基于心率传感器的睡眠时间估计的有效午睡支持系统

Daichi Nagata, Yutaka Arakawa, Takatomi Kubo, K. Yasumoto
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引用次数: 3

摘要

在日常生活中,睡眠不足是注意力不集中的主要原因之一。为了支持有效的午睡,被认为是恢复睡眠不足和提高用户注意力的好方法之一,我们提出了一个使用心率传感器的睡眠时间估计。由于心率传感器已经很普遍,我们的方法可以在我们的日常生活中广泛而方便地使用。大多数现有的睡眠支持系统旨在通过观察睡眠阶段来提供一个舒适的唤醒。与这些方法不同,我们的目标是通过估计睡眠时间来提供适当的睡眠时间。通过使用各种心率传感器、现有睡眠支持系统和64ch脑电图,我们试图找出小睡时各种生命信号与睡眠阶段的关系。最后,利用机器学习技术建立了睡眠时间估计模型。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Effective napping support system by hypnagogic time estimation based on heart rate sensor
In daily life, lack of sleep is one of the main reasons for poor concentration. To support an effective napping, considered as one of good methods for recovering insufficient sleep and enhancing a user's concentration, we propose a hypnagogic time estimation using a heart rate sensor. Because a heart rate sensor has already been common, our method can be used widely and easily in our daily life. Most of existing sleep support systems aim to provide a comfortable wake-up by observing the sleep stage. Unlike these methods, we aim to provide an appropriate sleep duration by estimating a hypnagogic timing. By using various heart rate sensors, existing sleep support systems and 64ch electroencephalography, we tried to find out the relationship between various vital signals and sleep stages during a napping. Finally, we build a hypnagogic time estimation model by using the machine learning technique.
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