Self-Adhesive Epidermal Bioelectrodes for Long-Term Electrophysiological Monitoring and Emotion Recognition

With the development of wearable health monitoring technology, long-term electrophysiological monitoring has shown significant promise in medical research and clinical applications. Facial electromyography (fEMG), as a pivotal tool for emotion recognition, is increasingly recognized for its value in the realm of affective analysis. However, the application of conventional electrodes for long-term monitoring is limited by comfort and signal quality constraints. To address these limitations, this paper presents a composite electrode film based on multi-walled carbon nanotubes (MWCNTs), poly(methyl vinyl ether-alt-maleic acid) (PMVEMA), and glycerol. The electrode exhibits excellent biocompatibility, self-adhesion, and conductivity, allowing stable monitoring of physiological electrical signals over long periods of time without the use of conductive gels. Further use of the film to detect facial EMG signals and run machine learning algorithms for emotion recognition demonstrates its potential for psychological research and clinical applications.