Evidence map›Paper›PMID 30213100›Full record

ArticleSensors (Basel, Switzerland)2018

Distorter Characterisation Using Mutual Inductance in Electromagnetic Tracking.

Herman Alexander Jaeger, Pádraig Cantillon-Murphy

Abstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

5 citing papers in PubMed.

  1. Review
  2. Article
  3. Article
  4. Article
  5. Electromagnetic Medical Sensing.Sensors (Basel, Switzerland) · 2019
    Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors.

Herman Alexander JaegerDepartment of Electrical and Electronic Engineering, School of Engineering, University College Cork, Cork, Ireland. h.jaeger@umail.ucc.ie.ORCID 0000-0003-4771-8469
Pádraig Cantillon-MurphyDepartment of Electrical and Electronic Engineering, School of Engineering, University College Cork, Cork, Ireland. p.cantillonmurphy@ucc.ie.ORCID 0000-0001-6679-2889

Funding

Eurostars 11581Science Foundation Ireland TIDA17/4897
6 · The paper itself

Abstract

Electromagnetic tracking (EMT) is playing an increasingly important role in surgical navigation, medical robotics and virtual reality development as a positional and orientation reference. Though EMT is not restricted by line-of-sight requirements, measurement errors caused by magnetic distortions in the environment remain the technology's principal shortcoming. The characterisation, reduction and compensation of these errors is a broadly researched topic, with many developed techniques relying on auxiliary tracking hardware including redundant sensor arrays, optical and inertial tracking systems. This paper describes a novel method of detecting static magnetic distortions using only the magnetic field transmitting array. An existing transmitter design is modified to enable simultaneous transmission and reception of the generated magnetic field. A mutual inductance model is developed for this transmitter design in which deviations from control measurements indicate the location, magnitude and material of the field distorter to an approximate degree. While not directly compensating for errors, this work enables users of EMT systems to optimise placement of the magnetic transmitter by characterising a distorter's effect within the tracking volume without the use of additional hardware. The discrimination capabilities of this method may also allow researchers to apply material-specific compensation techniques to minimise position error in the clinical setting.

Indexed as

distortionelectromagnetic trackingimage-guided interventionsmagneticsrobotics

Identifiers

PMID30213100
PMCPMC6165436

What OpenQuestion holds

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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.