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A systematic review and meta-analysis on dual-task sensor-based motion analysis for dementia detection
Iman Hosseini1, Joseph M Northey2, Nathan M D'Cunha3
1School of Computing, Australian National University, Acton, ACT, Australia.
Frontiers in Digital Health
|May 25, 2026
Summary
Instrumented dual-task tests can help detect dementia by measuring how cognitive tasks affect movement. These assessments show people with dementia walk slower and less steadily, especially during dual-task conditions.
Area of Science:
- Neuroscience
- Biomedical Engineering
- Gerontology
Background:
- Early dementia diagnosis is crucial for management.
- Objective, scalable tests are needed to capture cognitive-motor interference.
- Instrumented dual-task paradigms offer a potential solution.
Purpose of the Study:
- To systematically review and meta-analyze studies using instrumented dual-task paradigms for dementia detection and characterization.
- To assess the effectiveness of these paradigms in differentiating individuals with dementia from controls.
Main Methods:
- PRISMA-guided systematic review and meta-analysis of peer-reviewed studies.
- Inclusion of adults with clinically defined dementia and appropriate comparators.
- Meta-analysis of walking outcomes using random-effects models, with subgroup analyses.
Main Results:
- Studies predominantly focused on Alzheimer's disease, using inertial measurement units and force plates.
- People with dementia exhibited slower walking speed, shorter steps, and less steady timing compared to controls.
- Dual-task conditions amplified group differences, with arithmetic loads affecting speed/cadence and memory/fluency tasks affecting timing.
Conclusions:
- Instrumented dual-task assessments show promise in enhancing dementia detection and characterizing cognitive-motor impairment.
- Future research should broaden to diverse dementia subtypes, standardize protocols, and validate multi-modal analytic approaches for clinical translation.
