Evidence map›Paper›PMID 39687306›Full record

ArticleHardwareX2024

Low-cost, mobile EEG hardware for SSVEP applications.

M Kancaoğlu, M Kuntalp

Abstract read
In one paragraph

Article in HardwareX, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Review
  2. Article
  3. Review
  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

2 authors.

M KancaoğluDokuz Eylul University, Graduate School of Natural and Applied Sciences, Department of Biomedical Technologies, Turkey.
M KuntalpDokuz Eylul University, Graduate School of Natural and Applied Sciences, Department of Biomedical Technologies, Turkey.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The global shortage of integrated circuits due to the COVID-19 pandemic has made it challenging to build biopotential acquisition devices like electroencephalography (EEG) hardware. To address this issue, a new hardware system using common ICs has been designed, which is cost-effective, precise, and easily accessible from global distributors. The hardware system comprises 8-channel inputs EEG hardware with a mobile headset capable of acquiring 5-30Hz EEG signals. First two channels of the design is enabled for steady-state visual evoked potential (SSVEP) operations, and the remaining channels can be powered up as needed. A small 3D-printable enclosure is also designed for the hardware board, which is attached to protective glasses to be used as a head-mounted device. The board includes an additional green LED, 4 pulse width modulation (PWM) outputs for general-purpose input/output (GPIO), 2 buttons for input, and exposed programming pins and digital-to-analog converter (DAC) output from the microcontroller unit (MCU). The proposed hardware system is expected to enable students and young researchers to experiment with EEG signals, especially SSVEP, before investing in professional equipment with the availability of programming codes.

Indexed as

BciBiopotentialEegSsvep

Identifiers

PMID39687306
PMCPMC11647867

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.