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Unobtrusive physiological monitoring in an airplane seat

机译:飞机座椅的生理监测

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Air travel has become the preferred mode of long-distance transportation for most of the world's travelers. People of every age group and health status are traveling by airplane and thus the airplane has become part of our environment, in which people with health-related limitations need assistive support. Since the main interaction point between a passenger and the airplane is the seat, this work presents a smart airplane seat for measuring health-related signals of a passenger. We describe the design, implementation and testing of a multimodal sensor system integrated into the seat. The presented system is able to measure physiological signals, such as electrocardiogram, electrodermal activity, skin temperature, and respiration. We show how the design of the smart seat system is influenced by the trade-off between comfort and signal quality, I.e. incorporating unobtrusive sensors and dealing with erroneous signals. Artifact detection through sensor fusion is presented and the working principle is shown with a feasibility study, in which normal passenger activities were performed. Based on the presented method, we are able to identify signal regions in which the accuracies for detecting the heart- and respiration-rate are 88 and 82%, respectively, compared to 40 and 76% without any artifact removal.
机译:空中旅行已成为世界上大多数旅行者的首选长途运输方式。每个年龄段和健康状况的人都在乘飞机旅行,因此飞机已成为我们环境的一部分,在这个环境中,与健康相关的限制人士需要协助。由于乘客和飞机之间的主要交互点是座位,因此这项工作提出了一种智能飞机座位,用于测量乘客的健康相关信号。我们描述了集成到座椅中的多模式传感器系统的设计,实施和测试。所提出的系统能够测量生理信号,例如心电图,皮肤电活动,皮肤温度和呼吸。我们展示了智能座椅系统的设计如何受舒适度和信号质量之间的折衷影响,即结合了不显眼的传感器并处理了错误的信号。提出了通过传感器融合进行伪像检测,并通过可行性研究显示了工作原理,在该研究中,进行了正常的乘客活动。基于提出的方法,我们能够识别出检测心跳和呼吸频率的准确度分别为88%和82%的信号区域,而没有任何伪影去除的准确率分别为40%和76%。

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