Literature DB >> 32000145

Towards emerging EEG applications: a novel printable flexible Ag/AgCl dry electrode array for robust recording of EEG signals at forehead sites.

Guangli Li1, Jingtao Wu, Yonghui Xia, Yiyong Wu, Yaling Tian, Jun Liu, Dongchu Chen, Quanguo He.   

Abstract

OBJECTIVES: With the rapid development of EEG-based wearable healthcare devices and brain-computer interfaces, reliable and user-friendly EEG sensors for EEG recording, especially at forehead sites, are highly desirable and challenging. However, existing EEG sensors cannot meet the requirements, since wet electrodes require tedious setup and conductive pastes or gels, and most dry electrodes show unacceptable high contact impedance. In addition, the existing electrodes cannot absorb sweat effectively; sweat would cause cross-interferences, and even short circuits, between adjacent electrodes, especially in the moving scenarios, or a hot and humid environment. To resolve these problems, a novel printable flexible Ag/AgCl dry electrode array was developed for EEG acquisition at forehead sites, mainly consisting of screen printing the Ag/AgCl coating, conductive sweat-absorbable sponges and flexible tines. APPROACH: A systematic method was also established to evaluate the flexible dry electrode array. MAIN
RESULTS: The experimental results show the flexible dry electrode array has reproducible electrode potential, relatively low electrode-skin impedance, and good stability. Moreover, the EEG signals can be effectively captured with a high quality that is comparable to that of wet electrodes. SIGNIFICANCE: All the results confirmed the feasibility of forehead EEG recording in real-world scenarios using the proposed flexible dry electrode array, with a rapid and facile operation as well as the advantages of self-application, user-friendliness and wearer comfort.

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Year:  2020        PMID: 32000145     DOI: 10.1088/1741-2552/ab71ea

Source DB:  PubMed          Journal:  J Neural Eng        ISSN: 1741-2552            Impact factor:   5.379


  6 in total

1.  Titania/Electro-Reduced Graphene Oxide Nanohybrid as an Efficient Electrochemical Sensor for the Determination of Allura Red.

Authors:  Guangli Li; Jingtao Wu; Hongguang Jin; Yonghui Xia; Jun Liu; Quanguo He; Dongchu Chen
Journal:  Nanomaterials (Basel)       Date:  2020-02-11       Impact factor: 5.076

2.  Proposals and Comparisons from One-Sensor EEG and EOG Human-Machine Interfaces.

Authors:  Francisco Laport; Daniel Iglesia; Adriana Dapena; Paula M Castro; Francisco J Vazquez-Araujo
Journal:  Sensors (Basel)       Date:  2021-03-22       Impact factor: 3.576

3.  A Deep Learning Strategy for Automatic Sleep Staging Based on Two-Channel EEG Headband Data.

Authors:  Amelia A Casciola; Sebastiano K Carlucci; Brianne A Kent; Amanda M Punch; Michael A Muszynski; Daniel Zhou; Alireza Kazemi; Maryam S Mirian; Jason Valerio; Martin J McKeown; Haakon B Nygaard
Journal:  Sensors (Basel)       Date:  2021-05-11       Impact factor: 3.576

4.  Effect of Static Posture on Online Performance of P300-Based BCIs for TV Control.

Authors:  Dojin Heo; Minju Kim; Jongsu Kim; Yun-Joo Choi; Sung-Phil Kim
Journal:  Sensors (Basel)       Date:  2021-03-24       Impact factor: 3.576

Review 5.  State of the Art of Non-Invasive Electrode Materials for Brain-Computer Interface.

Authors:  Haowen Yuan; Yao Li; Junjun Yang; Hongjie Li; Qinya Yang; Cuiping Guo; Shenmin Zhu; Xiaokang Shu
Journal:  Micromachines (Basel)       Date:  2021-12-08       Impact factor: 2.891

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

Authors:  Musa Mahmood; Shinjae Kwon; Hojoong Kim; Yun-Soung Kim; Panote Siriaraya; Jeongmoon Choi; Boris Otkhmezuri; Kyowon Kang; Ki Jun Yu; Young C Jang; Chee Siang Ang; Woon-Hong Yeo
Journal:  Adv Sci (Weinh)       Date:  2021-07-17       Impact factor: 16.806

  6 in total

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