Wearable Chemical Nanosensors for Real-time Human Performance Monitoring and Workload Assessment

Abstract

Wearable sensors present a breakthrough in human factors engineering and ergonomics by offering a non-invasive alternative to conventional performance monitoring methods, enabling real-time, continuous assessment of worker physiological states and cognitive workload. The capability to continuously analyze and predict dynamic changes in various biomarkers in easily accessible body fluids (e.g., sweat) would significantly enhance workplace safety, optimize human-system integration, and improve overall operational efficiency in industrial settings. We develop novel wearable biosensors utilizing nanoscale semiconductors, specifically atomically thin tellurene, capable of detecting multiple biomarkers in sweat that correlate with mental workload and fatigue. The unique p-type characteristics of tellurene, combined with our ergonomic wearable design, enable sensitive and selective longitudinal monitoring of human performance metrics. The sensor facilitates real-time workforce analytics and predictive modeling of human performance variables by providing continuous, multi-analyte data streams. Integrating physiological monitoring with digital twin simulation creates new opportunities for workplace safety enhancement, process optimization, and data-driven decision making in industrial engineering applications.