Evidence map›Paper›PMID 30011900›Full record

Trial reportSensors (Basel, Switzerland)2018

Design and Validation of an FPGA-Based Configurable Transcranial Doppler Neurofeedback System for Chronic Pain Patients.

Beatriz Rey, Alejandro Rodríguez, Enrique Lloréns-Bufort, José Tembl, Miguel Ángel Muñoz, Pedro Montoya, Vicente Herrero-Bosch, Jose M Monzo

Abstract readRandomized Controlled TrialValidation Study
In one paragraph

Trial report 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 1 paper, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
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

8 authors.

Beatriz ReyDepartamento de Ingeniería Gráfica, Universitat Politècnica de València, Camino Vera s/n, 46022 Valencia, Spain. beareyso@dig.upv.es.ORCID 0000-0001-9213-1443
Alejandro RodríguezDepartamento de Ingeniería Gráfica, Universitat Politècnica de València, Camino Vera s/n, 46022 Valencia, Spain. alrodor@upv.es.
Enrique Lloréns-BufortInstituto de Instrumentación para Imagen Molecular (I3M), Centro Mixto CSIC-Universitat Politècnica de València-CIEMAT, Camino de Vera s/n, 46022 Valencia, Spain. enllobu@gmail.com.
José TemblDepartamento de Neurología, Hospital Universitari i Politècnic La Fe, 46026 Valencia, Spain. tembl_jos@gva.es.
Miguel Ángel MuñozDepartamento de Personalidad, Evaluación y Tratamiento Psicológico, Universidad de Granada, 18071 Granada, Spain. mamuoz@ugr.es.
Pedro MontoyaInstituto Universitario de Investigación en Ciencias de la Salud, Universitat Illes Balears, 07122 Palma, Spain. pedro.montoya@uib.es.ORCID 0000-0001-8652-948X
Vicente Herrero-BoschInstituto de Instrumentación para Imagen Molecular (I3M), Centro Mixto CSIC-Universitat Politècnica de València-CIEMAT, Camino de Vera s/n, 46022 Valencia, Spain. viherbos@eln.upv.es.
Jose M MonzoInstituto de Instrumentación para Imagen Molecular (I3M), Centro Mixto CSIC-Universitat Politècnica de València-CIEMAT, Camino de Vera s/n, 46022 Valencia, Spain. jmonfer@upvnet.upv.es.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Neurofeedback is a self-regulation technique that can be applied to learn to voluntarily control cerebral activity in specific brain regions. In this work, a Transcranial Doppler-based configurable neurofeedback system is proposed and described. The hardware configuration is based on the Red Pitaya board, which gives great flexibility and processing power to the system. The parameter to be trained can be selected between several temporal, spectral, or complexity features from the cerebral blood flow velocity signal in different vessels. As previous studies have found alterations in these parameters in chronic pain patients, the system could be applied to help them to voluntarily control these parameters. Two protocols based on different temporal lengths of the training periods have been proposed and tested with six healthy subjects that were randomly assigned to one of the protocols at the beginning of the procedure. For the purposes of the testing, the trained parameter was the mean cerebral blood flow velocity in the aggregated data from the two anterior cerebral arteries. Results show that, using the proposed neurofeedback system, the two groups of healthy volunteers can learn to self-regulate a parameter from their brain activity in a reduced number of training sessions.

Indexed as

Ultrasonography, Doppler, TranscranialAdolescentAdultAgedBlood Flow VelocityCerebrovascular CirculationChronic PainFemaleHumansMaleMiddle AgedNeurofeedbackYoung Adultchronic paindigital signal processingfibromyalgiaFPGAneurofeedbackSystem on Chiptranscranial doppler ultrasound

Identifiers

PMID30011900
PMCPMC6069097

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.