Use of Wearables for Identifying Factors Associated With Mild Cognitive Impairment and Early-Stage Alzheimer's Disease

Sponsor
Getúlio Vargas University Hospital
Study ID
NCT07391436
Status
Not Yet Recruiting

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Conditions

Eligibility Criteria

Sex
ALL
Age
65 Years - N/A
Healthy Volunteers
Accepted

Study Details

Cognitive decline affects millions of older adults worldwide and has a profound impact on individuals, families, and healthcare systems. Mild Cognitive Impairment (MCI) is often an early stage of Alzheimer's disease (AD), a condition for which there is currently no cure. Identifying individuals at risk at the earliest possible stage remains a major challenge. Traditional diagnostic approaches, such as laboratory biomarkers, neuroimaging, and neuropsychological testing, are usually performed at a single point in time and may fail to detect subtle or early changes in brain function and daily behavior. Recent advances in wearable technology, such as smartwatches and smart rings, allow continuous and noninvasive monitoring of physiological and behavioral patterns in daily life. These devices can capture data related to physical activity, sleep, heart rate, and other parameters that may change before clear cognitive symptoms become evident. When combined with clinical, laboratory, neuropsychological, neuroimaging, and electroencephalographic (EEG) information, these data may help identify early signs of cognitive decline. The objective of this study is to develop and validate models capable of detecting early indicators of MCI and early-stage Alzheimer's disease by integrating multiple sources of data, including clinical assessments, blood tests, neuropsychological evaluations, brain imaging, EEG recordings, and continuous data obtained from wearable devices. This is an observational, analytical, single-center, prospective cohort study that will include 150 participants of both sexes, aged 65 years or older. Participants will be recruited from the Dementia Outpatient Clinic of Getúlio Vargas University Hospital (HUGV), through referrals from external neurologists, or via study dissemination on social media. To achieve the target sample size, up to 250 individuals may be approached using a non-probabilistic, convenience-based recruitment strategy. After providing informed consent, participants will undergo a comprehensive medical evaluation, standardized and validated neuropsychological testing, laboratory and imaging examinations, and EEG recording. Participants will also receive training to use wearable devices for continuous monitoring in their daily routines. A control group of older adults without cognitive impairment will be included for comparison. All collected data will be securely stored in a centralized database and used to develop and validate analytical models aimed at identifying patterns associated with cognitive decline. The results of this study may support earlier identification of individuals at risk for MCI and Alzheimer's disease, help guide timely interventions, and potentially delay disease progression and early institutionalization, contributing to improved quality of life for older adults and their families.

Key Dates

First listed
Feb 5, 2026
Start date
Mar 31, 2026
Status verified
Jan 2026
Primary completion
Jul 31, 2027
Completion
Dec 31, 2027

Study Design

Enrollment
150 participants (estimated)

Arms

  • Arm: Control Group
    Individuals without significant abnormalities on imaging exams, biomarkers, or neuropsychological assessment.
  • Arm: Mild Cognitive Impairment (MCI)
    Participants with abnormalities in cognitive questionnaire scores and/or laboratory biomarkers, but without significant functional impairment.
  • Arm: Early-stage Alzheimer's disease (eAD)
    Individuals with altered laboratory and/or imaging results compatible with the initial phase of neurodegeneration.

Primary Outcome Measure

Accuracy of a Predictive Model for Identification of Mild Cognitive Impairment and Early Alzheimer's Disease [ Time Frame: Up to 30 days of continuous wearable monitoring ]

Central Contacts

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