Evidence map›Paper›PMID 41471663›Full record

ReviewSensors (Basel, Switzerland)2025

Wearable Sensor Technologies and Gait Analysis for Early Detection of Dementia: Trends and Future Directions.

Anna Tsiakiri, Spyridon Plakias, Georgios Giarmatzis, Georgia Tsakni, Foteini Christidi, Georgia Karakitsiou, Vasiliki Georgousopoulou, Georgios Manomenidis, Dimitrios Tsiptsios, Konstantinos Vadikolias and 2 more

Abstract readReview
In one paragraph

Review in Sensors (Basel, Switzerland), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. Article
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

12 authors.

Anna TsiakiriDepartment of Neurology, Democritus University of Thrace, 68100 Alexandroupolis, Greece.ORCID 0000-0003-3341-4093
Spyridon PlakiasDepartment of Physical Education and Sport Science, University of Thessaly, 42100 Trikala, Greece.ORCID 0000-0002-9511-6940
Georgios GiarmatzisDepartment of Physical Education and Sport Science, Democritus University of Thrace, 69100 Komotini, Greece.ORCID 0000-0003-1387-2134
Georgia TsakniDepartment of Occupational Therapy, University of West Attica, 12243 Athens, Greece.ORCID 0000-0002-9143-1329
Foteini ChristidiDepartment of Neurology, Democritus University of Thrace, 68100 Alexandroupolis, Greece.ORCID 0000-0003-1297-9415
Georgia KarakitsiouDepartment of Psychiatry, Medical School, Democritus University of Thrace, 68100 Alexandroupolis, Greece.ORCID 0009-0001-8279-1277
Vasiliki GeorgousopoulouDepartment of Nursing, Democritus University of Thrace, 68100 Alexandroupolis, Greece.ORCID 0000-0002-0351-9970
Georgios ManomenidisDepartment of Nursing, Democritus University of Thrace, 68100 Alexandroupolis, Greece.ORCID 0000-0003-2481-4335
Dimitrios Tsiptsios3rd Department of Neurology, Aristotle University of Thessaloniki, 54124 Thessaloniki, Greece.ORCID 0000-0002-1601-8788
Konstantinos VadikoliasDepartment of Neurology, Democritus University of Thrace, 68100 Alexandroupolis, Greece.ORCID 0000-0003-0484-369X
Nikolaos AggelousisDepartment of Physical Education and Sport Science, Democritus University of Thrace, 69100 Komotini, Greece.ORCID 0000-0001-5108-7335
Pinelopi VlotinouDepartment of Occupational Therapy, University of West Attica, 12243 Athens, Greece.ORCID 0000-0002-8828-9093

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The progressive nature of dementia necessitates early detection strategies capable of identifying preclinical cognitive decline. Gait disturbances, mediated by higher-order cognitive functions, have emerged as potential digital biomarkers in this context. This bibliometric review systematically maps the scientific output from 2010 to 2025 on the application of wearable sensor technologies and gait analysis in the early diagnosis of dementia. A targeted search of the Scopus database yielded 126 peer-reviewed studies, which were analyzed using VOSviewer for performance metrics, co-authorship networks, bibliographic coupling, co-citation, and keyword co-occurrence. The findings delineate a multidisciplinary research landscape, with major contributions spanning neurology, geriatrics, biomedical engineering, and computational sciences. Four principal thematic clusters were identified: (1) Cognitive and Clinical Aspects of Dementia, (2) Physical Activity and Mobility in Older Adults, (3) Technological and Analytical Approaches to Gait and Frailty and (4) Aging, Cognitive Decline, and Emerging Technologies. Despite the proliferation of research, significant gaps persist in longitudinal validation, methodological standardization, and integration into clinical workflows. This review emphasizes the potential of sensor-derived gait metrics to augment early diagnostic protocols and advocates for interdisciplinary collaboration to advance scalable, non-invasive diagnostic solutions for neurodegenerative diseases.

Indexed as

Biosensing TechniquesDementiaGaitGait AnalysisWearable Electronic DevicesCognitive DysfunctionEarly DiagnosisHumansdementiadigital biomarkersearly diagnosisgait analysismild cognitive impairmentwearable sensors

Identifiers

PMID41471663
PMCPMC12736759

What Socratic holds

Textmetadata
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 Socratic graph.