An endotracheal intubation confirmation system based on carina image detection: a proof of concept.
In this paper, a novel system for automatic confirmation of endotracheal intubation is proposed. The system comprises a miniature CMOS sensor and electric wires attached to a rigid stylet. Video signals are continuously acquired and processed by the algorithm implemented on a PC/DSP. The system is b...
| Publicado en: | Medical & Biological Engineering & Computing Vol. 49; no. 1; pp. 75 - 84 |
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| Autores principales: | , |
| Formato: | research Journal Article |
| Publicado: |
Springer Nature
Jan2011
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=104569758&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 104569758 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 01400118 PO0 jtl: Medical & Biological Engineering & Computing issn: 01400118 maglogo: N pubinfo: dt: Jan2011 vid: 49 iid: 1 pid: 237 pub: Springer Nature place: New York, New York artinfo: ui: 104569758 NLM20878551 2010918992 10.1007/s11517-010-0680-4 NLM20878551 104569758 ppf: 75 ppct: 9 formats: fmt: @attributes: type: P tig: atl: An endotracheal intubation confirmation system based on carina image detection: a proof of concept. aug: au: Lederman D Lederman, Dror affil: Department of Radiology, University of Pittsburgh, Pittsburgh, PA 15213, USA sug: subj: Intubation, Intratracheal Methods Trachea Anatomy and Histology Algorithms Esophagus Foreign Bodies Diagnosis Foreign Bodies Etiology Human Intubation, Intratracheal Adverse Effects Models, Anatomic Videorecording ab: In this paper, a novel system for automatic confirmation of endotracheal intubation is proposed. The system comprises a miniature CMOS sensor and electric wires attached to a rigid stylet. Video signals are continuously acquired and processed by the algorithm implemented on a PC/DSP. The system is based on detection of the carina image as an anatomical landmark of correct tube positioning and it thus utilizes direct visual cues. Detection of the carina is performed based on unsupervised clustering, using a greedy-Gaussian mixture framework. The performance of the proposed system was initially evaluated using a mannequin model. A scientific prototype was assembled and used to perform repeated intubations on the model and collect a database of video signals which were processed off-line. The videos were categoried by a medical professional into carina, upper-trachea, and esophagus. An accuracy of 100% was achieved in discriminating between the carina and other anatomical structures including esophagus and upper-trachea. As an additional validation, the system was tested using a dataset of 231 video images recorded from five human subjects during intubation. The system correctly classified 120 out of 125 non-carina images (i.e. a sensitivity of 96.0%), and 100 out of 106 carina images (i.e. a specificity 94.3%). Using a 10th-order median filter, applied on the frame-based classification results, a 100% accuracy rate was obtained. pubtype: Academic Journal doctype: research Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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