Banos Oresti, Toth Mate Attila, Damas Miguel, Pomares Hector, Rojas Ignacio
Department of Computer Architecture and Computer Technology, Research Center for Information and Communications Technologies-University of Granada (CITIC-UGR), C/Calle Periodista RafaelGomez Montero 2, Granada E18071, Spain.
Language and Speech Laboratory, University of the Basque Country, Paseo de la Universidad 5,Vitoria E01006, Spain.
Sensors (Basel). 2014 Jun 6;14(6):9995-10023. doi: 10.3390/s140609995.
Most wearable activity recognition systems assume a predefined sensor deployment that remains unchanged during runtime. However, this assumption does not reflect real-life conditions. During the normal use of such systems, users may place the sensors in a position different from the predefined sensor placement. Also, sensors may move from their original location to a different one, due to a loose attachment. Activity recognition systems trained on activity patterns characteristic of a given sensor deployment may likely fail due to sensor displacements. In this work, we innovatively explore the effects of sensor displacement induced by both the intentional misplacement of sensors and self-placement by the user. The effects of sensor displacement are analyzed for standard activity recognition techniques, as well as for an alternate robust sensor fusion method proposed in a previous work. While classical recognition models show little tolerance to sensor displacement, the proposed method is proven to have notable capabilities to assimilate the changes introduced in the sensor position due to self-placement and provides considerable improvements for large misplacements.
大多数可穿戴活动识别系统都假定有一个预定义的传感器部署，该部署在运行时保持不变。然而，这一假设并不能反映现实生活中的情况。在这类系统的正常使用过程中，用户可能会将传感器放置在与预定义传感器放置位置不同的位置。此外，由于固定不牢，传感器可能会从其原始位置移动到另一个位置。基于给定传感器部署的活动模式特征训练的活动识别系统可能会因传感器位移而失败。在这项工作中，我们创新性地探讨了由传感器的故意误放和用户自行放置所引起的传感器位移的影响。针对标准活动识别技术以及先前工作中提出的一种替代的鲁棒传感器融合方法，分析了传感器位移的影响。虽然经典识别模型对传感器位移的容忍度很小，但所提出的方法被证明具有显著的能力来吸收由于自行放置而在传感器位置引入的变化，并为大的误放提供了相当大的改进。
