Evidence map›Paper›PMID 31652579›Full record

ArticleSensors (Basel, Switzerland)2019

Simultaneous EEG Acquisition System for Multiple Users: Development and Related Issues.

Sunghan Lee, Hohyun Cho, Kiseong Kim, Sung Chan Jun

Abstract 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 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing 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

8 citing papers in PubMed.

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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

4 authors.

Sunghan LeeSchool of Electrical Engineering and Computer Science, Gwangju Institute of Science and Technology, Gwangju 61005, Korea. sunghanlee@gist.ac.kr.
Hohyun ChoWadsworth Center, New York State Department of Health, Albany, NY 12201, USA. Hohyun.Cho@health.ny.gov.
Kiseong KimDepartment of Bio and Brain Engineering, Korea Advanced Institute of Science and Technology, Daejeon 34141, Korea. iames@kaist.ac.kr.ORCID 0000-0001-9935-3516
Sung Chan JunSchool of Electrical Engineering and Computer Science, Gwangju Institute of Science and Technology, Gwangju 61005, Korea. scjun@gist.ac.kr.ORCID 0000-0001-5357-4436

Funding

Institute of Information & Communications Technology Planning & Evaluation 2017-0-00451
6 · The paper itself

Abstract

Social interaction is one of humans' most important activities and many efforts have been made to understand the phenomenon. Recently, some investigators have attempted to apply advanced brain signal acquisition systems that allow dynamic brain activities to be measured simultaneously during social interactions. Most studies to date have investigated dyadic interactions, although multilateral interactions are more common in reality. However, it is believed that most studies have focused on such interactions because of methodological limitations, in that it is very difficult to design a well-controlled experiment for multiple users at a reasonable cost. Accordingly, there are few simultaneous acquisition systems for multiple users. In this study, we propose a design framework for an acquisition system that measures EEG data simultaneously in an environment with 10 or more people. Our proposed framework allowed us to acquire EEG data at up to 1 kHz frequency from up to 20 people simultaneously. Details of our acquisition system are described from hardware and software perspectives. In addition, various related issues that arose in the system's development-such as synchronization techniques, system loads, electrodes, and applications-are discussed. In addition, simultaneous visual ERP experiments were conducted with a group of nine people to validate the EEG acquisition framework proposed. We found that our framework worked reasonably well with respect to less than 4 ms delay and average loss rates of 1%. It is expected that this system can be used in various hyperscanning studies, such as those on crowd psychology, large-scale human interactions, and collaborative brain-computer interface, among others.

Indexed as

ElectroencephalographyEvoked PotentialsHumansReproducibility of ResultsEEGhyperscanningsimultaneous acquisition

Identifiers

PMID31652579
PMCPMC6832946

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Registered trials

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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.