Evidence map›Paper›PMID 27809243›Full record

ArticleSensors (Basel, Switzerland)2016

A Cross-Correlational Analysis between Electroencephalographic and End-Tidal Carbon Dioxide Signals: Methodological Issues in the Presence of Missing Data and Real Data Results.

Maria Sole Morelli, Alberto Giannoni, Claudio Passino, Luigi Landini, Michele Emdin, Nicola Vanello

Abstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed, 1 pooled it
–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

4 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Article
  3. Article
  4. 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

6 authors.

Maria Sole MorelliInstitute of Life Science, Scuola Superiore Sant'Anna, 56127 Pisa, Italy. mar.morelli@sssup.it.
Alberto GiannoniFondazione Toscana Gabriele Monasterio, National Research Council, 56124 Pisa, Italy. alberto.giannoni@ftgm.it.
Claudio PassinoInstitute of Life Science, Scuola Superiore Sant'Anna, 56127 Pisa, Italy. passino@ftgm.it.
Luigi LandiniFondazione Toscana Gabriele Monasterio, National Research Council, 56124 Pisa, Italy. luigi.landini@iet.unipi.it.
Michele EmdinInstitute of Life Science, Scuola Superiore Sant'Anna, 56127 Pisa, Italy. emdin@ftgm.it.
Nicola VanelloDipartimento di Ingegneria dell'Informazione, University of Pisa, 56124 Pisa, Italy. nicola.vanello@unipi.it.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Electroencephalographic (EEG) irreducible artifacts are common and the removal of corrupted segments from the analysis may be required. The present study aims at exploring the effects of different EEG Missing Data Segment (MDS) distributions on cross-correlation analysis, involving EEG and physiological signals. The reliability of cross-correlation analysis both at single subject and at group level as a function of missing data statistics was evaluated using dedicated simulations. Moreover, a Bayesian-based approach for combining the single subject results at group level by considering each subject's reliability was introduced. Starting from the above considerations, the cross-correlation function between EEG Global Field Power (GFP) in delta band and end-tidal CO₂ (P

Indexed as

control of breathingcross correlation functionEEGmissing data segments

Identifiers

PMID27809243
PMCPMC5134487

What OpenQuestion holds

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LicenceCC BY
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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.