Learning Multiple Band-Pass Filters for Sleep Stage Estimation: Towards Care Support for Aged Persons
Learning Multiple Band-Pass Filters for Sleep Stage Estimation: Towards Care Support for Aged Persons
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学习用于睡眠阶段估计的多个带通滤波器：为老年人提供护理支持
DOI：
10.1587/transcom.e93.b.811
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发表时间：
2010
期刊：
影响因子：
--
通讯作者：
Nobuo Nakajima
中科院分区：
文献类型：
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作者：
K. Takadama;K. Hirose;H. Matsushima;K. Hattori;Nobuo Nakajima
本文提出了一种睡眠阶段估计方法，无需将任何设备连接到人体即可为每个人提供准确的估计。特别是，我们的方法学习适当的多个带通滤波器来提取心跳的特定波形，这是估计睡眠阶段所需的。为了准确估计，本文采用学习分类器系统（LCS）作为数据挖掘技术，并将其扩展到估计睡眠阶段。对五名混合健康受试者的广泛实验证实了以下含义：（1）所提出的方法可以提供比传统方法更准确的睡眠阶段估计，（2）无论受试者的身体状况如何，所提出的方法计算的睡眠阶段估计都是稳健的。
This paper proposes the sleep stage estimation method that can provide an accurate estimation for each person without connecting any devices to human's body. In particular, our method learns the appropriate multiple band-pass filters to extract the specific wave pattern of heartbeat, which is required to estimate the sleep stage. For an accurate estimation, this paper employs Learning Classifier System (LCS) as the data-mining techniques and extends it to estimate the sleep stage. Extensive experiments on five subjects in mixed health confirm the following implications: (1) the proposed method can provide more accurate sleep stage estimation than the conventional method, and (2) the sleep stage estimation calculated by the proposed method is robust regardless of the physical condition of the subject.