Remote Digital Assessments for Cognitive Disorders

The requested reference [1371907c3dad7213f92f76df6e36688b0daa3060] no longer exists in our database. It has been replaced by the current reference: [0d117b07f45d0c28677eb2414cbfd1c261eb5d96]

Authors
Category Primary study
Registry of TrialsClinicalTrials.gov
Year 2026
Memory and thinking problems in older adults, including mild cognitive impairment (MCI) and Alzheimer\'s disease (AD), can be difficult to assess promptly because evaluation often depends on in-person specialist visits. MonitorCog-AI is a computer-based platform designed to provide a more accessible way to assess and monitor cognitive changes using standard computers or tablets. Artificial intelligence (AI) will be used to analyze the digital information collected by the platform and examine whether combining several types of measures improves assessment of cognitive impairment. The study will include 60 adults aged 50 years and older: 20 healthy adults, 20 adults with MCI, and 20 adults with AD. Participants will be assessed at baseline, 6 months, and 12 months. At each timepoint, participants will complete one clinical assessment and one digital assessment. The clinical assessment will include standard measures of memory and thinking, an assessment of daily functioning, and a brief recording of brain electrical activity. The digital assessment will take approximately 60-80 minutes and will assess five areas: cognition, eye movements measured using a webcam, language, speech, and fine-motor performance measured using a mouse. At baseline, the digital assessment will be completed in the clinic; at 6 and 12 months, it will usually be completed remotely at home. The study has three main goals. First, it will determine whether MonitorCog-AI is feasible, acceptable, easy to use, and not overly burdensome for repeated assessment. Second, it will examine how well AI-based analysis of the digital measures distinguishes healthy adults, adults with MCI, and adults with AD, and whether combining several types of digital information performs better than any single type alone. Third, it will examine how digital measures change over 12 months and whether these changes are related to changes in clinical measures of cognition and daily functioning.
Epistemonikos ID: 42971b7b51ad366b630b3e167d57ec99342ad6ae
First added on: Oct 21, 2026