欢迎访问《汽车安全与节能学报》,

JASE ›› 2019, Vol. 10 ›› Issue (4): 433-442.DOI: 10.3969/j.issn.1674-8484.2019.04.004

• 汽车安全 • 上一篇    下一篇

基于驾驶模拟器和 fNIRS 的与晕动病相关脑活动区的差异性

张晨阳1,4,李曙光*2,4,李耀华3,姚进1,祝磊1,王敏    

  1. (1. 四川大学 机械工程学院,成都 610065,中国;2
    . 电子科技大学 自动化工程学院,成都 611731,中国;
     3. 成都市第一人民医院,成都 610000,中国; 
    4. 汽车安全与节能国家重点实验室,清华大学,北京 100084,中国)
  • 收稿日期:2019-03-22 出版日期:2019-12-31 发布日期:2020-01-01
  • 通讯作者: 李曙光(1986—),男(汉),四川,副研究员。E-mail: lsg042@163.com。
  • 作者简介:第一作者 / First author : 张晨阳(1993—),男(汉),四川,硕士研究生。E-mail: 18523507789@163.com。
  • 基金资助:
    汽车安全与节能国家重点实验室开放基金资助项目(KF1802)。

Differences of the motion sickness associated brain activity regions based on the driving simulator and fNIRS

ZHANG Chenyang1,4, LI Shuguang*2,4, LI Yaohua3, YAO Jin1, ZHU Lei1, WANG Min1   

  1. (1. School of Mechanical Engineering, Sichuan University, Chengdu 610065, China; 
    2. School of Automation Engineering, University of Electronic Science and Technology of China, Chengdu 611731, China; 
    3. Chengdu first people’s Hospital, Chengdu 610000, China; 
    4. The State Key Laboratory of Automotive Safety and Energy, Tsinghua University, Beijing 100084, China)
  • Received:2019-03-22 Online:2019-12-31 Published:2020-01-01

摘要: 为研发车辆自动驾驶技术,需探究自动驾驶的汽车和电动汽车上出现的晕动病的发病机理。 基于六自由度驾驶模拟器和非侵入式功能性近红外光谱技术(fNIRS),实验中设计了直线工况的实 验道路,直行工况下收集了52 位参与者的驾驶时间和距离等驾驶数据以及大脑的氧合血红蛋白浓度 变化值,并对驾驶数据与大脑数据进行差异性分析。结果表明:大脑区域的活跃度按 BA6、BA17 和 BA18 区域最活跃,接着是 BA1、BA2、BA3 和BA4区域,最后是 BA8、BA10 和BA40 区域依次 递减;直行工况下与晕动病相关的大脑 Brodmann区域会有不同的反应。该结果有助于从大脑的角度 研究晕动病。

关键词: 自动驾驶车辆, 脑活动, 晕动病, 驾驶模拟器, 功能性近红外光谱技术(fNIRS)

Abstract: The pathogenesis of motion sickness which appears on automated vehicles and electric vehicles needs to be explored to develop autonomous driving. The driving data, including driving time and distance, and cerebral oxygen exchange from 52 participants under the straight driving were collected and their differences were analyzed, based on the six-degree-of freedom driving simulator platform and noninvasive Functional NearInfrared Spectroscopy (fNIRS). The results show that the BA6, BA17 and BA18 areas of brain have the highest degree of activity, followed by the BA1, BA2, BA3 and BA4 areas, while the BA8, BA10 and BA40 areas are in the decreasing order. Brain Brodmann areas differ which are associated with motion sickness under the straight driving. These results will be helpful to have a better understood of the motion sickness from the perspective of the brain.

Key words: automated vehicles, brain activity, motion sickness, driving simulator, functional near-infrared spectroscopy (fNIRS)