Digital biomarkers for Alzheimer's Disease with compact dual-mode brain sensing

阿尔茨海默病的数字生物标志物与紧凑的双模式大脑传感 2018年，国家老龄化研究所和阿尔茨海默氏症协会联合创建了一个“研究框架”， 通过强调生物学构建提供阿尔茨海默病（AD）的新生物学定义， 专注于在活体中使用生物标志物诊断AD [1]。现在，“阿尔茨海默病（AD）被定义为 通过其潜在的病理过程，可以通过死后检查或在体内， 生物标志物。”[1]非常需要开发和验证用于早期检测AD的数字生物标志物。是 如果这种数字生物标记物可以用紧凑的装置测量，则更好。 已知AD脑在所有解剖学、生物学和病理学方面具有显著的变性， 方面这种恶化必然伴随着代谢、血液动力学和神经功能的脑功能障碍。 电生理（MHE）活动。此外，AD从早期到晚期的进展需要 通常在早期阶段没有或很少出现症状。然而，尖端的生物构造 基于脑传感技术的脑传感技术可以使得能够检测MHE活性的进行性退化。 本研究假设AD患者的大脑MHE功能受损， 通过来自15分钟的数字生物标志物来感知，同时进行静息状态大脑测量， 紧凑、双模、宽带近红外光谱（bbNIRS）和干/无线脑电图 （dwlEEG）从潜在的AD患者。 具体地说，我们希望进行一项原理验证研究，即开发、测试和演示一种新的 AD传感系统通过集成bbNIRS和dwlEEG（bbNIRS+dwlEEG）作为一个紧凑的，双模式，低成本， 和高效装置。所提出的bbNIRS+dwlEEG设备使我们能够进行静息态人体 脑测量，其将导致（1）脑代谢，（2）脑血容量的定量 和氧合，以及（3）分别以不同频率振荡的脑节律功率和连通性， 从正常人和AD患者身上。具体而言，对于R21建议，我们有两个目标：目标1是 建立基于静息状态的健康人脑的脑MHE活性的数字生物标志物或特征， 状态，使用紧凑的bbNIRS+dwlEEG系统进行神经生理学测量。目标2：确定适当的 生物标志物，可以准确地区分健康老年人与AD患者以及分层AD 根据痴呆的阶段（轻度和中度至重度）对患者进行分类。 该R21的结果将提供双模式bbNIRS+dwlEEG系统的原理证明 能够识别关键的数字生物标志物，从而能够准确检测和分层AD 在轻度或中度至重度阶段，允许我们进行更大的研究项目（即，R 01）用于 通过紧凑、低成本、有效的双模式大脑促进数字生物标志物用于早期检测AD 传感系统

Digital biomarkers for Alzheimer's Disease with compact dual-mode brain sensing In 2018, the National Institute on Aging and Alzheimer's Association jointly created a “research framework,” providing a new biological definition of Alzheimer's disease (AD) by emphasizing a biological construct and focuses on the diagnosis of AD with biomarkers in living persons [1]. Now, “Alzheimer's disease (AD) is defined by its underlying pathologic processes that can be documented by postmortem examination or in vivo by biomarkers.” [1] It is highly desirable to develop and validate digital biomarkers for early detection of AD. It is even better if such digital biomarkers can be measured with compact devices. It is known that the AD brain has significant degenerations in all anatomical, biological, and pathological aspects. Such deteriorations must be accompanied by cerebral dysfunctions of metabolic, hemodynamic, and electrophysiological (MHE) activities in the AD brain. Also, the progression from early to late stage of AD takes years and often shows no or few symptoms at the early stage. However, cutting-edge, biological-construct- based, brain-sensing technology may enable to detect progressive degeneration of MHE-activity. The hypothesis of this study is that patients with AD are impaired in their cerebral MHE functions and can be sensed by digital biomarkers derived from 15-min, resting-state brain measurements concurrently taken with compact, dual-mode, broadband near infrared spectroscopy (bbNIRS) and dry/wireless electroencephalogram (dwlEEG) from potential patients with AD. Specifically, we wish to conduct a proof-of-principle study, namely, to develop, test, and demonstrate a novel AD-sensing system by integrating bbNIRS and dwlEEG (bbNIRS+dwlEEG) as a compact, dual-mode, low-cost, and high-efficient device. The proposed bbNIRS+dwlEEG device enables us to perform resting-state human brain measurements which will result in quantifications of (1) cerebral metabolism, (2) cerebral blood volume and oxygenation, and (3) brain rhythm powers and connectivity oscillating at different frequencies, respectively, from both normal subjects and patients with AD. For this R21 proposal, specifically, we have two aims: Aim 1 is to establish digital biomarkers or features of cerebral MHE-activities of the healthy human brain based on resting- state, neurophysiological measures with a compact bbNIRS+dwlEEG system. Aim 2 is to identify appropriate biomarkers that can accurately separate healthy older adults from patients with AD as well as to stratify AD patients based on the stages of dementia (mild and moderate-to-severe). The outcome of this R21 will provide proof of principle that the dual-mode bbNIRS+dwlEEG system enables to identify critical digital biomarkers that will enable accurate detection and stratification of AD at mild or moderate-to-severe stage, permitting us to pursue a larger research project (i.e., R01) for promoting digital biomarkers for early detection of AD by a compact, low-cost, effective, dual-mode brain sensing system.