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Evaluation and visualizaton of evacuees' walking difficulty in disasters

机译:灾害中疏散人员行走困难的评估和可视化

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摘要

Identification of the evacuees with walking difficulty will definitely lead to quick rescue and thus improve the efficiency of evacuation in times of disasters or calamities. We are developing a new method using singular value decomposition for extracting features from the time-series data which is measured with various sensors such as an accelerometer, a motion capture system and a force sensor. In this paper, we apply this method to assess walking difficulty based on three dimensional acceleration data during walking. In order to verify the usefulness of the method, three levels of walking disability in the lower limbs are simulated by constraining the knee joint and ankle joint of the right leg. The accelerations of the middle of shanks and the back of the waist are measured and analyzed after normalization. Features related to walking difficulty are acquired from the time-series acceleration data using singular value decomposition. The results showed that the first singular values inferred from the acceleration data of the right and left shanks significantly related to the increase of the constraint to the joints. The first singular values of the shanks were suggested to be reliable criteria to evaluate walking difficulty. We propose a triangular tool to provide intuitive information extracted from the first singular values to assist the evaluation of the walking difficulty.
机译:识别出有步行困难的撤离人员肯定会导致迅速救援,从而在灾难或灾难发生时提高疏散效率。我们正在开发一种使用奇异值分解从时间序列数据中提取特征的新方法,该时间序列数据是通过各种传感器(如加速度计,运动捕捉系统和力传感器)进行测量的。在本文中,我们将这种方法基于步行过程中的三维加速度数据评估步行难度。为了验证该方法的有效性,通过约束右腿的膝盖关节和踝关节来模拟下肢的三个级别的步行残疾。归一化后,测量并分析小腿中部和腰部后部的加速度。使用奇异值分解从时间序列加速度数据中获取与行走困难相关的特征。结果表明,从右柄和左柄的加速度数据推断出的第一个奇异值与关节约束的增加显着相关。建议小腿的第一个奇异值是评估行走困难的可靠标准。我们提出了一种三角工具,以提供从第一奇异值中提取的直观信息,以帮助评估步行难度。

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