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dc.contributor.authorLee, Chien-Chingen_US
dc.contributor.authorChuang, Chia-Chunen_US
dc.contributor.authorLai, Bo-Chengen_US
dc.contributor.authorHuang, Yi-Chiaen_US
dc.contributor.authorChen, Jen-Yinen_US
dc.contributor.authorLin, Bor-Shyhen_US
dc.date.accessioned2020-07-01T05:22:12Z-
dc.date.available2020-07-01T05:22:12Z-
dc.date.issued2020-04-01en_US
dc.identifier.urihttp://dx.doi.org/10.3390/s20071891en_US
dc.identifier.urihttp://hdl.handle.net/11536/154614-
dc.description.abstractIn clinical practice, the catheter has to be placed at an accurate position during anesthesia administration. However, effectively guiding the catheter to the accurate position in deeper tissues can be difficult for an inexperienced practitioner. We aimed to address the current issues associated with catheter placement using a novel smart assistance system for blood vessel catheter placement. We used a hollow introducer needle embedded with dual wavelength (690 and 850 nm) optical fibers to advance the tip into the subclavian vessels in anesthetized piglets. The results showed average optical density changes, and the difference between the absorption spectra and hemoglobin concentrations of different tissue components effectively identified different tissues (p < 0.05). The radial basis function neural network (RBFNN) technique was applied to distinguish tissue components (the F-measure value and accuracy were 93.02% and 94%, respectively). Finally, animal experiments were designed to validate the performance of the proposed system. Using this system based on oximetry, we easily navigated the needle tip to the target vessel. Based on the experimental results, the proposed system could effectively distinguish different tissue layers of the animals.en_US
dc.language.isoen_USen_US
dc.subjectcatheter placementen_US
dc.subjectanesthesiaen_US
dc.subjectabsorption spectraen_US
dc.subjecttissue componentsen_US
dc.subjectoptical density changeen_US
dc.subjecthemoglobin concentrationen_US
dc.titleA Novel Smart Assistance System for Blood Vessel Approaching: A Technical Report Based on Oximetryen_US
dc.typeArticleen_US
dc.identifier.doi10.3390/s20071891en_US
dc.identifier.journalSENSORSen_US
dc.citation.volume20en_US
dc.citation.issue7en_US
dc.citation.spage0en_US
dc.citation.epage0en_US
dc.contributor.department影像與生醫光電研究所zh_TW
dc.contributor.departmentInstitute of Imaging and Biomedical Photonicsen_US
dc.identifier.wosnumberWOS:000537110500087en_US
dc.citation.woscount0en_US
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