基于脑区社团结构的恐高程度识别模型

doi:10.12068/j.issn.1005-3026.2021.03.012

东北大学学报（自然科学版） ›› 2021, Vol. 42 ›› Issue (3): 381-388.DOI: 10.12068/j.issn.1005-3026.2021.03.012

基于脑区社团结构的恐高程度识别模型

王翘秀，王宏，胡佛，化成城

(东北大学机械工程与自动化学院，辽宁沈阳110819)

收稿日期:2020-03-25 修回日期:2020-03-25 接受日期:2020-03-25 发布日期:2021-03-12
通讯作者: 王翘秀
作者简介:王翘秀(1991-)，女，辽宁沈阳人，东北大学博士研究生; 王宏(1960-)，女，辽宁沈阳人，东北大学教授，博士生导师.
基金资助:
国家重点研发计划项目 (2017YFB1300300).

Recognition Model of Fear of Heights Based on Brain Region Community Structure

WANG Qiao-xiu， WANG Hong， HU Fo， HUA Cheng-cheng

School of Mechanical Engineering & Automation， Northeastern University， Shenyang 110819， China.

Received:2020-03-25 Revised:2020-03-25 Accepted:2020-03-25 Published:2021-03-12
Contact: WANG Hong
About author:-
Supported by:
-

摘要/Abstract

摘要： 高层建筑拔地而起，客观的恐高检测手段是高空作业行业规范化的关键一步.本文结合虚拟现实技术设计高空暴露实验，深入研究了恐高反应的大脑神经机制，提出使用脑功能网络检测恐高程度.通过对比不同恐高程度脑功能网络的基本拓扑特征，使用阈值化处理找出与恐高程度关系密切的脑区.根据脑区划分社团结构，构建恐高程度识别模型.结果表明:恐高程度越严重，脑功能网络越复杂.发现参与恐高反应的主要脑区包括额叶、中央区和枕叶.使用这些脑区划分社团结构，计算连接强度对恐高程度识别的准确率可达到(97.37±0.58)%.

关键词: 脑电信号;脑功能网络;社团结构;恐高;虚拟现实

Abstract: With high-rise buildings emerging， objective fear of heights detection is a key step in the standardization of the aerial work industry. Taking into account virtual reality， this paper designs an aerial exposure experiment， which studies the brain neural mechanism of fear of heights reaction， and proposes the functional brain network (FBN) to detect the fear of heights .By comparing the basic topological characteristics of FBNs， the brain regions closely related to fear of heights are found through thresholding. By dividing the community structures according to the brain regions， the recognition model of fear of heights is established . The results show that the more severe the fear of heights， the more complicated the FBN. The main brain regions involved in fear of heights include frontal lobe， central area， and occipital lobe. Using these brain regions to divide the community structures， the calculation accuracy of connection strengths on fear of heights can reach (97.37±0.58)%.

Key words: electroencephalography; functional brain network; community structure; fear of heights; virtual reality

中图分类号:

R318

王翘秀，王宏，胡佛，化成城. 基于脑区社团结构的恐高程度识别模型[J]. 东北大学学报（自然科学版）, 2021, 42(3): 381-388.

WANG Qiao-xiu， WANG Hong， HU Fo， HUA Cheng-cheng. Recognition Model of Fear of Heights Based on Brain Region Community Structure[J]. Journal of Northeastern University(Natural Science), 2021, 42(3): 381-388.

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基于脑区社团结构的恐高程度识别模型

Recognition Model of Fear of Heights Based on Brain Region Community Structure

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