Instrument to Co-register EEG and NIRS for Accurate Sleep Sorting

描述（由申请人提供）： 项目概述睡眠障碍非常普遍，并与大量不良后果相关，包括机动车和其他事故、认知受损、免疫功能受损、情绪改变、生活质量下降和死亡率增加。用于评估睡眠生理学的金标准测试是多导睡眠图遭受许多公认的局限性。这些限制降低了睡眠研究人员在理解睡眠方面取得进展的能力，并削弱了临床医生检测和治疗睡眠障碍患者的能力。（PSG）。目前采用的PSG技术我们的长期目标是通过开发一种低成本、低成本的睡眠生理学自动评估方法来解决当前PSG方法的缺点。我们假设，这将是可能的，通过扩大类型的大脑进行评估，包括近红外光谱（NIRS），其中最近的证据表明，低频血流动力学振荡反映睡眠阶段相关的脑功能的变化。NIRS还同时提供脑氧饱和度、心率和呼吸率估计。在此应用中，我们建议设计，构建和测试功率，低噪声，超小型化，无线系统的原理验证原型系统相结合的扩散光学光谱，电生理和惯性。该系统将具有粘性绷带的形状因子，其将干扰和限制受试者到比传统PSG系统小得多的程度。我们将使用基于监督机器学习的方法来探索特定于睡眠阶段和临床相关事件的NIRS特征。其他创新包括记录惯性信号并结合自适应信号处理以消除伪影并提高信噪比（SNR），以及使用商用现成的接近传感器电路来支持NIRS前端。如果成功，该项目将提高开展睡眠研究以及检测和治疗睡眠障碍的能力。所提出的方法将测试是否可以探索新的临床相关的NIRS参数，从而进一步了解睡眠生理学。我们新的基于NIRS的无线系统的小型化、低成本和低功耗将为这些绷带在现实环境中的快速采用和部署铺平道路。鉴于睡眠障碍的高发病率和严重损害，该项目有可能对公共卫生产生重大积极影响。

DESCRIPTION (provided by applicant): PROJECT SUMMARY Sleep disorders are highly prevalent and are associated with substantial adverse consequences including motor vehicle and other accidents, impaired cognition, impaired immune function, altered mood, decreased quality of life, and increased mortality. The gold standard test for assessing the physiology of sleep is the polysomnogram suffers from a number of well-recognized limitations. These limitations decrease the capacity of sleep researchers to make advances in understanding sleep and diminish the capacity of clinicians to detect and treat patients suffering from sleep disorders. (PSG). Currently employed PSG technology Our long-term goal is to address the shortcomings of current PSG methodology by developing a low cost, low for automated assessment of sleep physiology. We hypothesize that this would be possible by expanding the types of brain assessments carried out to include near infrared spectroscopy (NIRS) where recent evidence suggests that the low frequency hemodynamic oscillation reflect sleep stage-related changes in brain function. NIRS also simultaneously provides cerebral oxygen saturation, heart rate and breathing rate estimates. In this application, we propose to design, build, and test power, low noise, ultra-miniaturized, wireless system a proof-of-principle prototype system combining diffuse optical spectroscopic, electrophysiological, and inertial . This system will have the form factor of an adhesive bandage which will disturb and limit subjects to a far lesser degree than traditional PSG systems. We will use supervised machine learning-based methods to explore NIRS features specific to sleep stages and clinically relevant events. Other innovations include recording inertial signals and incorporating adaptive signal processing in order to remove artifacts and improve the signal to noise ratio (SNR), and using commercial-off-the-shelf proximity sensor circuitry to support the NIRS front-end. measurement capabilities If successful, this project will lead to improved capacity to carry out sleep research and to detect and treat sleep disorders. The proposed methodology would test whether novel clinically relevant NIRS parameters can be explored enabling further understanding of sleep physiology. The miniaturization, low cost, and low power consumption of our new NIRS-based wireless system would pave the way for rapid adoption and deployment of these bandages for home-use in real-world settings. Given the high prevalence and substantial impairments associated with sleep disorders, this project has the potential to have a major positive impact on public health.