Michael Brendan, Howard Matthew
Department of Informatics, King's College London, London, United Kingdom.
PLoS One. 2017 Oct 4;12(10):e0184642. doi: 10.1371/journal.pone.0184642. eCollection 2017.
Observing human motion in natural everyday environments (such as the home), has evoked a growing interest in the development of on-body wearable sensing technology. However, wearable sensors suffer from motion artefacts introduced by the non-rigid attachment of sensors to the body, and the prevailing view is that it is necessary to eliminate these artefacts. This paper presents findings that suggest that these artefacts can, in fact, be used to distinguish between similar motions, by exploiting additional information provided by the fabric motion. An experimental study is presented whereby factors of both the motion and the properties of the fabric are analysed in the context of motion similarity. It is seen that while standard rigidly attached sensors have difficultly in distinguishing between similar motions, sensors mounted onto fabric exhibit significant differences (p < 0.01). An evaluation of the physical properties of the fabric shows that the stiffness of the material plays a role in this, with a trade-off between additional information and extraneous motion. This effect is evaluated in an online motion classification task, and the use of fabric-mounted sensors demonstrates an increase in prediction accuracy over rigidly attached sensors.
在自然的日常环境（如家中）中观察人体运动，引发了人们对可穿戴式传感技术发展的日益浓厚兴趣。然而，可穿戴传感器存在因传感器与身体非刚性附着而引入的运动伪像，并且普遍观点认为有必要消除这些伪像。本文提出的研究结果表明，实际上可以通过利用织物运动提供的额外信息，利用这些伪像来区分相似的运动。本文进行了一项实验研究，在运动相似性的背景下分析了运动和织物特性的因素。可以看出，虽然标准的刚性附着传感器难以区分相似的运动，但安装在织物上的传感器表现出显著差异（p < 0.01）。对织物物理特性的评估表明，材料的刚度在其中起作用，在额外信息和无关运动之间存在权衡。在在线运动分类任务中评估了这种效果，并且使用安装在织物上的传感器相比于刚性附着的传感器，预测准确率有所提高。
