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Recognition of a variety of activities considering smartphone positions

机译：考虑智能手机职位的各种活动的认识

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摘要

We present a high-accuracy recognition method for various activities using smartphone sensors based on device positions. Many researchers have attempted to estimate various activities, particularly using sensors such as the built-in accelerometer of a smartphone. Considerable research has been conducted under conditions such as placing a smartphone in a trouser pocket; however, few have focused on the changing context and influence of the smartphone position. Herein, we present a method for recognising seven types of activities considering three smartphone positions, and conducted two experiments to estimate each activity and identify the actual state under continuous movement at a university campus. The results indicate that the seven states can be classified with an average accuracy of 98.53% for three different smartphone positions. We also correctly identified these activities with 91.66% accuracy. Using our method, we can create practical services such as healthcare applications with a high degree of accuracy.
机译：我们基于设备位置使用智能手机传感器的各种活动提出了一种高精度识别方法。许多研究人员试图估算各种活动，特别是使用智能手机的内置加速度计等传感器。在将智能手机放在裤子口袋中的条件下进行了相当大的研究;然而，很少有人专注于改变的上下文和智能手机位置的影响。在此，我们提出了一种考虑三种智能手机位置的七种类型的方法，并进行了两个实验来估计每项活动，并在大学校园的连续运动下确定实际状态。结果表明，七种州的平均准确性为3个不同的智能手机位置的平均精度为98.53％。我们还正确地确定了这些活动，准确性为91.66％。使用我们的方法，我们可以创建具有高精度的医疗保健应用等实用服务。

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