issleep:一个智能手机系统,用于不显眼的睡眠质量监测

Xiangmao Chang, Cheng Peng, G. Xing, Tian Hao, Gang Zhou
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引用次数: 9

摘要

睡眠质量是保持健康生活方式的重要因素。在设计睡眠监测系统方面已经做了大量的工作。然而,由于对设备内部加速度计传感器的探索,现有的解决方案大多或多或少地给用户带来了侵扰。这篇文章介绍了issleep——一个实用的系统,可以用现成的智能手机监测人们的睡眠质量。issleep通过智能手机内置的麦克风来检测与睡眠质量密切相关的事件,并推断出睡眠质量的定量指标。issleep采用轻量级决策树算法对各种事件进行分类。对于双用户场景,issleep区分两个用户的事件,两部手机可以相互协作,两部手机不能相互通信。实验结果表明,issleep在单用户场景下各种不同设置下的事件分类准确率始终保持在90%以上,在双用户场景下区分用户的准确率始终保持在92%以上。通过提供细粒度的睡眠档案,描述睡眠相关事件的细节,issleep允许用户跟踪睡眠效率随着时间的推移,并将不规则的睡眠模式与可能的原因联系起来。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
iSleep: A Smartphone System for Unobtrusive Sleep Quality Monitoring
The quality of sleep is an important factor in maintaining a healthy life style. A great deal of work has been done for designing sleep monitoring systems. However, most of existing solutions bring invasion to users more or less due to the exploration of the accelerometer sensor inside the device. This article presents iSleep—a practical system to monitor people’s sleep quality using off-the-shelf smartphone. iSleep uses the built-in microphone of the smartphone to detect the events that are closely related to sleep quality, and infers quantitative measures of sleep quality. iSleep adopts a lightweight decision-tree-based algorithm to classify various events. For two-user scenario, iSleep differentiates the events of two users either when two phones can collaborate with each other or when two phones cannot communicate with each other. The experimental results show that iSleep achieves consistently above 90% accuracy for event classification in a variety of different settings in one-user scenario and above 92% accuracy for distinguishing users in two-user scenario. By providing a fine-grained sleep profile that depicts details of sleep-related events, iSleep allows the user to track the sleep efficiency over time and relate irregular sleep patterns to possible causes.
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