ACS Sens. 2026 Oct 16. doi: 10.1021/acssensors.6c01120. Online ahead of print.
ABSTRACT
Respiration serves as a critical physiological indicator, with abnormalities in its patterns and rates closely associated with respiratory and cardiovascular diseases, particularly sleep apnea syndrome (SAS). Wearable abdomen-mounted respiratory sensors offer a promising solution for long-term, comfortable, and noninvasive monitoring; however, the subtle mechanical deformations induced by respiration impose stringent requirements on sensor sensitivity and stability. Here, we report a versatile flexible strain sensor designed for comprehensive respiratory monitoring across diverse scenarios. This sensor adopts an all-fibrous and fully electrospun architecture composed of silver nanowires (AgNWs), graphene (GR), and thermoplastic polyurethane (TPU), which is fabricated through a dual-channel hybrid electrospinning strategy. The sensor exhibits dual-regime sensitivity. It delivers a stable and linear gauge factor (GF) of 133.3 in the low-strain range (0-40%), which is highly suitable for high-fidelity daily respiration monitoring. Meanwhile, a high GF is achieved in the high-strain region (>40%), enabling the accurate capture of vigorous physiological behaviors such as severe coughing and strenuous exercise. This multi-range sensitivity endows the sensor with high precision for subtle biological signals and reliable responsiveness to intense physiological events, along with outstanding flexibility, mechanical durability, and wearable comfort. Benefiting from the highly interpenetrated three-dimensional conductive network, the sensor enables precise detection of minute respiratory-induced deformations. Furthermore, an integrated respiratory monitoring system is developed, allowing accurate identification of different respiratory states through feature signal extraction and analysis. This work provides an efficient and scalable strategy for constructing high-performance dual-regime flexible strain sensors and demonstrates their strong potential for wearable respiratory health monitoring applications.
PMID:42887889 | DOI:10.1021/acssensors.6c01120