Expiratory Flow and Volume Estimation Through Thermal-<inline-formula><tex-math notation=$CO_{2}$ Imaging" data-sr-only="">
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Transue, Shane | - |
dc.contributor.author | Min, Se Dong | - |
dc.contributor.author | Choi, Min-Hyung | - |
dc.date.accessioned | 2023-03-09T07:40:55Z | - |
dc.date.available | 2023-03-09T07:40:55Z | - |
dc.date.issued | 2023-07 | - |
dc.identifier.issn | 0018-9294 | - |
dc.identifier.issn | 1558-2531 | - |
dc.identifier.uri | https://scholarworks.bwise.kr/sch/handle/2021.sw.sch/22165 | - |
dc.description.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. | - |
dc.format.extent | 11 | - |
dc.publisher | Institute of Electrical and Electronics Engineers | - |
dc.title | Expiratory Flow and Volume Estimation Through Thermal-<inline-formula><tex-math notation=$CO_{2}$ Imaging" data-sr-only=""> | - |
dc.type | Article | - |
dc.publisher.location | 미국 | - |
dc.identifier.doi | 10.1109/TBME.2023.3236597 | - |
dc.identifier.scopusid | 2-s2.0-85147259904 | - |
dc.identifier.wosid | 001016857400012 | - |
dc.identifier.bibliographicCitation | IEEE Transactions on Biomedical Engineering, v.70, no.7, pp 2111 - 2121 | - |
dc.citation.title | IEEE Transactions on Biomedical Engineering | - |
dc.citation.volume | 70 | - |
dc.citation.number | 7 | - |
dc.citation.startPage | 2111 | - |
dc.citation.endPage | 2121 | - |
dc.type.docType | Article | - |
dc.description.isOpenAccess | N | - |
dc.description.journalRegisteredClass | scie | - |
dc.description.journalRegisteredClass | scopus | - |
dc.relation.journalResearchArea | Engineering | - |
dc.relation.journalWebOfScienceCategory | Engineering, Biomedical | - |
dc.subject.keywordAuthor | Exhale visualization | - |
dc.subject.keywordAuthor | CO2 exhale flow | - |
dc.subject.keywordAuthor | non-contact exhale analysis | - |
dc.subject.keywordAuthor | quantitative exhale analysis | - |
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