Merickel Jennifer, High Robin, Smith Lynette, Wichman Christopher, Frankel Emily, Smits Kaitlin, Drincic Andjela, Desouza Cyrus, Gunaratne Pujitha, Ebe Kazutoshi, Rizzo Matthew
University of Nebraska Medical Center, College of Medicine, Department of Neurological Sciences 988440 Nebraska Medical Center, Omaha, NE, 68198.
University of Nebraska Medical Center, College of Public Health, Biostatistics 984355 Nebraska Medical Center, Omaha, NE, 68198.
Int J Automot Eng. 2019;10(1):34-40. doi: 10.20485/jsaeijae.10.1_34. Epub 2019 Feb 4.
Our goal is to address the need for driver-state detection using wearable and in-vehicle sensor measurements of driver physiology and health. To address this goal, we deployed in-vehicle systems, wearable sensors, and procedures capable of quantifying real-world driving behavior and performance in at-risk drivers with insulin-dependent type 1 diabetes mellitus (DM). We applied these methodologies over 4 weeks of continuous observation to quantify differences in real-world driver behavior profiles associated with physiologic changes in drivers with DM (N=19) and without DM (N=14). Results showed that DM driver behavior changed as a function of glycemic state, particularly hypoglycemia. DM drivers often drive during at-risk physiologic states, possibly due to unawareness of impairment, which in turn may relate to blunted physiologic responses (measurable heart rate) to hypoglycemia after repeated episodes of hypoglycemia. We found that this DM driver cohort has an elevated risk of crashes and citations, which our results suggest is linked to the DM driver's own momentary physiology. Overall, our findings demonstrate a clear link between at-risk driver physiology and real-world driving. By discovering key relationships between naturalistic driving and parameters of contemporaneous physiologic changes, like glucose control, this study directly advances the goal of driver-state detection through wearable physiologic sensors as well as efforts to develop "gold standard" metrics of driver safety and an individualized approach to driver health and wellness.
我们的目标是通过对驾驶员生理和健康状况进行可穿戴及车载传感器测量,来满足对驾驶员状态检测的需求。为实现这一目标,我们部署了能够量化胰岛素依赖型1型糖尿病(DM)高危驾驶员在现实世界中的驾驶行为和表现的车载系统、可穿戴传感器及相关程序。我们将这些方法应用于连续4周的观察中,以量化与患有DM(N = 19)和未患DM(N = 14)的驾驶员生理变化相关的现实世界驾驶员行为特征差异。结果表明,DM驾驶员的行为会随着血糖状态,尤其是低血糖状态而变化。DM驾驶员常在生理风险状态下驾驶,这可能是由于对身体损伤缺乏认知,而这又可能与反复发生低血糖后对低血糖的生理反应(可测量的心率)迟钝有关。我们发现,这一DM驾驶员群体发生撞车和违规的风险较高,我们的研究结果表明这与DM驾驶员自身的瞬时生理状况有关。总体而言,我们的研究结果表明高危驾驶员的生理状况与现实世界中的驾驶行为之间存在明显联系。通过发现自然驾驶与同期生理变化参数(如血糖控制)之间的关键关系,本研究直接推动了通过可穿戴生理传感器进行驾驶员状态检测的目标,以及制定驾驶员安全“金标准”指标和个性化驾驶员健康与福祉方法的努力。