驾驶模拟器中同步生理和行为传感器

R. Taib, Benjamin Itzstein, Kun Yu
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引用次数: 2

摘要

通过结合生理、行为和环境信号,可以实现准确和噪声稳健的多模式活动和精神状态监测。这在辅助驾驶技术中尤其有前景,因为现在的车辆配备了从车轮和踏板活动到声音和眼睛追踪的传感器。然而,在实践中,由于传感、获取和存储系统的多样性,多模态用户研究面临着具有挑战性的数据收集和同步问题。参考当前在驾驶模拟器中认知负荷测量的研究,本文描述了我们使用轨道测量库(OML)框架,结合电影板的多模态版本,持续收集和同步信号所采取的步骤。结果数据以结构化格式自动存储在网络数据库中,包括有关数据和实验的元数据。此外,在没有额外硬件的情况下,提供了所有信号之间的细粒度同步,并且可以事后纠正时钟漂移。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Synchronising Physiological and Behavioural Sensors in a Driving Simulator
Accurate and noise robust multimodal activity and mental state monitoring can be achieved by combining physiological, behavioural and environmental signals. This is especially promising in assistive driving technologies, because vehicles now ship with sensors ranging from wheel and pedal activity, to voice and eye tracking. In practice, however, multimodal user studies are confronted with challenging data collection and synchronisation issues, due to the diversity of sensing, acquisition and storage systems. Referencing current research on cognitive load measurement in a driving simulator, this paper describes the steps we take to consistently collect and synchronise signals, using the Orbit Measurement Library (OML) framework, combined with a multimodal version of a cinema clapperboard. The resulting data is automatically stored in a networked database, in a structured format, including metadata about the data and experiment. Moreover, fine-grained synchronisation between all signals is provided without additional hardware, and clock drift can be corrected post-hoc.
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