Evidence map›Paper›PMID 30744081›Full record

ArticleSensors (Basel, Switzerland)2019

Correlation and Similarity between Cerebral and Non-Cerebral Electrical Activity for User's States Assessment.

Gianluca Borghini, Pietro Aricò, Gianluca Di Flumeri, Nicolina Sciaraffa, Fabio Babiloni

Open access · goldAbstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.

0numbers the graph read from it
0cells of the map it votes in
19citing papers in PubMed
2.2field-weighted citation impact, top 13% of its field
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

19 citing papers in PubMed, 33 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Review
  6. Article
  7. Article
  8. Article
  9. Review
  10. Article
  11. Article
  12. Article
  13. Article
  14. Article
  15. Article
  16. Article
  17. Article
  18. Review
  19. 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

5 authors at 1 institution in 2 countries.

Gianluca BorghiniDepartment of Molecular Medicine, Sapienza University of Rome, Piazzale Aldo Moro, 5, 00185 Rome, Italy. gianluca.borghini@uniroma1.it.ORCID 0000-0001-8560-5671
Pietro AricòDepartment of Molecular Medicine, Sapienza University of Rome, Piazzale Aldo Moro, 5, 00185 Rome, Italy. pietro.arico@uniroma1.it.ORCID 0000-0002-3831-6620
Gianluca Di FlumeriDepartment of Molecular Medicine, Sapienza University of Rome, Piazzale Aldo Moro, 5, 00185 Rome, Italy. gianluca.diflumeri@uniroma1.it.ORCID 0000-0003-4426-051X
Nicolina SciaraffaBrainSigns srl, via Sesto Celere, 00152 Rome, Italy. nicolina.sciaraffa@brainsigns.com.
Fabio BabiloniDepartment of Molecular Medicine, Sapienza University of Rome, Piazzale Aldo Moro, 5, 00185 Rome, Italy. fabio.babiloni@uniroma1.it.ORCID 0000-0002-4962-176X
SAES Group (Italy) · IT

Funding

European Commission 723386
6 · The paper itself

Abstract

Human tissues own conductive properties, and the electrical activity produced by human organs can propagate throughout the body due to neuro transmitters and electrolytes. Therefore, it might be reasonable to hypothesize correlations and similarities between electrical activities among different parts of the body. Since no works have been found in this direction, the proposed study aimed at overcoming this lack of evidence and seeking analogies between the brain activity and the electrical activity of non-cerebral locations, such as the neck and wrists, to determine if i) cerebral parameters can be estimated from non-cerebral sites, and if ii) non-cerebral sensors can replace cerebral sensors for the evaluation of the users under specific experimental conditions, such as eyes open or closed. In fact, the use of cerebral sensors requires high-qualified personnel, and reliable recording systems, which are still expensive. Therefore, the possibility to use cheaper and easy-to-use equipment to estimate cerebral parameters will allow making some brain-based applications less invasive and expensive, and easier to employ. The results demonstrated the occurrence of significant correlations and analogies between cerebral and non-cerebral electrical activity. Furthermore, the same discrimination and classification accuracy were found in using the cerebral or non-cerebral sites for the user's status assessment.

Indexed as

Electric ConductivitySignal Processing, Computer-AssistedAdultBrainBrain WavesElectroencephalographyHandHumansMachine LearningNeckYoung Adultbiopotentialsbrain activitycorrelationEEGelectrical activityhuman bodyhuman tissues conductibilityindividual alpha frequencymachine-learning analysismental states assessment

Identifiers

PMID30744081
PMCPMC6387465
OpenAlexW2914294201

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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.