SGER: Exploratory Research to Diagnose Dementia from Vehicle Operation Data

SGER：根据车辆操作数据诊断痴呆症的探索性研究

• 批准号: 0302255
• 负责人: Roman Kuc
• 金额: $ 10万
• 依托单位: Yale University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2003
• 资助国家: 美国
• 起止时间: 2003-05-01 至 2005-10-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0302255&HistoricalAwards=false
• 关键词: SGER; Exploratory; Research; Diagnose; Dementia

0302255KucThis research explores the feasibility of diagnosing and monitoring an operator's state of dementia by characterizing on-road operation of a vehicle. Five elements comprise the research plan: the human transfer function, vehicle operation data, dementia modeling, measures extracted from data that correlate with dementia model parameter values, and an experimental means to assess the performance of the methods.The experiments involve normal volunteers (engineering undergraduates who assist in the conduct of the research) drive an electric scooter equipped with sensors to monitor vehicle location, speed, acceleration, and direction; position of nearby objects; and, the driver's actions in controlling the scooter joystick. The scooter can also be programmed to modify the driver's actions, as if the driver had dementia. Signal processing procedures extract features in the driving data that correlate with dementia, which include slowed reaction speed, poor judgment and inappropriate actions. In these experiments the "correct answer" is known because the "dementia simulator" mimics slowed reaction speed by introducing a delay in the joystick control. Similar random modifications in the joystick signals simulate poor judgment and inappropriate actions. The vehicle then illustrates the degradation of driving behavior as the degree of dementia increases. Preliminary scooter results and computer simulations verify this claim. Results of the research are expected to be reported in the IEEE Transactions on Biomedical Engineering and the IEEE Transactions on Robotics and Automation for the engineering community, and the Journal of the American Geriatrics Society for the clinical community.

0302255 KucThis研究探讨了诊断和监测运营商的状态的痴呆症的车辆的道路上运行的特点的可行性。研究计划包括五个要素：人类传递函数、车辆操作数据、痴呆建模、从与痴呆模型参数值相关的数据中提取的测量，以及评估方法性能的实验手段。（协助进行研究的工程专业本科生）驾驶一辆配备有传感器的电动踏板车，以监测车辆位置，速度，加速度和方向;附近物体的位置;以及驾驶员在控制踏板车操纵杆时的动作。踏板车还可以被编程来修改驾驶员的行为，就好像驾驶员患有痴呆症一样。信号处理程序提取驾驶数据中与痴呆症相关的特征，包括反应速度减慢，判断力差和不适当的行动。在这些实验中，“正确答案”是已知的，因为“痴呆症模拟器”通过在操纵杆控制中引入延迟来模仿减慢的反应速度。操纵杆信号中类似的随机修改模拟了糟糕的判断和不适当的行动。然后，车辆说明了随着痴呆程度的增加，驾驶行为的退化。初步的滑板车结果和计算机模拟验证了这一说法。 研究结果预计将在工程界的IEEE生物医学工程学报和IEEE机器人与自动化学报以及临床界的美国老年病学会杂志上发表。