An Interfacial Gel Electrode Patch with Tunable Hydrogen Bond Network for Electromyographic Sensing and Discrimination

The sensitivity and fidelity of surface electromyography (sEMG) signal monitoring is critical for muscle status and fatigue assessment, prosthetic control, and gesture recognition. However, the incompatible skin-electrode interface and complex electrophysiological environment restrict the sensitive acquisition and accurate analysis of sEMG signals. Focused on the impedance of the skin-electrode interface issue, we developed an interfacial gel electrode patch with a tunable hydrogen bond network to simultaneously achieve a conformal interface, suitable adhesion, and high conductivity for sEMG signal monitoring. By exploiting hydroxyethylidene diphosphonic acid (HEDP) and 2-hydroxyphosphono-acetic acid (HPAA) as hydrogen bonding regulators were introduced into the polyvinyl alcohol (PVA)-based hydrogel network to regulate the hydrogen bond cross-linking network. As a result, the balance of elastic modulus, adhesion, and electrical conductivity of PVA-HEDP-HPAA (PHH) hydrogel are achieved. The reliable electrode-skin interface is manipulated to achieve conformal contact by matching the elastic modulus, reducing the gap of electrode-skin interface by adhesion, and promoting ion and electron conduction by electrical conductivity. The PHH electrode patches exhibit a lower interfacial impedance (12.56 kΩ) and a signal-to-noise ratio of 38.09 ± 1.28 dB for accurate analysis of muscle strength and evaluation of the fatigue state. With the assistance of the artificial neural network algorithm, seven gestures can be recognized with 100% prediction accuracy. The interfacial gel electrode patch contributes a bio-matching electrophysiological platform for prosthetic control, human-machine interaction, and clinical or athletic auxiliary monitoring.