A Complementary Dual-Mode Ion-Electron Conductive Hydrogel Enables Sustained Conductivity for Prolonged Electroencephalogram Recording.

Conductive gel interface materials are widely employed as reliable agents for electroencephalogram (EEG) recording. However, prolonged EEG recording poses challenges in maintaining stable and efficient capture due to inevitable evaporation in hydrogels, which restricts sustained high conductivity. This study introduces a novel ion-electron dual-mode conductive hydrogel synthesized through a cost-effective and streamlined process. By embedding graphite nanoparticles into ionic hyaluronic acid (HAGN), the hydrogel maintains higher conductivity for over 72 h, outperforming commercial gels. Additionally, it exhibits superior low skin contact impedance, considerable electrochemical capability, and excellent tensile and adhesion performance in both dry and wet conditions. The biocompatibility of the HAGN hydrogel, verified through in vitro cell viability assays and in vivo skin irritation tests, underscores its suitability for prolonged skin contact without eliciting adverse reactions. Furthermore, in vivo EEG tests confirm the HAGN hydrogel's capability to provide high-fidelity signal acquisition across multiple EEG protocols. The HAGN hydrogel proves to be an effective interface for prolonged high-quality EEG recording, facilitating high-performance capture and classification of evoked potentials, thereby providing a reliable conductive medium for EEG-based systems.

Advancements in Fatigue Detection: Integrating fNIRS and Non-Voluntary Attention Brain Function Experiments.

BACKGROUND: Driving fatigue is a significant concern in contemporary society, contributing to a considerable number of traffic accidents annually. This study explores novel methods for fatigue detection, aiming to enhance driving safety. METHODS: This study utilizes electroencephalography (EEG) and functional near-infrared spectroscopy (fNIRS) to monitor driver fatigue during simulated driving experiments lasting up to 7 h. RESULTS: Analysis reveals a significant correlation between behavioral data and hemodynamic changes in the prefrontal lobe, particularly around the 4 h mark, indicating a critical period for driver performance decline. Despite a small participant cohort, the study's outcomes align closely with established fatigue standards for drivers. CONCLUSIONS: By integrating fNIRS into non-voluntary attention brain function experiments, this research demonstrates promising efficacy in accurately detecting driving fatigue. These findings offer insights into fatigue dynamics and have implications for shaping effective safety measures and policies in various industrial settings.