Evidence map›Paper›PMID 41743052›Full record

SynthesisFrontiers in neurology

Digital biomarkers for early agitation detection in dementia: a scoping review of emerging wearable and smart technologies for personalized care.

Alex Malioukis, R Sterling Snead, Julia Marczika, Radha Ambalavanan, Gideon Towett, Mercy Mbogori-Kairichi

Abstract readSystematic Review
In one paragraph

Synthesis in Frontiers in neurology. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Review
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.

Alex MalioukisThe Self Research Institute, Broken Arrow, OK, United States.
R Sterling SneadThe Self Research Institute, Broken Arrow, OK, United States.
Julia MarczikaThe Self Research Institute, Broken Arrow, OK, United States.
Radha AmbalavananThe Self Research Institute, Broken Arrow, OK, United States.
Gideon TowettThe Self Research Institute, Broken Arrow, OK, United States.
Mercy Mbogori-KairichiThe Self Research Institute, Broken Arrow, OK, United States.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: Agitation is a common and burdensome symptom in people with dementia, particularly when compounded by impaired communication, making early detection and effective management difficult. Wearable sensor technologies may offer a promising avenue for supporting real-time behavioral monitoring and personalized care in this context. Objective: This study aims to examine the current clinical and technological capabilities of wearable sensor systems for detecting and managing agitation in persons with dementia, to assess whether these technologies can effectively support personalized care. Additionally, it seeks to identify key challenges and opportunities in applying human-centered design principles and tailored interventions to improve outcomes for both patients and caregivers. Methods: We conducted a scoping literature review, registered on OSF and guided by PRISMA-ScR guidelines. Five databases-Google Scholar, Scopus, PubMed, PsycINFO, and ACM Digital Library-were searched for English-language peer-reviewed studies published between 2016 and early 2025. From an initial pool of 798 articles, a multi-phase screening process led to a final inclusion of 13 studies that met predefined criteria. Results: The reviewed studies demonstrated that wearable sensors, particularly those employing multimodal data and personalized machine learning models, enable reliable detection of agitation symptoms and support timely, tailored interventions. The concept of digital phenotyping emerged as a promising approach for capturing complex behavioral signatures, while user-centered design was identified as essential for adoption and long-term compliance. Discussion: The evidence identified in this scoping review indicates that wearable and multimodal sensor technologies may offer promising approaches for monitoring agitation in dementia, while acknowledging that the research remains in early stages. We recommend future research focus on large-scale, longitudinal validation and the expansion of these tools to other populations with communication challenges, such as individuals with autism spectrum disorder or traumatic brain injury. Systematic review registration: https://doi.org/10.17605/OSF.IO/DNHYM.

Indexed as

agitationbiomarkersdementiaearly detectionpersonalized carewearables

Identifiers

PMID41743052
PMCPMC12929127

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.