Files and links (1)
Published VersionCC BY V4.0, Open Access
Journal article
Relationship Between Cognitive Abilities and Lower-Limb Movements: Can Analyzing Gait Parameters and Movements Help Detect Dementia? A Systematic Review
Sensors , Vol.25(3), pp.1-22
2025
PMID: 39943452
Abstract
Identifying and diagnosing cognitive impairment remains challenging. Some diagnostic procedures are invasive, expensive, and not always accurate. Meanwhile, evidence suggests that cognitive impairment is associated with changes in gait parameters. Certain gait parameters manifesting differences between people with and without cognitive impairment are more pronounced when adding a secondary task (dual-task scenario). In this systematic review, the capability of gait analysis to identify cognitive impairment is investigated. Twenty-three studies published between 2014 and 2024 met the inclusion criteria. A significantly lower gait speed and cadence as well as higher gait variability were found in people with mild cognitive impairment (MCI) and/or dementia, compared with the group with no cognitive impairment. While dual tasks appeared to amplify the differences between the two populations, the type of secondary tasks (e.g., calculations and recalling phone numbers) had an effect on gait changes. The activity and volume of different brain regions were also different between the two populations during walking. In conclusion, while this systematic review supported the potential of using gait analysis to identify cognitive impairment, there are a number of parameters researchers need to consider such as gait variables to be studied, types of dual tasks, and analysis of brain changes while performing the movement tasks.
Details
- Title
- Relationship Between Cognitive Abilities and Lower-Limb Movements: Can Analyzing Gait Parameters and Movements Help Detect Dementia? A Systematic Review
- Authors
- Swapno Aditya - University of WollongongLucy Armitage - University of WollongongAdam Clarke - University of WollongongVictoria Traynor - University of the Sunshine Coast, Queensland, School of Health - NursingEvangelos Pappas - RMIT UniversityThanaporn Kanchanawong - University of WollongongWinson Chiu-Chun Lee - University of Wollongong
- Publication details
- Sensors , Vol.25(3), pp.1-22
- Publisher
- MDPI AG
- Date published
- 2025
- DOI
- 10.3390/s25030813
- ISSN
- 1424-8220
- PMID
- 39943452
- Copyright note
- © 2025 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
- Data Availability
- No new data were created or analyzed in this study.
- Grant note
- This work is funded by an IPA (International Postgraduate Award) provided by the University of Wollongong as well as an AEGIS grant for multidisciplinary research (R-6074), which is also provided by the University of Wollongong.
- Organisation Unit
- School of Health - Nursing
- Language
- English
- Record Identifier
- 991127001802621
- Output Type
- Journal article
Metrics
26 Record Views
InCites Highlights
These are selected metrics from InCites Benchmarking & Analytics tool, related to this output
- Collaboration types
- Domestic collaboration
- Web Of Science research areas
- Chemistry, Analytical
- Engineering, Electrical & Electronic
- Instruments & Instrumentation
UN Sustainable Development Goals (SDGs)
This output has contributed to the advancement of the following goals:
Source: InCites