A virtual reality based simulator for learning nasogastric tube placement.
Identifieur interne : 000B41 ( Main/Merge ); précédent : 000B40; suivant : 000B42A virtual reality based simulator for learning nasogastric tube placement.
Auteurs : Kup-Sze Choi [République populaire de Chine] ; Xuejian He [République populaire de Chine] ; Vico Chung-Lim Chiang [République populaire de Chine] ; Zhaohong Deng [République populaire de Chine]Source :
- Computers in biology and medicine [ 1879-0534 ] ; 2015.
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Abstract
Nasogastric tube (NGT) placement is a common clinical procedure where a plastic tube is inserted into the stomach through the nostril for feeding or drainage. However, the placement is a blind process in which the tube may be mistakenly inserted into other locations, leading to unexpected complications or fatal incidents. The placement techniques are conventionally acquired by practising on unrealistic rubber mannequins or on humans. In this paper, a virtual reality based training simulation system is proposed to facilitate the training of NGT placement. It focuses on the simulation of tube insertion and the rendering of the feedback forces with a haptic device. A hybrid force model is developed to compute the forces analytically or numerically under different conditions, including the situations when the patient is swallowing or when the tube is buckled at the nostril. To ensure real-time interactive simulations, an offline simulation approach is adopted to obtain the relationship between the insertion depth and insertion force using a non-linear finite element method. The offline dataset is then used to generate real-time feedback forces by interpolation. The virtual training process is logged quantitatively with metrics that can be used for assessing objective performance and tracking progress. The system has been evaluated by nursing professionals. They found that the haptic feeling produced by the simulated forces is similar to their experience during real NGT insertion. The proposed system provides a new educational tool to enhance conventional training in NGT placement.
DOI: 10.1016/j.compbiomed.2014.12.006
PubMed: 25546468
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Electronic address: hskschoi@polyu.edu.hk.</nlm:affiliation><country xml:lang="fr">République populaire de Chine</country><wicri:regionArea>School of Nursing, The Hong Kong Polytechnic University, Hong Kong, China; Centre for Smart Health, School of Nursing, The Hong Kong Polytechnic University, Hong Kong, China; Interdisciplinary Division of Biomedical Engineering, The Hong Kong Polytechnic University, Hong Kong</wicri:regionArea><wicri:noRegion>Hong Kong</wicri:noRegion></affiliation></author><author><name sortKey="He, Xuejian" sort="He, Xuejian" uniqKey="He X" first="Xuejian" last="He">Xuejian He</name><affiliation wicri:level="1"><nlm:affiliation>Centre for Smart Health, School of Nursing, The Hong Kong Polytechnic University, Hong Kong, China.</nlm:affiliation><country xml:lang="fr">République populaire de Chine</country><wicri:regionArea>Centre for Smart Health, School of Nursing, The Hong Kong Polytechnic University, Hong Kong</wicri:regionArea><wicri:noRegion>Hong Kong</wicri:noRegion></affiliation></author><author><name sortKey="Chiang, Vico Chung Lim" sort="Chiang, Vico Chung Lim" uniqKey="Chiang V" first="Vico Chung-Lim" last="Chiang">Vico Chung-Lim Chiang</name><affiliation wicri:level="1"><nlm:affiliation>School of Nursing, The Hong Kong Polytechnic University, Hong Kong, China.</nlm:affiliation><country xml:lang="fr">République populaire de Chine</country><wicri:regionArea>School of Nursing, The Hong Kong Polytechnic University, Hong Kong</wicri:regionArea><wicri:noRegion>Hong Kong</wicri:noRegion></affiliation></author><author><name sortKey="Deng, Zhaohong" sort="Deng, Zhaohong" uniqKey="Deng Z" first="Zhaohong" last="Deng">Zhaohong Deng</name><affiliation wicri:level="1"><nlm:affiliation>School of Digital Media, Jiangnan University, Wuxi, China.</nlm:affiliation><country xml:lang="fr">République populaire de Chine</country><wicri:regionArea>School of Digital Media, Jiangnan University, Wuxi</wicri:regionArea><wicri:noRegion>Wuxi</wicri:noRegion></affiliation></author></titleStmt><publicationStmt><idno type="wicri:source">PubMed</idno><date when="2015">2015</date><idno type="RBID">pubmed:25546468</idno><idno type="pmid">25546468</idno><idno type="doi">10.1016/j.compbiomed.2014.12.006</idno><idno type="wicri:Area/PubMed/Corpus">000456</idno><idno type="wicri:Area/PubMed/Curation">000456</idno><idno type="wicri:Area/PubMed/Checkpoint">000440</idno><idno type="wicri:Area/Ncbi/Merge">003580</idno><idno type="wicri:Area/Ncbi/Curation">003580</idno><idno type="wicri:Area/Ncbi/Checkpoint">003580</idno><idno type="wicri:Area/Main/Merge">000B41</idno></publicationStmt><sourceDesc><biblStruct><analytic><title xml:lang="en">A virtual reality based simulator for learning nasogastric tube placement.</title><author><name sortKey="Choi, Kup Sze" sort="Choi, Kup Sze" uniqKey="Choi K" first="Kup-Sze" last="Choi">Kup-Sze Choi</name><affiliation wicri:level="1"><nlm:affiliation>School of Nursing, The Hong Kong Polytechnic University, Hong Kong, China; Centre for Smart Health, School of Nursing, The Hong Kong Polytechnic University, Hong Kong, China; Interdisciplinary Division of Biomedical Engineering, The Hong Kong Polytechnic University, Hong Kong, China. 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However, the placement is a blind process in which the tube may be mistakenly inserted into other locations, leading to unexpected complications or fatal incidents. The placement techniques are conventionally acquired by practising on unrealistic rubber mannequins or on humans. In this paper, a virtual reality based training simulation system is proposed to facilitate the training of NGT placement. It focuses on the simulation of tube insertion and the rendering of the feedback forces with a haptic device. A hybrid force model is developed to compute the forces analytically or numerically under different conditions, including the situations when the patient is swallowing or when the tube is buckled at the nostril. To ensure real-time interactive simulations, an offline simulation approach is adopted to obtain the relationship between the insertion depth and insertion force using a non-linear finite element method. The offline dataset is then used to generate real-time feedback forces by interpolation. The virtual training process is logged quantitatively with metrics that can be used for assessing objective performance and tracking progress. The system has been evaluated by nursing professionals. They found that the haptic feeling produced by the simulated forces is similar to their experience during real NGT insertion. The proposed system provides a new educational tool to enhance conventional training in NGT placement.</div></front></TEI></record>Pour manipuler ce document sous Unix (Dilib)
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