Λεπτομέρειες βιβλιογραφικής εγγραφής
| Τίτλος: |
Template-Based Respiratory Monitoring and Tidal Volume Estimation. |
| Συγγραφείς: |
Huy HV, Albert K, Ramachandran S, Jouvet P, Noumeir R |
| Πηγή: |
IEEE journal of biomedical and health informatics [IEEE J Biomed Health Inform] 2026 Aug; Vol. 30 (8), pp. 7093-7106. |
| Τύπος έκδοσης: |
Journal Article |
| Γλώσσα: |
English |
| Στοιχεία περιοδικού: |
Publisher: Institute of Electrical and Electronics Engineers Country of Publication: United States NLM ID: 101604520 Publication Model: Print Cited Medium: Internet ISSN: 2168-2208 (Electronic) Linking ISSN: 21682194 NLM ISO Abbreviation: IEEE J Biomed Health Inform Subsets: MEDLINE |
| Imprint Name(s): |
Original Publication: New York, NY : Institute of Electrical and Electronics Engineers, 2013- |
| Ιατρικοί όροι (MeSH): |
Tidal Volume*/physiology , Image Processing, Computer-Assisted*/methods, Monitoring, Physiologic/methods ; Respiratory Rate/physiology ; Humans ; Algorithms ; Male ; Female ; Adult |
| Περίληψη: |
Vision-based monitoring has gained attention as a non-invasive alternative to conventional contact-based methods in intensive care units (ICUs). While prior studies highlight its potential for respiratory monitoring, the approach remains nascent, with challenges such as heuristically defined respiratory-relevant regions. This lack of anatomically consistent definitions can undermine the reliability of volume estimation techniques. Typically, patient-specific calibration data are required to address this limitation, yet such data are frequently unavailable in practical settings. In this study, we introduce a novel method for modeling the torso region to enable precise respiratory monitoring and volume estimation. Using a Kinect camera, we capture the patient's body surface, which is then aligned and registered with a standardized human template for consistent segmentation of the respiration-relevant region. Subsequently, an efficient and accurate volume computation algorithm extracts respiratory parameters and monitors tidal volume. We validated our approach on a cohort of volunteers, benchmarking it against gold-standard spirometry and expert annotations. Overall, the proposed method achieves over 90% accuracy in tidal volume estimation and 95% accuracy in respiratory rate estimation, without relying on patient-specific calibration. These results demonstrate its robustness and suitability for ICU respiratory monitoring. |
| Entry Date(s): |
Date Created: 20251110 Date Completed: 20260805 Latest Revision: 20260806 |
| Update Code: |
20260806 |
| DOI: |
10.1109/JBHI.2025.3558821 |
| PMID: |
41212706 |
| Βάση Δεδομένων: |
MEDLINE |