Abstract
Background: Circadian and sleep disturbances are associated with increased risk of mild cognitive impairment (MCI) and Alzheimer's disease (AD). Wearable activity trackers could provide a new approach in diagnosis and prevention. Objective: To evaluate sleep and circadian rhythm parameters, through wearable activity trackers, in MCI and AD patients as compared to controls, focusing on sex dissimilarities. Methods: Based on minute level data from consumer wearable devices, we analyzed actigraphic sleep parameters by applying an electromedical type I registered algorithm, and the corresponding circadian variables in 158 subjects: 86 females and 72 males (42 AD, 28 MCI, and 88 controls). Moreover, we used a confusion-matrix chart method to assess accuracy, precision, sensitivity, and specificity of two decision-tree models based on actigraphic data in predicting disease or health status. Results: Wake after sleep onset (WASO) was higher (p
Original language | English |
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Pages (from-to) | 1707-1719 |
Number of pages | 13 |
Journal | J. Alzheimer's Dis. |
Volume | 78 |
Issue number | 4 |
DOIs | |
Publication status | Published - 2020 |
Keywords
- Alzheimer's disease
- circadian rhythms
- confusion matrix
- mild cognitive impairment
- sex differences
- sleep disturbances
- sleep parameters
- sleep regularity index
- wearable activity tracker