Noninvasive Respiratory Monitoring Through Correlation of Thoracoabdominal Movements and Pressure Fluctuations
This study presents a novel, noninvasive system that quantifies thoracoabdominal respiratory movements and correlates them with back pressure fluctuations, advancing respiratory monitoring. A key contribution is the development of a method to measure the 3-D movements of the chest and abdomen using a 3-D motion capture system, enabling high-precision analysis of respiratory dynamics. In addition, another significant contribution of this work is the development of a novel correlation model that integrates the thoracoabdominal motion data with back pressure fluctuations recorded by a tactile sensor array. This integration represents a critical departure from previous research, which often examines these parameters in isolation. By linking back pressure fluctuations to respiratory displacements, our method facilitates noncontact, unobtrusive respiratory monitoring, offering a practical and patient friendly alternative to traditional contact-based techniques such as respiratory inductance plethysmography (RIP). Furthermore, this study identifies optimal regions for pressure monitoring, which enhances the system’s precision and usability for long-term monitoring in clinical and home environments. This step addresses a critical gap in the current literature, where practical implementation strategies are often overlooked. The results reveal a clear correlation between pressure fluctuations and respiratory movements, forming the basis for a model that can predict respiratory states. This system provides significant potential for practical application, offering a promising solution for reliable, unobtrusive respiratory monitoring in both clinical and home settings.
Authors
- Song Yao (ORCID: https://orcid.org/0000-0002-9474-7281)
- Shijie Guo (ORCID: https://orcid.org/0000-0002-1335-2852)
- Bowen Liang (ORCID: https://orcid.org/0000-0002-1452-4222)
Institutions
- Hebei University of Technology (CN)
Publication Details
- Journal
- IEEE Sensors Journal
- Published
- 2025-02-26
- DOI
- https://doi.org/10.1109/jsen.2025.3543178
- Primary Topic
- Non-Invasive Vital Sign Monitoring
- Type
- article
- Field-Weighted Citation Impact
- 0.00