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Dilemma and Solution of Traditional Feature Extraction Methods Based on Inertial Sensors

机译：基于惯性传感器的传统特征提取方法的困境与对策

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摘要

Correctly identifying human activities is very significant in modern life. Almost all feature extraction methods are based directly on acceleration and angular velocity. However, we found that some activities have no difference in acceleration and angular velocity. Therefore, we believe that for these activities, any feature extraction method based on acceleration and angular velocity is difficult to achieve good results. After analyzing the difference of these indistinguishable movements, we propose several new features to improve accuracy of recognition. We compare the traditional features and our custom features. In addition, we examined whether the time-domain features and frequency-domain features based on acceleration and angular velocity are different. The results show that (1) our custom features significantly improve the precision of the activities that have no difference in acceleration and angular velocity; and (2) the combination of time-domain features and frequency-domain features does not significantly improve the recognition of different activities.
机译：正确识别人类活动在现代生活中非常重要。几乎所有特征提取方法都直接基于加速度和角速度。但是，我们发现某些活动在加速度和角速度上没有差异。因此，我们认为，对于这些活动，任何基于加速度和角速度的特征提取方法都难以获得良好的效果。在分析了这些无法区分的运动的差异之后，我们提出了一些新功能来提高识别的准确性。我们比较传统功能和自定义功能。另外，我们检查了基于加速度和角速度的时域特征和频域特征是否不同。结果表明：（1）我们的自定义特征显着提高了运动的精度，而加速度和角速度没有差异。 （2）时域特征和频域特征的组合并不能显着提高对不同活动的识别。

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  • 来源
    《Mobile Information Systems》 |2018年第3期|2659142.1-2659142.6|共6页
  • 作者

    Peng Zhiqiang; Zhang Yue;

  • 作者单位

    Tsinghua Univ, Grad Sch Shenzhen, Div Informat Sci & Technol, Shenzhen, Peoples R China;

    Tsinghua Univ, Grad Sch Shenzhen, Div Informat Sci & Technol, Shenzhen, Peoples R China;

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