Relevant outcome measurements for the study have been selected through the following longitudinal process:

Identification of functional domains that meet one or more of the following criteria:

Predicts conversion of MCI due to AD to mild AD dementia. Impaired in mild AD dementia. Predicts functional decline in AD dementia. Reported as important by an AD dementia patient advisory board. Identification of candidate RMTs to cover real-life measurement of the functional domains identified in step 1.

Identification of candidate digital biomarkers, which are life-log data such as steps, sleep, heart rate and exercise collected by RMTs, to cover clinical measurement of the functional domains identified in step 1.

Functional domains, RMTs, and clinical assessments that resulted from the selection process above are listed in Table 1, and 2. The selection process described in step 1 resulted in the identification of the following functional domains, sorted by relevance [HR (highly relevant), R (relevant), N (neutral), and LR (least relevant)].

The central assumption of the study is that functional disabilities proportionally increase with the progressive worsening of the AD. A recent classification proposed by the FDA 2018 draft guidance for the development of novel treatments in AD identifies the early disease progression in 3 stages: (a) Patients with characteristic pathophysiologic changes of Preclinical AD but no evidence of clinical impact (Stage 1) (b) Patients with characteristic pathophysiologic changes of AD and subtle or more apparent detectable abnormalities on sensitive neuropsychological measures, but no functional impairment (Stage 2), and (c) Patients with characteristic pathophysiologic changes of AD and subtle or more apparent detectable abnormalities on sensitive neuropsychological measures, but mild and detectable functional impairment (Stage 3). The aim of the DNS study is to assess the feasibility, utility and performance of selected RMTs in profiling ADL in real-world settings. This goal will be achieved by evaluating digital signals collected either continuously, or daily, or weekly at home, either using wearable devices or home-located ambient devices, determining as much as possible the specific context-dependent conditions in which the signals are measured. As a general hypothesis, RMTs will deliver more sensitive and less variable measurements when compared to standard clinical assessments, questionnaires and tests measuring specific functional capabilities in the clinics.

The most important results of the study will be (1) the evidence that some RMT parameters will provide insights for lower variance than the standard scales or questionnaires, (2) the capacity of Altoida, Inc. NMI and/or RMTs to significantly differentiate the preclinical AD stages 1 & 2 when compared to healthy volunteers with negative AD biomarkers as a control, and (3) a similar capabilities of Altoida, Inc. NMI and/or RMTs to detect monotonic change in the mild cognitive impairment (MCI) due to AD group and, even more, in mild, moderate and severe AD dementia groups, proportional to the specific functional impairment known to worsen during the disease progression.