Evidence map›Paper›PMID 42179817›Full record

ReviewFrontiers in digital health2026

A systematic review and meta-analysis on dual-task sensor-based motion analysis for dementia detection.

Iman Hosseini, Joseph M Northey, Nathan M D'Cunha, Raul Fernandez Rojas, Abishek Shrestha, Maryam Ghahramani

Abstract readReview
In one paragraph

Review in Frontiers in digital health, 2026. 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.

Iman HosseiniSchool of Computing, Australian National University, Acton, ACT, Australia.
Joseph M NortheyUC Research Institute for Sport and Exercise, University of Canberra, Bruce, ACT, Australia.
Nathan M D'CunhaCentre for Ageing Research & Translation, University of Canberra, Bruce, ACT, Australia.
Raul Fernandez RojasBioSIS (Biosensing & Intelligent Systems) Lab, Centre for Intelligent Computing and Systems, University of Canberra, Canberra, ACT, Australia.
Abishek ShresthaBioSIS (Biosensing & Intelligent Systems) Lab, Centre for Intelligent Computing and Systems, University of Canberra, Canberra, ACT, Australia.
Maryam GhahramaniBioSIS (Biosensing & Intelligent Systems) Lab, Centre for Intelligent Computing and Systems, University of Canberra, Canberra, ACT, Australia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: Early diagnosis of dementia may be improved by objective, scalable tests that capture how cognitive tasks interfere with movement. This study examined the use of instrumented dual-task paradigms for dementia detection and characterisation. Methods: We performed a PRISMA-guided systematic review and meta-analysis of peer-reviewed studies that used dual-task paradigms in adults with clinically defined dementia and an appropriate comparator. We extracted primary motor tasks, secondary cognitive or motor loads, sensor modalities, and analytic approaches. Walking outcomes were meta-analysed using inverse-variance weighted random-effects models, including subgroup analyses for single-task versus dual-task conditions and for arithmetic versus memory and verbal fluency assessments. Results: The literature was dominated by cognitive-motor dual-task paradigms in Alzheimer's disease cohorts. Inertial measurement units and force plates were the most common instruments, and most studies used classical statistics, with fewer applying machine learning. Pooled effects showed consistent group differences; compared with controls, people with dementia walked more slowly, took shorter steps, and showed less steady timing. Although heterogeneity was substantial across studies, the direction of effects was stable, and dual-task conditions generally amplified group differences relative to single-task performance. Arithmetic loads tended to accentuate changes linked to speed and cadence, whereas memory and verbal fluency assessments tended to prolong timing measures. Balance, turning, and some upper-limb outcomes also differentiated groups. Discussion: Instrumented dual-task assessments appear to enhance detection of cognitive-motor impairment in dementia and may complement existing evaluations. To support clinical translation, future work should extend beyond Alzheimer's disease, standardise task instructions and reporting, and evaluate multi-modal, validated analytic approaches across different dementia subtypes. Systematic Review Registration: https://www.crd.york.ac.uk/PROSPERO/view/CRD420251114199, CRD420251114199.

Indexed as

cognitive-motor interferencedementia detectiondigital biomarkersdual-task assessmentgait analysisinstrumented analysis

Identifiers

PMID42179817
PMCPMC13190577

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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.