%0 Conference Proceedings
%T Research on the Integration of Human-Computer Interaction and Cognitive Neuroscience
%+ Beijing University of Posts and Telecommunications (BUPT)
%+ Inner Mongolia University of Science & Technology
%A Miao, Xiu
%A Hou, Wen-Jun
%Z Part 1: Trends in Human Work Interaction Design
%< avec comité de lecture
%( IFIP Advances in Information and Communication Technology
%B 6th IFIP Working Conference on Human Work Interaction Design (HWID)
%C Beijing, China
%Y Ganesh Bhutkar
%Y Barbara R. Barricelli
%Y Qin Xiangang
%Y Torkil Clemmensen
%Y Frederica Gonçalves
%Y José Abdelnour-Nocera
%Y Arminda Lopes
%Y Fei Lyu
%Y Ronggang Zhou
%Y Wenjun Hou
%I Springer International Publishing
%3 Human Work Interaction Design. Artificial Intelligence and Designing for a Positive Work Experience in a Low Desire Society
%V AICT-609
%P 66-82
%8 2021-05-15
%D 2021
%R 10.1007/978-3-031-02904-2_3
%K Human-computer Interaction
%K Cognitive Neuroscience
%K EEG
%K Brain-computer Interface
%Z Computer Science [cs]Conference papers
%X This paper aims at reviewing the development of the integration of Cognitive Neuroscience and Human-computer Interaction, and put forward the main directions of the development of Brain-computer Interaction in the future.Research status and application of Human-computer Interaction based on Cognitive Neuroscience were reviewed by desktop analysis and literature survey, combined with the new research trends of Brain-computer Interface according to domestic and foreign development. According to the brain signal acquisition method and application, the types of BCI are divided into (1) Passive brain-computer interface: exploring and modeling neural mechanisms related to human interaction and on that basis realizing iterative improvement of computer design. (2) Initiative brain-computer interface: direct interaction between brain signal and computer. Then the main development direction of Brain-computer Interface field in the future from three progressive levels are discussed: broadening existing interactive channels, improving the reliability of human-computer interaction system and improving the interaction experience. The deep integration and two-way promotion of Cognitive Neuroscience and Human-computer Interaction will usher in the era of Brain-computer Interface and the next generation of artificial intelligence after overcoming a series of problems such as scene mining, algorithm optimization and model generalization.
%G English
%Z TC 13
%Z WG 13.6
%2 https://inria.hal.science/hal-03771290/document
%2 https://inria.hal.science/hal-03771290/file/509061_1_En_3_Chapter.pdf
%L hal-03771290
%U https://inria.hal.science/hal-03771290
%~ IFIP
%~ IFIP-AICT
%~ IFIP-WG
%~ IFIP-HWID
%~ IFIP-TC13
%~ IFIP-WG13-6
%~ IFIP-AICT-609