A flexible multimodal sensor with intrinsic signal decoupling for wearable respiratory monitoring

Abstract

Continuous, noninvasive monitoring of multiple physiological signals derived from exhaled breath (EB), is critical for managing respiratory diseases such as asthma and chronic obstructive pulmonary disease (COPD). However, current wearable sensors face fundamental limitations, including signal cross-talk, inadequate multi-parameter detection, and poor mechanical stability. Here, we introduce a flexible multimodal sensor with intrinsic device-level signal decoupling for comprehensive wearable respiratory monitoring. The sensor features a compact vertically stacked architecture that integrates pressure, temperature, and nitric oxide (NO) modules, each isolating signals through orthogonal transduction mechanisms: piezoresistive current, junction potential, and chemiresistive response. The pressure module, based on aerosol-jet-printed MXene (Ti₃C₂T_x)/hydroxyethyl cellulose (HEC) films with engineered gradient microstructures, achieves exceptional sensitivity of 2.75 kPa^-1 over a broad linear range up to 160 kPa with high linearity (R² > 0.99). Simultaneously, the temperature module, constructed from an MXene/EtDAB·4PbI₂ Schottky-like junction, delivers a remarkable sensitivity of 6.5 mV·K^-1. For gas detection, an electrochemically exfoliated graphene (EEG)/Co₃(HITP)₂ hybrid enables an NO detection limit down to 25 ppb under ambient conditions. In addition, we integrated the sensor into a smart facemask to enable real-time monitoring of respiratory patterns and to distinguish normal and high-fractional exhaled nitric oxide simulated EB, illustrating the potential of this technology for personalized healthcare.

Keywords

Multimodal sensor / self-decoupling / respiration monitoring / flexible sensor / MXene / metal–organic framework

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