Scalable Fabrication of Uniform Fast-Response Humidity Field Sensing Array for Respiration Recognition and Contactless Human-Machine Interaction

In the wake of the COVID-19 pandemic, there is an increased demand for humidity sensors that can accurately detect targets without direct contact, driving advancements in contactless human-machine interaction (HMI) and non-invasive medical diagnostics. However, it is difficult for traditional individual sensors to accurately acquire humidity field information for reliable HMI. Here, an ionogel film-based flexible and fast-response humidity field sensing array is developed via a scalable, efficient, and modified spin-coating-based fabrication strategy for accurate detection of humidity distribution. By optimizing the structure and constitution of the hydrophobic ionogel films, the sensors display ultrafast response and recovery time (0.65/0.85 s), a broad detection range (11-98% RH), long-term stability (120 days), excellent repeatability, flexibility, and environmental tolerances. Thanks to the one-time scalable fabrication, the sensing units in the array exhibit superior uniformity, as the device-to-device deviation is reduced to one-ninth compared to traditional multi-batch fabrication methods. With the aid of machine learning algorithms, this humidity sensing array realizes not only the accurate identification of various subtle breath abnormalities (e.g., oral breathing, apnea, left and right nasal congestions) by conformally attaching to wearable masks, but also the precise contactless HMI applications (e.g., anti-interference gesture recognition and wireless control of intelligent executive terminals).