4.8 Article

Multimodal Hydrogel-Based Respiratory Monitoring System for Diagnosing Obstructive Sleep Apnea Syndrome

期刊

ADVANCED FUNCTIONAL MATERIALS
卷 32, 期 40, 页码 -

出版社

WILEY-V C H VERLAG GMBH
DOI: 10.1002/adfm.202204686

关键词

cellulose hydrogels; hydrogel sensors; obstructive sleep apnea syndrome diagnosis; respiration monitoring; wearable electronics

资金

  1. National Natural Science Foundation of China [51903093]
  2. Natural Science Foundation of Guangdong Province [2020A1515010770]
  3. Project of Key Disciplines of Forestry Engineering of Bureau of Education of Guangzhou Municipality

向作者/读者索取更多资源

In this study, a multimodal hydrogel sensor with excellent comprehensive performance was developed for monitoring respiration and diagnosing obstructive sleep apnea syndrome (OSAS). The hydrogel sensor exhibited good mechanical properties and extreme temperature tolerance, enabling independent monitoring of mechanical variation and thermal change. This sensor provides a new and practical way for real-time respiratory monitoring and preventing the occurrence of sleep-related diseases.
Real-time monitoring of respiration is vital for human health, especially for forecasting the sleep-related diseases. A respiratory monitoring system with high accuracy, wearing comfort, portability, and environmental tolerance, is highly desirable, which however remains a big challenge. Here, a multimodal hydrogel sensor with excellent comprehensive performance is fabricated to monitor respiration and diagnose obstructive sleep apnea syndrome (OSAS). The synthetic cellulose-based hydrogel exhibits good mechanical properties and extreme temperature tolerance, ascribing to the synergistic effects between chemical cross-linking and multiple hydrogen bonding within the hydrogel network. The fabricated hydrogel sensor can independently monitor the mechanical variation and the thermal change via output signals of capacitance and resistance, respectively. These extraordinary properties of the hydrogel sensor enable the highly reliable and accurate monitoring of the respiratory events and diagnosis of OSAS. This work provides the new and practical way for real-time respiratory monitoring and preventing the occurrence of sleep-related diseases.

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