Expiratory Flow and Volume Estimation Through Thermal-<inline-formula><tex-math notation=$CO_{2}$ Imaging" data-sr-only="">
- Authors
- Transue, Shane; Min, Se Dong; Choi, Min-Hyung
- Issue Date
- Jul-2023
- Publisher
- Institute of Electrical and Electronics Engineers
- Keywords
- Exhale visualization; CO2 exhale flow; non-contact exhale analysis; quantitative exhale analysis
- Citation
- IEEE Transactions on Biomedical Engineering, v.70, no.7, pp 2111 - 2121
- Pages
- 11
- Journal Title
- IEEE Transactions on Biomedical Engineering
- Volume
- 70
- Number
- 7
- Start Page
- 2111
- End Page
- 2121
- URI
- https://scholarworks.bwise.kr/sch/handle/2021.sw.sch/22165
- DOI
- 10.1109/TBME.2023.3236597
- ISSN
- 0018-9294
1558-2531
- Abstract
- Objective: In this work, we introduce a quantitative non-contact respiratory evaluation method for finegrain exhale flow and volume estimation through Thermal-CO2 imaging. This provides a form of respiratory analysis that is driven by visual analytics of exhale behaviors, creating quantitative metrics for exhale flow and volume modeled as open-air turbulent flows. This approach introduces a novel form of effort-independent pulmonary evaluation enabling behavioral analysis of natural exhale behaviors. Methods: CO2 filtered infrared visualizations of exhale behaviors are used to obtain breathing rate, volumetric flow estimations (L/s) and per-exhale volume (L) estimations. We conduct experiments validating visual flow analysis to formulate two behavioral Long-Short-Term-Memory (LSTM) estimation models generated from visualized exhale flows targeting per-subject and cross-subject training datasets. Results: Experimental model data generated for training on our per-individual recurrent estimation model provide an overall flow correlation estimate correlation of R-2 = 0.912 and volume in-the-wild accuracy of 75.65-94.44%. Our cross-patient model extends generality to unseen exhale behaviors, obtaining an overall correlation of R-2 = 0.804 and in-the-wild volume accuracy of 62.32-94.22%. Conclusion: This method provides non-contact flow and volume estimation through filtered CO2 imaging, enabling effort-independent analysis of natural breathing behaviors. Significance: Effort-independent evaluation of exhale flow and volume broadens capabilities in pulmonological assessment and long-term non-contact respiratory analysis.
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Collections - College of Medical Sciences > Department of Medical IT Engineering > 1. Journal Articles
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