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野外条件下汽车驾驶过程中与适度精神负荷相关的生理反应。

Physiological responses related to moderate mental load during car driving in field conditions.

作者信息

Wiberg Henrik, Nilsson Emma, Lindén Per, Svanberg Bo, Poom Leo

机构信息

Volvo Car Corporation, Research and Development, Gothenburg, Sweden.

Volvo Car Corporation, Research and Development, Gothenburg, Sweden.

出版信息

Biol Psychol. 2015 May;108:115-25. doi: 10.1016/j.biopsycho.2015.03.017. Epub 2015 Apr 6.

Abstract

We measured physiological variables on nine car drivers to capture moderate magnitudes of mental load (ML) during driving in prolonged and repeated city and highway field conditions. Ecological validity was optimized by avoiding any artificial interference to manipulate drivers ML, drivers were alone in the car, they were free to choose their paths to the target, and the repeated drives familiarized drivers to the procedure. Our aim was to investigate if driver's physiological variables can be reliably measured and used as predictors of moderate individual levels of ML in naturally occurring unpredictably changing field conditions. Variables investigated were: heart-rate, skin conductance level, breath duration, blink frequency, blink duration, and eye fixation related potentials. After the drives, with support from video uptakes, a self-rating and a score made by external raters were used to distinguish moderately high and low ML segments. Variability was high but aggregated data could distinguish city from highway drives. Multivariate models could successfully classify high and low ML within highway and city drives using physiological variables as input. In summary, physiological variables have a potential to be used as indicators of moderate ML in unpredictably changing field conditions and to advance the evaluation and development of new active safety systems.

摘要

我们对九名汽车驾驶员的生理变量进行了测量,以获取在长时间重复的城市和高速公路实地驾驶条件下中等程度的心理负荷(ML)。通过避免任何人为干扰来操纵驾驶员的心理负荷,优化了生态效度,驾驶员独自在车内,他们可以自由选择前往目的地的路线,并且重复驾驶使驾驶员熟悉了该过程。我们的目的是研究在自然发生的不可预测变化的实地条件下,驾驶员的生理变量是否能够被可靠地测量,并用作中等个体心理负荷水平的预测指标。所研究的变量包括:心率、皮肤电导水平、呼吸持续时间、眨眼频率、眨眼持续时间以及与眼注视相关的电位。驾驶结束后,在视频记录的支持下,使用自我评分和外部评分者给出的分数来区分中等程度的高心理负荷和低心理负荷时段。变异性很高,但汇总数据能够区分城市驾驶和高速公路驾驶。多变量模型能够使用生理变量作为输入,成功地在高速公路驾驶和城市驾驶中对高心理负荷和低心理负荷进行分类。总之,生理变量有潜力在不可预测变化的实地条件下用作中等心理负荷的指标,并推动新型主动安全系统的评估和开发。

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