A Methodological Review of fNIRS in Driving Research: Relevance to the Future of Autonomous Vehicles

Author:

Balters Stephanie,Baker Joseph M.,Geeseman Joseph W.,Reiss Allan L.

Abstract

As automobile manufacturers have begun to design, engineer, and test autonomous driving systems of the future, brain imaging with functional near-infrared spectroscopy (fNIRS) can provide unique insights about cognitive processes associated with evolving levels of autonomy implemented in the automobile. Modern fNIRS devices provide a portable, relatively affordable, and robust form of functional neuroimaging that allows researchers to investigate brain function in real-world environments. The trend toward “naturalistic neuroscience” is evident in the growing number of studies that leverage the methodological flexibility of fNIRS, and in doing so, significantly expand the scope of cognitive function that is accessible to observation via functional brain imaging (i.e., from the simulator to on-road scenarios). While more than a decade’s worth of study in this field of fNIRS driving research has led to many interesting findings, the number of studies applying fNIRS during autonomous modes of operation is limited. To support future research that directly addresses this lack in autonomous driving research with fNIRS, we argue that a cogent distillation of the methods used to date will help facilitate and streamline this research of tomorrow. To that end, here we provide a methodological review of the existing fNIRS driving research, with the overarching goal of highlighting the current diversity in methodological approaches. We argue that standardization of these approaches will facilitate greater overlap of methods by researchers from all disciplines, which will, in-turn, allow for meta-analysis of future results. We conclude by providing recommendations for advancing the use of such fNIRS technology in furthering understanding the adoption of safe autonomous vehicle technology.

Publisher

Frontiers Media SA

Subject

Behavioral Neuroscience,Biological Psychiatry,Psychiatry and Mental health,Neurology,Neuropsychology and Physiological Psychology

Reference95 articles.

1. Exploring neuro-physiological correlates of drivers’ mental fatigue caused by sleep deprivation using simultaneous eeg, ecg, and fnirs data.;Ahn;Frontiers in human neuroscience,2016

2. Portable functional neuroimaging as an environmental epidemiology tool: a how-to guide for the use of fnirs in field studies.;Baker;Environmental health perspectives,2017

3. “Learning-by-doing: using near infrared spectroscopy to detect habituation and adaptation in automated driving,” in;Balters;Proceedings of the 9th International Conference on Automotive User Interfaces and Interactive Vehicular Applications (ACM),2017

4. “Intelligent driver monitoring systems based on physiological sensor signals: A review,” in;Begum;Proceedings of the 16th International IEEE Conference on Intelligent Transportation Systems (ITSC 2013),2013

5. Update of fnirs as an input to brain–computer interfaces: A review of research from the tufts human–computer interaction laboratory.;Bosworth;Photonics,2019

Cited by 12 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3