减少传感器定向变量的影响在人类活动识别中,使用一致的参考系统
Manuel Gil-Martín1, Javier López-Iniesta1, Fernando Fernández-Martínez1
1Speech Technology and Machine Learning, Information Processing and Telecommunications Center, E.T.S.I. de Telecomunicación, Universidad Politécnica de Madrid, 28040 Madrid, Spain.
Sensors (Basel, Switzerland)
|July 14, 2023
概括
传感器方向的变化显著影响人类活动识别 (HAR) 系统. 本研究引入了一个预处理模块,该模块建立了一个一致的参考系统,转换三轴信号以减轻定向错误并提高HAR准确性.
科学领域:
- 计算机科学 计算机科学
- 机器学习 机器学习
- 信号处理 信号处理
背景情况:
- 传感器的定位对于使用三轴信号进行准确的人类活动识别 (HAR) 是至关重要的.
- 传感器位置的变化引入了重大错误,降低了HAR系统的性能.
研究的目的:
- 开发和评估一种新的预处理模块,以解决HAR中的传感器方向变化.
- 为了提高HAR系统的稳定性和准确性,尽管传感器的方向不一致.
主要方法:
- 一个预处理模块被设计用于估计一个一致的参考系统.
- 三轴传感器信号被转化为这个参考系统.
- 该方法在六个不同的HAR数据集中使用主体智能交叉验证进行了验证.
主要成果:
- 拟议的模块有效地减轻了传感器方向变化对HAR准确度的负面影响.
- 即使在传感器方向发生突然变化时,也可以实现强大的HAR性能.
- 在WISDM数据集上,精度从89.19%恢复到91.46%,与一致的定向相匹配的性能.
结论:
- 开发的预处理模块在现实场景中显著提高了HAR系统的可靠性.
- 这种方法为部署HAR系统提供了一个实用的解决方案,在这些系统中,传感器的方向不能被严格控制.
- 该方法在多个数据集的分类准确性方面取得了实质性的改进.
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