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

描述(由申请人提供)： 项目摘要睡眠障碍非常普遍，并与严重的不良后果有关，包括机动车辆和其他事故、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。评估睡眠生理学的金标准测试是多导睡眠图受到一些公认的局限性的影响。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)。目前使用的PSG技术我们的长期目标是通过开发一种低成本、低成本的睡眠生理自动评估来解决当前PSG方法的缺点。我们假设，这是可能的，通过扩大进行的大脑评估的类型，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大脑功能变化。NIRS还同时提供大脑氧饱和度、心率和呼吸频率的估计。在这一应用中，我们建议设计、建造和测试功率、低噪声、超小型化、无线系统，一个结合漫反射光学光谱、电生理和惯性的原理验证原型系统。该系统将具有粘性绷带的形状因素，与传统的PSG系统相比，它对受试者的干扰和限制程度要小得多。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近红外光谱特征。其他创新包括记录惯性信号和融入自适应信号处理，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。测量能力如果成功，该项目将提高开展睡眠研究、检测和治疗睡眠障碍的能力。建议的方法将测试是否可以探索新的临床相关的近红外光谱参数，从而进一步了解睡眠生理学。我们基于NIRS的新无线系统的小型化、低成本和低功耗将为在现实世界中快速采用和部署这些家用绷带铺平道路。鉴于睡眠障碍的高患病率和严重损害，该项目有可能对公众健康产生重大积极影响。

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.