Carboxymethyl Cellulose/Sodium Lignosulfonate Composite Hydrogel with Toughness, Adhesiveness, and Antibacterial Properties for Monitoring Respiration in Heart Failure Patients.
Journal:
ACS applied materials & interfaces
Published Date:
Feb 9, 2026
Abstract
The advancement of personalized medicine is increasingly reliant on wearable health monitoring technologies. While hydrogels offer great promise for skin-integrated sensors due to their biocompatibility, flexibility, and conductivity, developing materials that simultaneously possess robust mechanical properties, reliable adhesion, and antimicrobial efficacy remains a challenge. To address the critical need for monitoring nocturnal respiratory abnormalities in heart failure patients, we have successfully developed a hydrogel composed of acrylic acid (AA), carboxymethyl cellulose (CMC), double-bond-modified sodium lignosulfonate (DLS), and polydopamine-modified nanohydroxyapatite loaded with silver particles (PDA-nHAP@Ag). The developed hydrogel sensor exhibits a suite of superior properties, including high conductivity (1.1 S/m), excellent mechanical strength (0.41 MPa tensile stress, 1295% strain), and high sensitivity (gauge factor of 5.58), enabling stable skin adhesion. It demonstrated outstanding biocompatibility (>98% cell viability) and potent antibacterial activity (97% inhibition against both E. coli and S. aureus). Furthermore, the sensor showed remarkable durability, maintaining signal stability over 2500 cycles in tests monitoring joint bending and laryngeal movements. In practical application, the system captured electrocardiogram signals with superior waveform clarity compared to commercial electrodes. Most importantly, through multichannel signal analysis, it achieved precise classification of breathing patterns (fast, normal, slow) in heart failure patients with an accuracy of 97.8%. This work overcomes the limitations of conventional single-function systems by integrating electrophysiological monitoring, motion sensing, and respiratory analysis, providing a viable pathway toward next-generation intelligent health monitoring platforms.
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