首页> 外文会议>International Conference on Computer Engineering and Technology;ICCET 2010 >Multi-parametric Analysis of Sensory Data Collected from Automotive Drivers for Building a Safety-Critical Wearable Computing System
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Multi-parametric Analysis of Sensory Data Collected from Automotive Drivers for Building a Safety-Critical Wearable Computing System

机译:从汽车驾驶员收集的用于建立安全关键型可穿戴计算系统的感官数据的多参数分析

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We present a methodology and an off-line analysis of data collected from several body-mounted sensors for automotive drivers during multiple fixed-route,segmented driving on real roads. This analysis was used for a range of preliminary processes including those related but not limited to stress detection. It also attempts to illustrate cases of several drivers for whom the real-time data acquisition was carried out through online physiological sensors. This analysis is to be used to designing and building a wearable computer involving Body Sensor Network for avoiding road accidents. In order to estimate the mental and physical fatigue to which a driver may be subjected to,we collected GSR,SpO2,Respiration,and ECG signals during relaxed and stressful driving scenarios.
机译:我们提供了一种方法和离线分析,这些数据是从在多个固定路线上,在实际道路上的分段驾驶期间从汽车驾驶员的几个车载传感器收集的数据得出的。该分析用于一系列初步过程,包括相关但不限于压力检测的那些过程。它还试图说明通过在线生理传感器对其进行实时数据采集的几个驾驶员的情况。该分析将用于设计和构建涉及人体传感器网络的可穿戴计算机,以避免发生道路事故。为了估计驾驶员可能遭受的精神和身体疲劳,我们在放松和压力驾驶的情况下收集了GSR,SpO2,呼吸和ECG信号。

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