Evidence map›Paper›PMID 41982278›Full record

ReviewDementia and geriatric cognitive disorders extra

Can Sensor Technologies Accurately Detect and Monitor Behavioural and Psychological Symptoms of Dementia? A Systematic Review.

Khalid Abdul Jabbar, Sing Qin Ting, Shze Yee Choo, Yasmin Lynda Munro, Shian Ming Tan, Iris Rawtaer

Abstract readReview
In one paragraph

Review in Dementia and geriatric cognitive disorders extra. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

6 authors.

Khalid Abdul JabbarResearch Office, Sengkang General Hospital, Singapore, Singapore.
Sing Qin TingDepartment of Psychiatry, Sengkang General Hospital, Singapore, Singapore.
Shze Yee ChooDepartment of Psychiatry, Sengkang General Hospital, Singapore, Singapore.
Yasmin Lynda MunroLee Kong Chian School of Medicine, Nanyang Technological University, Singapore, Singapore.
Shian Ming TanDepartment of Psychiatry, Sengkang General Hospital, Singapore, Singapore.
Iris RawtaerResearch Office, Sengkang General Hospital, Singapore, Singapore.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: Although sensor technologies hold potential for addressing challenges for the detection and management of behavioural and psychological symptoms of dementia (BPSD), their application in this context remains in its early stages. This review evaluated the accuracy of sensor technologies to detect and/or monitor neuropsychiatric symptoms in individuals with dementia, particularly in real-world home settings. Methods: Systematic searches were conducted in five databases on February 20, 2025. Two independent reviewers performed data extraction, with a third reviewer resolving any disagreements. Results: Of 109 records meeting the inclusion criteria for full-text review, 17 studies were included. Sensor-based detection of agitation (number of studies, Conclusions: This review highlights that the application of sensor technology for detecting and monitoring BPSD remains at an early stage, with existing evidence largely confined to a small subset of symptoms and providing limited clinimetric validation. Additionally, it emphasizes the need for consensus on standard definitions, outcome measures, and validation methodologies to guide and inform future research, which can then leverage these technologies to improve the care and quality of life of persons with dementia and their caregivers.

Indexed as

BPSDDementiaPeople living with dementiaReal-world settingsSensor technology

Identifiers

PMID41982278
PMCPMC13075880

What OpenQuestion holds

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Registered trials

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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.