移动通信2025，Vol.49Issue(3)：107-116,10.DOI:10.3969/j.issn.1006-1010.20241125-0003
基于内生智能脑机接口技术的虚拟仿真实验设计与专注度分析
Attention State Detection Based on Brain-Computer Interface and Network Endogenous Intelligence with Simulated Experiments
摘要
Abstract
Brain-computer interface technology provides a novel method for brain and human perception in future communication networks,enabling bidirectional empowerment with network endogenous intelligence.This paper uses attention analysis based on brain-computer interface as an entry point to deeply explore attention state detection capabilities.First,we propose a neural network-based attention state detection algorithm that applies attention mechanisms and convolution techniques to efficiently extract complex features of electroencephalogram signals in temporal,frequency,and spatial(acquisition channel)domains.Then,12 subjects were recruited to participate in virtual simulation experiments designed for electric power inspection scenarios,where data comparing attentive and non-attentive states were collected from each subject for subsequent algorithm model training and testing.Results demonstrate that the proposed algorithm achieves higher accuracy in attention state recognition compared to four traditional electroencephalogram signal processing algorithms.This work explores the integration of virtual simulation experiments with brain-computer interface technology.The proposed method shows promise for further deployment on future endogenous intelligence computing hardware,providing support for efficient operation of integrated brain-computer interface-network systems.关键词
脑机接口/内生智能/专注度检测/神经网络算法/仿真实验Key words
brain-computer interface/endogenous intelligence/attention state detection/artificial neural network/simulated experiment分类
信息技术与安全科学引用本文复制引用
吴巨爱,王振宇,陈春超,张腾飞,宋宁..基于内生智能脑机接口技术的虚拟仿真实验设计与专注度分析[J].移动通信,2025,49(3):107-116,10.基金项目
江苏省自然科学基金(BK20230369) （BK20230369）
