Sleep stage estimation by evolutionary computation using heartbeat data and body-movement
Sleep stage estimation by evolutionary computation using heartbeat data and body-movement
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使用心跳数据和身体运动通过进化计算估计睡眠阶段
DOI：
10.4156/ijact.vol4.issue22.31
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发表时间：
2012
期刊：
影响因子：
--
通讯作者：
K. Takadama
中科院分区：
文献类型：
--
作者：
H. Matsushima;K. Hirose;K. Hattori;Hiroyuki Sato;K. Takadama
本文着重于REM阶段（即，浅睡眠）和非REM阶段（即，深睡眠），并通过采用这种独特变化的特征来改进我们的睡眠估计方法。特别是，在REM阶段心率不规则地增加，而在非REM阶段心率降低。在REM阶段，身体活动剧烈，而在Non-REM阶段，身体活动不频繁。使用这种独特的变化，我们提出了一个新的适应度函数，确定REM/非REM阶段，并将其引入到我们的睡眠估计方法的基础上遗传算法（GAs），进化的睡眠阶段为每个人根据健身。要调查一个新的适应度函数的有效性，我们比较估计的睡眠阶段，我们的方法采用建议的适应度函数与渡边的方法作为传统的方法。实验结果表明，我们的方法采用建议的健身功能有能力估计的睡眠阶段准确比渡边的方法，而无需连接任何设备。
This paper focuses on distinctive changes of not only the heart rate but also the body movement in REM stage (i.e., light sleep) and Non-REM stage (i.e., deep sleep) and improves our sleep estimation method by employing the feature of such distinctive changes. In particular, the heart rate increases irregularly in REM stage, while the heart rate decreases in Non-REM stage. The body moves intensively in REM stage, while the body does not frequently move in Non-REM stage. Using such distinctive changes, we propose a new fitness function which determines the REM/Non-REM stage and introduce it into for our sleep estimation method based on Genetic Algorithms (GAs), which evolve the sleep stage for each person according to the fitness. To investigate an effectiveness of a new fitness function, we compare the estimated sleep stages of our method employing the proposed fitness function with that of Watanabe’s method as the conventional method. The experimental results suggest that our method employing the proposed fitness function has a capability to estimate the sleep stage accurately than Watanabe’s method without connecting any devices.