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.