Optical fiber technology enables smart needles for epidurals: an


Journal

Biomedical optics express
ISSN: 2156-7085
Titre abrégé: Biomed Opt Express
Pays: United States
ID NLM: 101540630

Informations de publication

Date de publication:
01 Mar 2019
Historique:
received: 14 05 2018
revised: 18 12 2018
accepted: 14 01 2019
entrez: 21 3 2019
pubmed: 21 3 2019
medline: 21 3 2019
Statut: epublish

Résumé

Nowadays, epidural space identification is made by using subjective and manual techniques characterized by failure rates up to 7%. In this work, we propose a fiber optic sensor technology based needle guidance system, that is directly inspired by the most common technique currently used for epidurals; through real-time strain measurements, the fiber Bragg grating integrated inside the needle lumen is able to effectively perceive the typical force drop occurring when the needle enters the epidural space. An

Identifiants

pubmed: 30891351
doi: 10.1364/BOE.10.001351
pii: 331554
pmc: PMC6420287
doi:

Types de publication

Journal Article

Langues

eng

Pagination

1351-1364

Déclaration de conflit d'intérêts

The authors declare that there are no conflicts of interest related to this article.

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Auteurs

Benito Carotenuto (B)

Optoelectronics Group, Engineering Department, University of Sannio, Benevento I-82100, Italy.

Armando Ricciardi (A)

Optoelectronics Group, Engineering Department, University of Sannio, Benevento I-82100, Italy.
aricciardi@unisannio.it.

Alberto Micco (A)

Optoelectronics Group, Engineering Department, University of Sannio, Benevento I-82100, Italy.

Ezio Amorizzo (E)

Pain Medicine Unit, Sant'Andrea Hospital, "Sapienza" University, Rome I-00189, Italy.

Marco Mercieri (M)

Pain Medicine Unit, Sant'Andrea Hospital, "Sapienza" University, Rome I-00189, Italy.

Antonello Cutolo (A)

Optoelectronics Group, Engineering Department, University of Sannio, Benevento I-82100, Italy.

Andrea Cusano (A)

Optoelectronics Group, Engineering Department, University of Sannio, Benevento I-82100, Italy.
a.cusano@unisannio.it.

Classifications MeSH