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Micro Activity Recognition of Mobile Phone Users Using Inbuilt Sensors

机译:使用内置传感器的手机用户微活动识别

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Human Activity Recognition using smartphone sensors is an area of active research. Micro activities of locomotion are indicators of higher level activities and general wellbeing of a user. In this paper, an approach for detecting a set of most common micro activities has been proposed and implemented. Five micro activities of locomotion namely sitting, standing, running, staircase ascend and descend have been considered. A two level classification model has been implemented to recognize these activities from data of inbuilt sensors of smartphone held in any of the three common positions by the user. Recognition accuracy of proposed approach is better than results reported in literature for similar problem. For purpose of training and testing, datasets have been collected on three different users and an android app has been developed to recognize activities in real time.
机译:使用智能手机传感器进行人类活动识别是一个活跃的研究领域。运动的微活动是高级活动和用户总体健康的指标。在本文中,已经提出并实现了一种用于检测一组最常见的微活动的方法。已经考虑了五个微型运动,即坐,站,跑步,楼梯上升和下降。已经实现了两级分类模型,以从用户在三个常用位置中的任何一个位置保持的智能手机内置传感器的数据中识别这些活动。提出的方法的识别精度优于文献报道的相似问题。为了进行培训和测试,已在三个不同的用户上收集了数据集,并开发了一个Android应用程序来实时识别活动。

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