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Recognition of Walking Activities Using Wireless Inertial and Orientation Sensors: A Performance Evaluation

机译:使用无线惯性和方向传感器识别步行活动:性能评估

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In this paper, we evaluate experimentally several methods for recognizing walking activities using on-body wireless nodes equipped with inertial and orientation sensors. The walking activities (walking on flat surfaces, uphill and down-hill, upstairs and downstairs) are selected by healthcare experts as being relevant for elderly patients suffering from Chronic Obstructive Pulmonary Disease (COPD). We target specifically recognition methods that operate with time-domain features only, due to the limitations of sensor nodes in terms of computational power, memory and energy. The results show that among all sensors the compass sensor performs best regardless of the classification method. Both the compass and gyroscope sensors outperform significantly the accelerometer sensor, which is typically used in previous related work. The best trade-off in performance vs. time complexity is obtained by fusing the gyroscope and compass information, with an overall accuracy of 91percent.
机译:在本文中,我们通过配备有惯性和方向传感器的身体无线节点来评估实验几种方法来识别步行活动。步行活动(在平坦的表面上行走,上坡,楼上和楼下)由医疗保健专家选择与患有慢性阻塞性肺病(COPD)的老年患者相关。我们针对仅在计算功率,存储器和能量方面的传感器节点的限制,仅针对仅使用时域特征进行操作的识别方法。结果表明,无论分类方法如何,罗盘传感器都能最佳地执行。罗盘和陀螺仪传感器都显着优于加速度计传感器,这通常在先前的相关工作中使用。通过融合陀螺仪和指南针信息,可以获得最佳折衷的性能与时间复杂度,整体准确性为91%。

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