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Towards Improving Sleep Quality Using Automatic Sleep Stage Classification and Binaural Beats

机译:通过自动睡眠阶段分类和双耳节拍来改善睡眠质量

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Sleep disorders are extremely common in today’s society and are greatly affecting the health and safety of every person suffering from one. Over the last decades, Automatic Sleep Stage Classification (ASSC) systems have been developed to assist specialists in the sleep stage scoring process and therefore in the diagnosis of sleep disorders. Binaural beats are auditory phenomena that have been shown to have a positive impact in sleep quality and mental state. This paper introduces a framework that combines an ASSC system and a binaural beats generator in real time. Our goal is to pave the way for developing systems which could reproduce specific binaural beats depending on the detected sleep stage, in order to entrain the brain into a more efficient sleep. For the ASSC stage, different classifiers were evaluated using data signals retrieved from a public sleep stage signals database, corresponding to ten subjects. The complete framework was tested using the database signals and signals from a test subject, captured and processed in real time. Our proposed framework may lead to a fully automated system to improve sleep quality without the need of medication.
机译:睡眠障碍在当今社会极为普遍,并且极大地影响着每个遭受睡眠障碍困扰的人的健康和安全。在过去的几十年中,已经开发了自动睡眠阶段分类(ASSC)系统,以协助专家进行睡眠阶段评分过程,从而帮助诊断睡眠障碍。双耳节律是听觉现象,已被证明对睡眠质量和精神状态有积极影响。本文介绍了一个将ASSC系统和双耳节拍发生器实时结合的框架。我们的目标是为开发系统奠定基础,该系统可以根据检测到的睡眠阶段来重现特定的双耳节律,从而使大脑进入更有效的睡眠状态。对于ASSC阶段,使用从公共睡眠阶段信号数据库中检索到的数据信号(对应于十个受试者)对不同的分类器进行了评估。完整的框架使用数据库信号和来自测试对象的信号进行了测试,并实时捕获和处理。我们提出的框架可能会导致无需药物即可改善睡眠质量的全自动系统。

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