable adhesion of the CAC hydrogel to the skin, which aided in keeping the electrode attached to the skin during the subject movement. Finally, we fabricated a multichannel array of CAC-coated composite electrodes (CACCE) to demonstrate the accurate classification of the EMG signals based on hand movements and channel placement, which was followed by the movement of the robot arm.