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

Instrument to Co-register EEG and NIRS for Accurate Sleep Sorting
联合注册 EEG 和 NIRS 进行准确睡眠分类的仪器
批准号:
8771722
负责人:
Alper Bozkurt
金额:
$26.58万
依托单位国家:
美国
项目类别:
财政年份:
2014
资助国家:
美国
项目状态:
已结题
起止时间:
2014-09-22 至 2016-08-31

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