Using Brain-Computer Interfaces to Improve Multitasking in Driving
Liang, Calvin.
2018
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Abstract: Previous
research has sought to understand and mitigate deteriorating performance during
multitasking while driving, but there have not been any proposed solutions. Our system
is an adaptive reading interface that builds upon implicit interface work to improve
driving performance in multitasking situations - as well as the overall multitasking
experience. This thesis demonstrates a ... read moreproof-of-concept closed-loop solution for
multitasking while driving and tests its usability through a preliminary study. Our
study involved a functional near-infrared spectroscopy (fNIRS) device, driving
simulator, and adaptive reading interface. The fNIRS device monitors brain activity and
triggers expansion of the reading interface in response to brain activity evoked by the
challenges presented by the driving simulation. While this is preliminary research,
future work can build upon our contributions. In doing so, this research will provide
insight into how to diminish the effects of task-switching while
driving.
Thesis (M.S.)--Tufts University, 2018.
Submitted to the Dept. of Mechanical Engineering.
Advisor: James Intriligator.
Committee: Rob Jacob, and Nathan Ward.
Keywords: Mechanical engineering, Computer science, and Psychology.read less - ID:
- pc289w893
- Component ID:
- tufts:25049
- To Cite:
- TARC Citation Guide EndNote
