Evidence map›Paper›PMID 41137623›Full record

ArticleAlzheimer's & dementia : the journal of the Alzheimer's Association2025

Contactless longitudinal monitoring in the home characterizes aging and Alzheimer's disease-related night-time behavior and physiology.

Eyal Soreq, Magdalena A Kolanko, CRT group, Kiran K G Ravindran, Ciro Della Monica, Victoria Revell, Sarah Daniels, Anna Joffe, Helen Lai, Mara Golemme and 9 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Alzheimer's & dementia : the journal of the Alzheimer's Association, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

7 citing papers in PubMed.

  1. The DREAMS START intervention for sleep in dementia: Long-term follow-up of a randomized controlled trial.Alzheimer's & dementia : the journal of the Alzheimer's Association · 2026
    Trial
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

19 authors.

Eyal SoreqUK Dementia Research Institute Care Research and Technology Centre, Imperial College London Sir Michael Uren Hub, White City Campus, London, and the University of Surrey, Guildford, UK.
Magdalena A KolankoUK Dementia Research Institute Care Research and Technology Centre, Imperial College London Sir Michael Uren Hub, White City Campus, London, and the University of Surrey, Guildford, UK.
CRT group
Kiran K G RavindranUK Dementia Research Institute Care Research and Technology Centre, Imperial College London Sir Michael Uren Hub, White City Campus, London, and the University of Surrey, Guildford, UK.
Ciro Della MonicaUK Dementia Research Institute Care Research and Technology Centre, Imperial College London Sir Michael Uren Hub, White City Campus, London, and the University of Surrey, Guildford, UK.
Victoria RevellUK Dementia Research Institute Care Research and Technology Centre, Imperial College London Sir Michael Uren Hub, White City Campus, London, and the University of Surrey, Guildford, UK.
Sarah DanielsUK Dementia Research Institute Care Research and Technology Centre, Imperial College London Sir Michael Uren Hub, White City Campus, London, and the University of Surrey, Guildford, UK.
Anna JoffeUK Dementia Research Institute Care Research and Technology Centre, Imperial College London Sir Michael Uren Hub, White City Campus, London, and the University of Surrey, Guildford, UK.
Helen LaiUK Dementia Research Institute Care Research and Technology Centre, Imperial College London Sir Michael Uren Hub, White City Campus, London, and the University of Surrey, Guildford, UK.
Mara GolemmeUK Dementia Research Institute Care Research and Technology Centre, Imperial College London Sir Michael Uren Hub, White City Campus, London, and the University of Surrey, Guildford, UK.
Martina Del GiovaneUK Dementia Research Institute Care Research and Technology Centre, Imperial College London Sir Michael Uren Hub, White City Campus, London, and the University of Surrey, Guildford, UK.
Chloe WalshUK Dementia Research Institute Care Research and Technology Centre, Imperial College London Sir Michael Uren Hub, White City Campus, London, and the University of Surrey, Guildford, UK.
David WingfieldUK Dementia Research Institute Care Research and Technology Centre, Imperial College London Sir Michael Uren Hub, White City Campus, London, and the University of Surrey, Guildford, UK.
Ramin NilforooshanUK Dementia Research Institute Care Research and Technology Centre, Imperial College London Sir Michael Uren Hub, White City Campus, London, and the University of Surrey, Guildford, UK.
Marie-Ange StefanosWithings Inc., Issy-les-Moulineaux, France.
Benjamin VittrantWithings Inc., Issy-les-Moulineaux, France.
Paul de VillèleWithings Inc., Issy-les-Moulineaux, France.
Derk-Jan DijkUK Dementia Research Institute Care Research and Technology Centre, Imperial College London Sir Michael Uren Hub, White City Campus, London, and the University of Surrey, Guildford, UK.
David J SharpUK Dementia Research Institute Care Research and Technology Centre, Imperial College London Sir Michael Uren Hub, White City Campus, London, and the University of Surrey, Guildford, UK.

Funding

Alzheimer's Research UKMedical Research CouncilUK Dementia Research Institute 7201UK Dementia Research Institute 7206
6 · The paper itself

Abstract

introductionDisturbed sleep patterns are common in dementia but have not been objectively quantified over long periods.

methodsWe 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.

resultsAD 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 clinical events and dementia progression at the individual level. DISCUSSION: Our approach may help bridge a gap in dementia care by providing a zero-burden method for longitudinal monitoring of health events, disease progression, and dementia risk. HIGHLIGHTS: Continuous monitoring reveals dementia-specific nocturnal sleep disturbances. We developed a novel sleep biomarker, Dementia Research Institute Sleep Index (AD), for tracking Alzheimer's disease (AD) progression. We used contactless under-mattress sensors for low-burden, long-term data collection. Prolonged bedtimes and frequent exits were identified as key dementia-related sleep traits. We demonstrated the feasibility of in-home monitoring for dementia care and risk assessment.

Indexed as

AgingAlzheimer DiseaseSleep Wake DisordersAgedAged, 80 and overDisease ProgressionFemaleHumansLongitudinal StudiesMachine LearningMaleMonitoring, PhysiologicSleepagingAlzheimer's diseasebed exitscontactless monitoringDementia Research Institute Sleep Indexdigital biomarkerslongitudinal studymachine learningnocturnal behaviorphysiological monitoringsleep disturbancessleep fragmentationWithings sleep analyzer

Identifiers

PMID41137623
PMCPMC12552897

What OpenQuestion holds

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LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.