Recent advances in personalized sleep medicine and home-based health monitoring have grown rapidly, yet progress remains limited by the lack of comfortable, reliable, and durable sensors for long-term respiration tracking. Here, we present a flexible humidity sensor fabricated through a freeze-drying-assisted direct-ink-writing (DIW) 3D printing strategy. This sensor is constructed from a poly(vinyl alcohol)/nanocellulose/graphene/multiwalled carbon nanotubes (PVA/CNF/Gr/MWCNTs, PCGM) composite aerogel, with a hierarchically porous conductive architecture. This aerogel was stabilized by a biocompatible PVA matrix reinforced by nanocellulose, while graphene ensures high conductivity, and it was further enhanced by carbon nanotubes in the 3D structure. Moreover, the considerable hydrogen bonding and π-π conjugation within this hybrid material contribute to exceptional interfacial stability, water-adsorption capacity, and electrical conductivity, resulting in a remarkable humidity-sensing performance with high sensitivity, fast response/recovery times, and excellent stability across a broad humidity range. Remarkably, the sensor can accurately differentiate diverse sleep postures and respiratory patterns, including normal, snoring, and coughing. Furthermore, we further enabled a 600-sample-trained deep convolutional neural network and achieved a high-precision pattern recognition, with 100% accuracy in respiratory state classification and 97% accuracy for spoken-word recognition classification. Our work provides an integrated strategy for next-generation high-performance wearable health monitoring and human-machine interaction systems.
Chen et al. (2026) studied this question.