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Herbert C. Brain-computer interfaces and human factors: the role of language and cultural differences-Still a missing gap? Front Hum Neurosci 2024; 18:1305445. [PMID: 38665897 PMCID: PMC11043545 DOI: 10.3389/fnhum.2024.1305445] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/01/2023] [Accepted: 02/02/2024] [Indexed: 04/28/2024] Open
Abstract
Brain-computer interfaces (BCIs) aim at the non-invasive investigation of brain activity for supporting communication and interaction of the users with their environment by means of brain-machine assisted technologies. Despite technological progress and promising research aimed at understanding the influence of human factors on BCI effectiveness, some topics still remain unexplored. The aim of this article is to discuss why it is important to consider the language of the user, its embodied grounding in perception, action and emotions, and its interaction with cultural differences in information processing in future BCI research. Based on evidence from recent studies, it is proposed that detection of language abilities and language training are two main topics of enquiry of future BCI studies to extend communication among vulnerable and healthy BCI users from bench to bedside and real world applications. In addition, cultural differences shape perception, actions, cognition, language and emotions subjectively, behaviorally as well as neuronally. Therefore, BCI applications should consider cultural differences in information processing to develop culture- and language-sensitive BCI applications for different user groups and BCIs, and investigate the linguistic and cultural contexts in which the BCI will be used.
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Affiliation(s)
- Cornelia Herbert
- Applied Emotion and Motivation Psychology, Institute of Psychology and Education, Ulm University, Ulm, Germany
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Lin S, Jiang J, Huang K, Li L, He X, Du P, Wu Y, Liu J, Li X, Huang Z, Zhou Z, Yu Y, Gao J, Lei M, Wu H. Advanced Electrode Technologies for Noninvasive Brain-Computer Interfaces. ACS NANO 2023; 17:24487-24513. [PMID: 38064282 DOI: 10.1021/acsnano.3c06781] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/27/2023]
Abstract
Brain-computer interfaces (BCIs) have garnered significant attention in recent years due to their potential applications in medical, assistive, and communication technologies. Building on this, noninvasive BCIs stand out as they provide a safe and user-friendly method for interacting with the human brain. In this work, we provide a comprehensive overview of the latest developments and advancements in material, design, and application of noninvasive BCIs electrode technology. We also explore the challenges and limitations currently faced by noninvasive BCI electrode technology and sketch out the technological roadmap from three dimensions: Materials and Design; Performances; Mode and Function. We aim to unite research efforts within the field of noninvasive BCI electrode technology, focusing on the consolidation of shared goals and fostering integrated development strategies among a diverse array of multidisciplinary researchers.
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Affiliation(s)
- Sen Lin
- School of Physical Science and Technology, Guangxi University, Nanning 530004, China
| | - Jingjing Jiang
- School of Physical Science and Technology, Guangxi University, Nanning 530004, China
| | - Kai Huang
- State Key Laboratory of New Ceramics and Fine Processing, School of Materials Science and Engineering, Tsinghua University, Beijing 100084, China
- State Key Laboratory of Information Photonics and Optical Communications and School of Science, Beijing University of Posts and Telecommunications, Beijing 100876, China
| | - Lei Li
- National Engineering Research Center of Electric Vehicles, Beijing Institute of Technology, Beijing 100081, China
| | - Xian He
- State Key Laboratory of New Ceramics and Fine Processing, School of Materials Science and Engineering, Tsinghua University, Beijing 100084, China
| | - Peng Du
- State Key Laboratory of New Ceramics and Fine Processing, School of Materials Science and Engineering, Tsinghua University, Beijing 100084, China
| | - Yufeng Wu
- State Key Laboratory of New Ceramics and Fine Processing, School of Materials Science and Engineering, Tsinghua University, Beijing 100084, China
| | - Junchen Liu
- State Key Laboratory of New Ceramics and Fine Processing, School of Materials Science and Engineering, Tsinghua University, Beijing 100084, China
- State Key Laboratory of Information Photonics and Optical Communications and School of Science, Beijing University of Posts and Telecommunications, Beijing 100876, China
| | - Xilin Li
- School of Physical Science and Technology, Guangxi University, Nanning 530004, China
- Advanced Institute for Brain and Intelligence, Guangxi University, Nanning 530004, China
| | - Zhibao Huang
- School of Physical Science and Technology, Guangxi University, Nanning 530004, China
| | - Zenan Zhou
- School of Physical Science and Technology, Guangxi University, Nanning 530004, China
| | - Yuanhang Yu
- School of Physical Science and Technology, Guangxi University, Nanning 530004, China
| | - Jiaxin Gao
- School of Physical Science and Technology, Guangxi University, Nanning 530004, China
| | - Ming Lei
- State Key Laboratory of Information Photonics and Optical Communications and School of Science, Beijing University of Posts and Telecommunications, Beijing 100876, China
| | - Hui Wu
- State Key Laboratory of New Ceramics and Fine Processing, School of Materials Science and Engineering, Tsinghua University, Beijing 100084, China
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孙 静, 孟 佳, 尤 佳, 杨 明, 江 京, 许 敏, 明 东. [Research progress of brain-computer interface application paradigms based on rapid serial visual presentation]. SHENG WU YI XUE GONG CHENG XUE ZA ZHI = JOURNAL OF BIOMEDICAL ENGINEERING = SHENGWU YIXUE GONGCHENGXUE ZAZHI 2023; 40:1235-1241. [PMID: 38151948 PMCID: PMC10753308 DOI: 10.7507/1001-5515.202305061] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Subscribe] [Scholar Register] [Received: 05/30/2023] [Revised: 11/08/2023] [Indexed: 12/29/2023]
Abstract
Rapid serial visual presentation (RSVP) is a type of psychological visual stimulation experimental paradigm that requires participants to identify target stimuli presented continuously in a stream of stimuli composed of numbers, letters, words, images, and so on at the same spatial location, allowing them to discern a large amount of information in a short period of time. The RSVP-based brain-computer interface (BCI) can not only be widely used in scenarios such as assistive interaction and information reading, but also has the advantages of stability and high efficiency, which has become one of the common techniques for human-machine intelligence fusion. In recent years, brain-controlled spellers, image recognition and mind games are the most popular fields of RSVP-BCI research. Therefore, aiming to provide reference and new ideas for RSVP-BCI related research, this paper reviewed the paradigm design and system performance optimization of RSVP-BCI in these three fields. It also looks ahead to its potential applications in cutting-edge fields such as entertainment, clinical medicine, and special military operations.
