Evidence map›Paper›PMID 27337708›Full record

ArticleIEEE transactions on bio-medical engineering2017

Separation of Physiological Signals Using Minimum Norm Projection Operators.

James D Wilson, Jens Haueisen

Abstract readEvaluation Study
In one paragraph

Article in IEEE transactions on bio-medical engineering, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing 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

6 citing papers in PubMed.

  1. Review
  2. Article
  3. Article
  4. Article
  5. Article
  6. Adaptable Sensor Arrays for Fetal Magnetocardiographic Measurements Using Optically-Pumped Magnetometers: A Pilot Study.Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference · 2020
    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.

James D Wilson
Jens Haueisen

Funding

Development of Analysis Tools to Enhance Fetal Neurological AssessmentR01EB007826 · NIBIB · UNIV OF ARKANSAS FOR MED SCIS · PI ESWARAN, HARI · 2007 to 2013
$1.4M
NIBIB NIH HHS R01 EB007826
6 · The paper itself

Abstract

objectiveThis paper presents the development of a fast and robust method which can be applied to multichannel physiologic signals for the purpose of either removing a selected interfering signal or separating signals that arise from temporally correlated and spatially distributed signals such as maternal or fetal cardiac waveform recordings.

methodsProjection operators based upon both the weighted and un-weighted minimum norm equations are presented. The weighted formulation uses models based on signal covariance and the un-weighted formulation requires that a statistical model be built using time-locked averaging.

resultsWe present examples that demonstrate the utility of our projection operators when applied to maternal and fetal magneto-cardiograms. In addition, we demonstrate the ability to separate fetal breathing signals from both maternal and fetal cardiac signals.

conclusionThe method is effective, robust, fast, and does not require significant input from a user. SIGNIFICANCE: Although we demonstrate the utility of our projection operators applied to biomagnetic signals, the method can easily be adapted to other applications were the goal is to either separate or suppress selected signal components.

Indexed as

AlgorithmsData Interpretation, StatisticalSignal Processing, Computer-AssistedAnimalsCardiotocographyComputer SimulationFemaleHeart Rate, FetalHumansMagnetocardiographyModels, BiologicalModels, StatisticalReproducibility of ResultsSensitivity and Specificity

Identifiers

PMID27337708
PMCPMC5486981

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Registered trials

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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.