Deploying Partially Cross-Linked Elastomers to Optimize Adhesion for Long-Term Surface Electromyography Electrodes
Journal article, 2025

Electrophysiological signals generated during daily activities are essential for monitoring and diagnosing various health conditions. Traditionally, Ag/AgCl electrodes with conductive gels have been used to capture these signals, recording them as electrocardiogram (ECG) and electromyogram (EMG). However, gelled electrodes glued to the skin presents challenges related to placement and are uncomfortable to wear for extended recordings. Recent studies have made significant advancements in dry electrodes for electrophysiological signals, mainly focusing on ECG applications with less emphasis on surface EMG (sEMG). To address this gap, this study introduces a novel set of skin-friendly electrodes made from a blend of conductive carbon black (CB) and partially cross-linked Ecoflex substrates. By varying the proportions of Ecoflex components A and B, a balance between adequate adhesion and electromechanical properties for good skin contact and long-term usabi is achieved, owing to the formation of silanol bonds. The CB-Ecoflex electrodes have been tested through over 50 wash cycles and 100 peel-offs, demonstrating strong durability and use resilience. Additionally, they maintain good recording conditions for 48 h and when sweat and oil are introduced on the skin. These electrodes consistently deliver reliable performance in 48-h continuous sEMG recordings, making them suitable for long-term applications.

surface electromyography

ecoflex

skin-adhesive

dry electrodes

carbon black

Author

Yuqi Wang

University of Manchester

Shandong Laboratory of Advanced Materials and Green Manufacturing at Yantai

Xi Wang

University of Manchester

University of Borås

Leif Sandsjö

University of Borås

Chalmers, Industrial and Materials Science, Design and Human Factors

Xuqing Liu

Northwestern Polytechnical University

Shandong Laboratory of Advanced Materials and Green Manufacturing at Yantai

L. Guo

University of Borås

Advanced Materials Interfaces

2196-7350 (eISSN)

Vol. In Press

Subject Categories (SSIF 2025)

Other Medical Engineering

DOI

10.1002/admi.202400757

More information

Latest update

1/30/2025