Associations of daily step counts with cognitive, clinical, and resting-state electroencephalographic measures in patients with cognitive decline due to Alzheimer’s disease

Sedentary behavior is a recognized and modifiable risk factor for cognitive decline and dementia across neurodegenerative conditions. This study used a smartwatch-based telemonitoring procedure combined with ecological cognitive assessment to examine whether step counts can capture sedentary behavior and its association with cognitive functioning in patients with mild cognitive impairment (ADMCI) and dementia (ADD) due to Alzheimer’s disease. Then, 19 ADD, 28 ADMCI, and 23 cognitively unimpaired older adults (Nold) were consecutively recruited. Participants underwent clinical assessment, resting-state electroencephalography (rsEEG), and neuropsychological testing. They were then monitored at home for approximately one week using Samsung Galaxy Watch 4–6 devices recording step counts (total, purposeful, and incidental) and activity intensity (peak 30-min cadence), together with the unsupervised SmartMe&You-TELEMAIA serious videogame battery administered on a commercial tablet for cognitive assessment. The ADD group showed reduced step counts and lower peak cadence than both ADMCI and Nold participants, whereas rsEEG markers and cognitive measures discriminated the three groups with a graded pattern. Within the AD sample, smartwatch-derived activity metrics were associated with cognitive functioning as assessed by conventional neuropsychological testing and ecological serious videogame performance, but showed limited associations with rsEEG rhythms. EEG delta and alpha rhythms were also more abnormal in the ADD group than in the ADMCI group. Home-based daytime activity monitoring with commercial smartwatches indicated that step volume and intensity are associated with cognitive status in patients with ADMCI and ADD. These findings suggest that smartwatch-derived activity metrics may provide feasible and cost-effective markers of everyday functioning in Alzheimer’s disease. Graphical abstract a Schematic overview of the study design, including resting-state EEG, one-week smartwatch-based activity monitoring, and unsupervised ecological cognitive assessment with the SmartMe&You-TELEMAIA Platform. b Group differences in daily activity metrics across participants with Alzheimer’s disease with dementia (ADD; N = 19), Alzheimer’s disease with mild cognitive impairment (ADMCI; N = 28), and cognitively unimpaired older adults (Nold; N = 23), indicating reduced daily step volume and peak cadence mainly in ADD. c Representative significant associations within the AD clinical sample (ADD + ADMCI; up to N = 47), showing that step metrics were more closely related to cognition (MMSE) and depressive symptom severity (BDI-II) than to resting-state EEG activity, for which only limited associations emerged.