Analysis of Breathing Rate in a Multi-Scenario Driving Acquisition

2023 27th International Conference Information Visualisation (IV)(2023)

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摘要
Distracted driving is a major cause of traffic accidents. Drivers undergoing cognitive and physical stress are not only factors that distract drivers from the task of driving but can also affect a person's long-term health. This work investigates the effect of distracted driving on body vital signs, specifically on breathing rate. Details of a recent experiment where subjects are asked to drive in a simulator while also being asked to perform various cognitively demanding or stressful tasks are provided. As part of a larger study on driver distraction, fatigue, and cognitive load, the primary focus of this work is on identifying a correlation between breathing rate variability during different stages of the experiment and examining how this change in breathing rate may differ between participants. Some of the tasks included in the data acquisition were participants being exposed to white noise and random news clips asked to answer questions or using their smartphones to look for directions. Other tasks included driving without distraction to provide a baseline cognitive level. Analysis of this data using visualization showed a clear correlation between breathing rate variability and cognitive demand of the experiment tasks. Thus, this study emphasizes the importance of non-contact driver cognitive load monitoring to help reduce accidents and increase road safety. This paper presents a method of analysis and is the first documentation of this data acquisition presented in the literature.
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关键词
breathing rate estimation,ground truth annotation,driving analysis,stress,cognitive load
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