Evidence map›Paper›PMID 34272934›Full record

ArticleAdvanced science (Weinheim, Baden-Wurttemberg, Germany)2021

Wireless Soft Scalp Electronics and Virtual Reality System for Motor Imagery-Based Brain-Machine Interfaces.

Musa Mahmood, Shinjae Kwon, Hojoong Kim, Yun-Soung Kim, Panote Siriaraya, Jeongmoon Choi, Boris Otkhmezuri, Kyowon Kang, Ki Jun Yu, Young C Jang and 2 more

Abstract read
In one paragraph

Article in Advanced science (Weinheim, Baden-Wurttemberg, Germany), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 29 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
29citing 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

29 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Article
  3. Full-Stack Architectures for Intelligent Brain-Computer Interfaces.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026
    Review
  4. Wrinkle-Adaptive Kirigami Wearables With Anisotropic Deformability for Sleep EEG Monitoring.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026
    Article
  5. Review
  6. Article
  7. Article
  8. Motion artifact-controlled micro-brain sensors between hair follicles for persistent augmented reality brain-computer interfaces.Proceedings of the National Academy of Sciences of the United States of America · 2025
    Article
  9. Review
  10. Article
  11. Article
  12. Beyond Flexible: Unveiling the Next Era of Flexible Electronic Systems.Advanced materials (Deerfield Beach, Fla.) · 2024
    Review
  13. Article
  14. Article
  15. Article
  16. Article
  17. Article
  18. Review
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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

12 authors.

Musa MahmoodGeorge W. Woodruff School of Mechanical Engineering, College of Engineering, Georgia Institute of Technology, Atlanta, GA, 30332, USA.
Shinjae KwonGeorge W. Woodruff School of Mechanical Engineering, College of Engineering, Georgia Institute of Technology, Atlanta, GA, 30332, USA.
Hojoong KimGeorge W. Woodruff School of Mechanical Engineering, College of Engineering, Georgia Institute of Technology, Atlanta, GA, 30332, USA.
Yun-Soung KimGeorge W. Woodruff School of Mechanical Engineering, College of Engineering, Georgia Institute of Technology, Atlanta, GA, 30332, USA.
Panote SiriarayaSchool of Computing, University of Kent, Canterbury, Kent, CT2 7NT, UK.
Jeongmoon ChoiSchool of Biological Sciences, College of Sciences, Georgia Institute of Technology, Atlanta, GA, 30332, USA.
Boris OtkhmezuriSchool of Computing, University of Kent, Canterbury, Kent, CT2 7NT, UK.
Kyowon KangSchool of Electrical and Electronic Engineering, Yonsei University, Seoul, 03722, Republic of Korea.
Ki Jun YuSchool of Electrical and Electronic Engineering, Yonsei University, Seoul, 03722, Republic of Korea.
Young C JangSchool of Biological Sciences, College of Sciences, Georgia Institute of Technology, Atlanta, GA, 30332, USA.
Chee Siang AngSchool of Computing, University of Kent, Canterbury, Kent, CT2 7NT, UK.
Woon-Hong YeoGeorge W. Woodruff School of Mechanical Engineering, College of Engineering, Georgia Institute of Technology, Atlanta, GA, 30332, USA.ORCID 0000-0002-5526-3882

Funding

Developing an imperceptible electroencephalography at-home sleep monitoring system for cognitive and clinical researchR21AG064309 · NIA · UNIVERSITY OF TEXAS AT AUSTIN · PI DUARTE, AUDREY, YEO, WOON-HONG · 2020 to 2020
$421k
Georgia Tech Institute for Electronics and NanotechnologyNational Research Foundation of Korea NRF-2018M3A7B4071109National Research Foundation of Korea NRF-2019R1A2C2086085NIA NIH HHS R21 AG064309NIH HHS NIH R21AG064309
6 · The paper itself

Abstract

Motor imagery offers an excellent opportunity as a stimulus-free paradigm for brain-machine interfaces. Conventional electroencephalography (EEG) for motor imagery requires a hair cap with multiple wired electrodes and messy gels, causing motion artifacts. Here, a wireless scalp electronic system with virtual reality for real-time, continuous classification of motor imagery brain signals is introduced. This low-profile, portable system integrates imperceptible microneedle electrodes and soft wireless circuits. Virtual reality addresses subject variance in detectable EEG response to motor imagery by providing clear, consistent visuals and instant biofeedback. The wearable soft system offers advantageous contact surface area and reduced electrode impedance density, resulting in significantly enhanced EEG signals and classification accuracy. The combination with convolutional neural network-machine learning provides a real-time, continuous motor imagery-based brain-machine interface. With four human subjects, the scalp electronic system offers a high classification accuracy (93.22 ± 1.33% for four classes), allowing wireless, real-time control of a virtual reality game.

Indexed as

Brain-Computer InterfacesUser-Computer InterfaceVirtual RealityBrainElectrodesElectroencephalographyHumansScalpbrain-machine interfacesmotor imagery brain signalsvirtual reality systemwireless soft scalp electronics

Identifiers

PMID34272934
PMCPMC8498913

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.