心冲击描记法用于睡眠分期的研究
Using Ballistocardiography for Sleep Stage Classification
摘要：
随着我们开始了解睡眠对人们生活的巨大影响，一种检测睡眠阶段的实用方法变得更加必要。当前的睡眠阶段检测方法是昂贵的，对人的睡眠是侵入性的，并且在现代家庭环境中不实用。虽然通过监测大脑活动，肌肉活动和眼球运动来检测睡眠阶段的方法，通过实验室环境中的脑电图，提供了检测的金标准，但本文旨在研究一种新方法，该方法将允许一个人获得类似的洞察力和结果，而不会影响他们的正常睡眠习惯。心冲击描记术（BCG）是一种非侵入性传感技术，通过测量心脏产生的弹道力来收集信息。使用从BCG提取的特征，如使用时间，心率，呼吸率，相对每搏输出量和心率变异性，我们建议实现一个睡眠阶段检测算法，并将其与从Fitbit Sense智能手表提取的睡眠阶段进行比较。BCG的可访问性、易用性和相对低的成本为使用该设备提供了许多应用和优势。通过标准化该设备，人们将能够从BCG中受益，分析自己的睡眠模式，并得出关于睡眠效率的结论。这项工作证明了使用BCG作为一种准确和非侵入性的睡眠监测方法的可行性，这种方法可以在个人舒适的睡眠环境中进行设置。
英文摘要：
A practical way of detecting sleep stages has become more necessary as we begin to learn about the vast effects that sleep has on people's lives. The current methods of sleep stage detection are expensive, invasive to a person's sleep, and not practical in a modern home setting. While the method of detecting sleep stages via the monitoring of brain activity, muscle activity, and eye movement, through electroencephalogram in a lab setting, provide the gold standard for detection, this paper aims to investigate a new method that will allow a person to gain similar insight and results with no obtrusion to their normal sleeping habits. Ballistocardiography (BCG) is a non-invasive sensing technology that collects information by measuring the ballistic forces generated by the heart. Using features extracted from BCG such as time of usage, heart rate, respiration rate, relative stroke volume, and heart rate variability, we propose to implement a sleep stage detection algorithm and compare it against sleep stages extracted from a Fitbit Sense Smart Watch. The accessibility, ease of use, and relatively-low cost of the BCG offers many applications and advantages for using this device. By standardizing this device, people will be able to benefit from the BCG in analyzing their own sleep patterns and draw conclusions on their sleep efficiency. This work demonstrates the feasibility of using BCG for an accurate and non-invasive sleep monitoring method that can be set up in the comfort of a one's personal sleep environment.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
