Literature DB >> 28036093

Detecting stages of needle penetration into tissues through force estimation at needle tip using fiber Bragg grating sensors.

Saurabh Kumar1, Venkoba Shrikanth2, Bharadwaj Amrutur3, Sundarrajan Asokan4, Musuvathi S Bobji5.   

Abstract

Several medical procedures involve the use of needles. The advent of robotic and robot assisted procedures requires dynamic estimation of the needle tip location during insertion for use in both assistive systems as well as for automatic control. Most prior studies have focused on the maneuvering of solid flexible needles using external force measurements at the base of the needle holder. However, hollow needles are used in several procedures and measurements of forces in proximity of such needles can eliminate the need for estimating frictional forces that have high variations. These measurements are also significant for endoscopic procedures in which measurement of forces at the needle holder base is difficult. Fiber Bragg grating sensors, due to their small size, inert nature, and multiplexing capability, provide a good option for this purpose. Force measurements have been undertaken during needle insertion into tissue mimicking phantoms made of polydimethylsiloxane as well as chicken tissue using an 18-G needle instrumented with FBG sensors. The results obtained show that it is possible to estimate the different stages of needle penetration including partial rupture, which is significant for procedures in which precise estimation of needle tip position inside the organ or tissue is required.

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Year:  2016        PMID: 28036093     DOI: 10.1117/1.JBO.21.12.127009

Source DB:  PubMed          Journal:  J Biomed Opt        ISSN: 1083-3668            Impact factor:   3.170


  4 in total

1.  Design of a force-measuring setup for colorectal compression anastomosis and first ex-vivo results.

Authors:  Jana Steger; Isabella Patzke; Maximilian Berlet; Stefanie Ficht; Markus Eblenkamp; Petra Mela; Dirk Wilhelm
Journal:  Int J Comput Assist Radiol Surg       Date:  2021-04-23       Impact factor: 3.421

2.  Spatio-temporal deep learning models for tip force estimation during needle insertion.

Authors:  Nils Gessert; Torben Priegnitz; Thore Saathoff; Sven-Thomas Antoni; David Meyer; Moritz Franz Hamann; Klaus-Peter Jünemann; Christoph Otte; Alexander Schlaefer
Journal:  Int J Comput Assist Radiol Surg       Date:  2019-05-30       Impact factor: 2.924

3.  Needle tip force estimation by deep learning from raw spectral OCT data.

Authors:  M Gromniak; N Gessert; T Saathoff; A Schlaefer
Journal:  Int J Comput Assist Radiol Surg       Date:  2020-07-22       Impact factor: 2.924

4.  Study of needle punctures into soft tissue through audio and force sensing: can audio be a simple alternative for needle guidance?

Authors:  Muhannad Sabieleish; Katarzyna Heryan; Axel Boese; Christian Hansen; Michael Friebe; Alfredo Illanes
Journal:  Int J Comput Assist Radiol Surg       Date:  2021-10-15       Impact factor: 2.924

  4 in total

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