biostudies-literatureSoreq EUK Dementia Research InstituteMedical Research CouncilAlzheimer’s Research UKAlzheimer's Research UKe70758https://www.ebi.ac.uk/biostudies/studies/S-EPMC12552897biostudies-literatureUnknown21(10)<h4>Introduction</h4>Disturbed sleep patterns are common in dementia but have not been objectively quantified over long periods.<h4>Methods</h4>We compared a cohort of 83 Alzheimer's disease (AD) patients to 13,588 individuals from the general population. Sleep patterns, heart rate, and breathing rate data were acquired using a zero-burden contactless, under-mattress pressure sensor. Data reduction and explainable machine learning approaches were used to identify sleep phenotypes.<h4>Results</h4>AD was characterized by longer time in bed, more bed exits, less snoring, and changes in estimated sleep states. We derived the Dementia Research Institute Sleep Index for Alzheimer's Disease (DRI-SI-AD), a digital biomarker quantifying sleep disturbances. DRI-SI-AD detected the effects of acute clAlzheimer's & dementia : the journal of the Alzheimer's AssociationContactless longitudinal monitoring in the home characterizes aging and Alzheimer's disease-related night-time behavior and physiology.PMC1255289772017206Lai HVittrant BSoreq ENilforooshan RJoffe AStefanos MAde Villele PRevell VKolanko MAWingfield DWalsh CCRT groupSharp DJRavindran KKGGolemme MDijk DJDaniels SGiovane MDDella Monica CfalseContactless longitudinal monitoring in the home characterizes aging and Alzheimer's disease-related night-time behavior and physiology.<h4>Introduction</h4>Disturbed sleep patterns are common in dementia but have not been objectively quantified over long periods.<h4>Methods</h4>We compared a cohort of 83 Alzheimer's disease (AD) patients to 13,588 individuals from the general population. Sleep patterns, heart rate, and breathing rate data were acquired using a zero-burden contactless, under-mattress pressure sensor. Data reduction and explainable machine learning approaches were used to identify sleep phenotypes.<h4>Results</h4>AD was characterized by longer time in bed, more bed exits, less snoring, and changes in estimated sleep states. We derived the Dementia Research Institute Sleep Index for Alzheimer's Disease (DRI-SI-AD), a digital biomarker quantifying sleep disturbances. DRI-SI-AD detected the effects of acute cl2025-01-01T00:00:00Z2025 Oct2026-06-05T04:50:45.051Z2026-05-13T14:29:19.641ZS-EPMC125528974113762310.1002/alz.70758