Medical-grade development of flexible respiratory sensing technology: Pathways for medical physics implementation and clinical pulmonary function data validation
The rapid monitoring devices, but there are still challenges in achieving medical-grade accuracy in quantitative pulmonary function assessment. This study integrates water molecule-responsive flexible sensing technology, wearable devices, and cloud-based intelligent analysis platform to develop the first medical-grade flexible respiratory sensing system (SFMS). By utilizing the synergistic effect of bionic microcavity differential pressure sensing and humidity-sensitive interfaces, combined with a pressure difference-flux dynamic model, the system can simultaneously resolve peak expiratory flow (PEF) and forced vital capacity (FVC), accurately obtaining core pulmonary function indicators such as FEV<sub>1</sub>/FVC. Clinical validation of 454 cases demonstrates high consistency with gold-standard spirometry (intraclass correlation coefficient [ICC] = 0.93–0.97), with a sensitivity of 89.7% and specificity of 92.3% in differentiating chronic obstructive pulmonary disease (COPD) from asthma. Technologically, this work pioneers a medical-grade flexible sensor for quantitative pulmonary testing, and eliminates dependence on specialized operators through an embedded edge computing architecture that supports real-time cloud data interaction. The system establishes disease-specific profiles through multi-parametric physiological correlation analysis. Practically, its low cost, portability, and user-friendly operation facilitate seamless integration into primary healthcare and home health management, providing technical tools for hierarchical diagnosis and treatment of chronic respiratory diseases. Aligned with WHO's Respiratory Health Action Plan, this innovation enables universal monitoring to advance early screening and long-term disease management. As this innovation possesses significant clinical translation potential, it provides a groundbreaking solution for building a comprehensive prevention and control framework for respiratory diseases.
Authors
- Xie Baosong
- Liheng Yang (ORCID: https://orcid.org/0000-0001-6842-086X)
- Keyi Li (ORCID: https://orcid.org/0009-0004-2712-2208)
- Yang Yingqi
- Lin Guiyang
- Lin Guihua
- Zheng Guanying
- Cui Lina
Publication Details
- Journal
- Acta Physica Sinica
- Published
- 2025-01-01
- DOI
- https://doi.org/10.7498/aps.74.20250433
- Citations
- 1
- Primary Topic
- Advanced Sensor and Energy Harvesting Materials
- Type
- article
- Field-Weighted Citation Impact
- 0.67