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Affiliation(s)
- 静敏 孙
- 天津大学 精密仪器与光电子工程学院(天津 300072)School of Precision Instruments and Opto-Electronic Engineering, Tianjin University, Tianjin 300072, P. R. China
| | - 佳圆 孟
- 天津大学 精密仪器与光电子工程学院(天津 300072)School of Precision Instruments and Opto-Electronic Engineering, Tianjin University, Tianjin 300072, P. R. China
- 天津大学 医学工程与转化医学研究院(天津 300072)Academy of Medical Engineering and Translational Medicine, Tianjin University, Tianjin 300072, P. R. China
| | - 佳 尤
- 天津大学 精密仪器与光电子工程学院(天津 300072)School of Precision Instruments and Opto-Electronic Engineering, Tianjin University, Tianjin 300072, P. R. China
| | - 明明 杨
- 天津大学 精密仪器与光电子工程学院(天津 300072)School of Precision Instruments and Opto-Electronic Engineering, Tianjin University, Tianjin 300072, P. R. China
| | - 京 江
- 天津大学 精密仪器与光电子工程学院(天津 300072)School of Precision Instruments and Opto-Electronic Engineering, Tianjin University, Tianjin 300072, P. R. China
| | - 敏鹏 许
- 天津大学 精密仪器与光电子工程学院(天津 300072)School of Precision Instruments and Opto-Electronic Engineering, Tianjin University, Tianjin 300072, P. R. China
- 天津大学 医学工程与转化医学研究院(天津 300072)Academy of Medical Engineering and Translational Medicine, Tianjin University, Tianjin 300072, P. R. China
| | - 东 明
- 天津大学 精密仪器与光电子工程学院(天津 300072)School of Precision Instruments and Opto-Electronic Engineering, Tianjin University, Tianjin 300072, P. R. China
- 天津大学 医学工程与转化医学研究院(天津 300072)Academy of Medical Engineering and Translational Medicine, Tianjin University, Tianjin 300072, P. R. China
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Fernández-Rodríguez Á, Ron-Angevin R, Velasco-Álvarez F, Diaz-Pineda J, Letouzé T, André JM. Evaluation of Single-Trial Classification to Control a Visual ERP-BCI under a Situation Awareness Scenario. Brain Sci 2023; 13:886. [PMID: 37371365 DOI: 10.3390/brainsci13060886] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/11/2023] [Revised: 05/15/2023] [Accepted: 05/29/2023] [Indexed: 06/29/2023] Open
Abstract
An event-related potential (ERP)-based brain-computer interface (BCI) can be used to monitor a user's cognitive state during a surveillance task in a situational awareness context. The present study explores the use of an ERP-BCI for detecting new planes in an air traffic controller (ATC). Two experiments were conducted to evaluate the impact of different visual factors on target detection. Experiment 1 validated the type of stimulus used and the effect of not knowing its appearance location in an ERP-BCI scenario. Experiment 2 evaluated the effect of the size of the target stimulus appearance area and the stimulus salience in an ATC scenario. The main results demonstrate that the size of the plane appearance area had a negative impact on the detection performance and on the amplitude of the P300 component. Future studies should address this issue to improve the performance of an ATC in stimulus detection using an ERP-BCI.
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Affiliation(s)
- Álvaro Fernández-Rodríguez
- Departamento de Tecnología Electrónica, Instituto Universitario de Investigación en Telecomunicación de la Universidad de Málaga (TELMA), Universidad de Málaga, 29071 Malaga, Spain
| | - Ricardo Ron-Angevin
- Departamento de Tecnología Electrónica, Instituto Universitario de Investigación en Telecomunicación de la Universidad de Málaga (TELMA), Universidad de Málaga, 29071 Malaga, Spain
| | - Francisco Velasco-Álvarez
- Departamento de Tecnología Electrónica, Instituto Universitario de Investigación en Telecomunicación de la Universidad de Málaga (TELMA), Universidad de Málaga, 29071 Malaga, Spain
| | | | - Théodore Letouzé
- Laboratoire IMS, CNRS UMR 5218, Cognitive Team, Bordeaux INP-ENSC, 33400 Talence, France
| | - Jean-Marc André
- Laboratoire IMS, CNRS UMR 5218, Cognitive Team, Bordeaux INP-ENSC, 33400 Talence, France
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