Evidence map›Paper›PMID 37033908›Full record

ArticleFrontiers in human neuroscience2023

Novel electrotactile brain-computer interface with somatosensory event-related potential based control.

Andrej M Savić, Marija Novičić, Olivera Ðorđević, Ljubica Konstantinović, Vera Miler-Jerković

Open access · goldAbstract read
In one paragraph

Article in Frontiers in human neuroscience, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed, 1 pooled it
3.3field-weighted citation impact, top 7% 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

12 citing papers in PubMed, 1 synthesis or guideline pooled it, 19 citations in OpenAlex.

  1. Pooled it
  2. Article
  3. Review
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Tactile Location Perception Encoded by Gamma-Band Power.Bioengineering (Basel, Switzerland) · 2024
    Article
  10. Review
  11. Article
  12. 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 2 institutions in 1 country.

Andrej M SavićSchool of Electrical Engineering, University of Belgrade, Belgrade, Serbia.
Marija NovičićSchool of Electrical Engineering, University of Belgrade, Belgrade, Serbia.
Olivera ÐorđevićFaculty of Medicine, University of Belgrade, Belgrade, Serbia.
Ljubica KonstantinovićFaculty of Medicine, University of Belgrade, Belgrade, Serbia.
Vera Miler-JerkovićInnovation Center of the School of Electrical Engineering, University of Belgrade, Belgrade, Serbia.
University of Belgrade · RSCenter for Health, Exercise and Sport Sciences · RS

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective: A brain computer interface (BCI) allows users to control external devices using non-invasive brain recordings, such as electroencephalography (EEG). We developed and tested a novel electrotactile BCI prototype based on somatosensory event-related potentials (sERP) as control signals, paired with a tactile attention task as a control paradigm. Approach: A novel electrotactile BCI comprises commercial EEG device, an electrical stimulator and custom software for EEG recordings, electrical stimulation control, synchronization between devices, signal processing, feature extraction, selection, and classification. We tested a novel BCI control paradigm based on tactile attention on a sensation at a target stimulation location on the forearm. Tactile stimuli were electrical pulses delivered at two proximal locations on the user's forearm for stimulating branches of radial and median nerves, with equal probability of the target and distractor stimuli occurrence, unlike in any other ERP-based BCI design. We proposed a compact electrical stimulation electrodes configuration for delivering electrotactile stimuli (target and distractor) using 2 stimulation channels and 3 stimulation electrodes. We tested the feasibility of a single EEG channel BCI control, to determine pseudo-online BCI performance, in ten healthy subjects. For optimizing the BCI performance we compared the results for two classifiers, sERP averaging approaches, and novel dedicated feature extraction/selection methods Main results: We achieved a single EEG channel BCI classification accuracy in the range of 75.1 to 88.1% for all subjects. We have established an optimal combination of: single trial averaging to obtain sERP, feature extraction/selection methods and classification approach. Significance: The obtained results demonstrate that a novel electrotactile BCI paradigm with equal probability of attended (target) and unattended (distractor) stimuli and proximal stimulation sites is feasible. This method may be used to drive restorative BCIs for sensory retraining in stroke or brain injury, or assistive BCIs for communication in severely disabled users.

Indexed as

brain computer interface (BCI)electrical stimulationevent-related potentials (ERP)machine learningsomatosensory evoked potential (SEP)tactile attentiontactile BCI

Identifiers

PMID37033908
PMCPMC10078957
OpenAlexW4360618557

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.