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Effects of Different Types of Cognitive Loading on Gait With Growing Age

To Determine the Effects of Different Types of Cognitive Loading on Gait With Growing Age

Status
Completed
Phases
NA
Study type
Interventional
Source
ClinicalTrials.gov
Registry ID
NCT06656052
Enrollment
150
Registered
2024-10-24
Start date
2024-10-24
Completion date
2024-12-30
Last updated
2025-01-13

For informational purposes only — not medical advice. Sourced from public registries and may not reflect the latest updates. Terms

Conditions

Cognitive Load, Performance, Gait Analysis

Keywords

gait, cognitive load, cognitive loading

Brief summary

The goal of this study is to determine how different types of cognitive loading affect the gait of an individual and its association with growing age. The main aim is to find out if: 1. There is a significant difference in the effect of three different methods of cognitive loading on gait parameters across age groups. 2. There is an association of cognitive loading with different age groups.

Interventions

OTHER1. working memory task.

Arithmetic test (Backward counting with serial 3 subtraction and articulation): participants will be asked to count out loud backward with serial subtraction of 3 from each number, starting with a random number provided by the researcher.

Stroop colour word test (modified Stroop test): participants will be asked to name the colour of ink that each word is printed in. This test will appear on the mobile phone in their hands while they walk to increase the effect of cognitive loading.

OTHER3. Motor Task

Participants will be asked to hold a tray of glasses filled with water and walk 10 meters to calculate the effect of cognitive loading on gait.

Sponsors

Riphah International University
Lead SponsorOTHER

Study design

Allocation
RANDOMIZED
Intervention model
PARALLEL
Primary purpose
HEALTH_SERVICES_RESEARCH
Masking
TRIPLE (Subject, Investigator, Outcomes Assessor)

Intervention model description

research

Eligibility

Sex/Gender
ALL
Age
21 Years to 70 Years
Healthy volunteers
Yes

Inclusion criteria

* Both male and female genders. * Age between 21-70 years. * Healthy individuals with normal systemic history. * Individuals with normal cognitive level (score between 0-7 on 6CIT test)

Exclusion criteria

* Individuals having any comorbidities. * Individuals having diagnosed gait disorders/deviations. * Non-cooperative participants

Design outcomes

Primary

MeasureTime frameDescription
Walking speedBaselineA smartphone-based accelerometer through a mobile app named Gait & Balance (G&B app) will be used to detect the walking speed of the participant. A decrease in walking speed is the usual effect of cognitive loading on this gait parameter.
Gait SymmetryBaselineA smartphone-based accelerometer through a mobile app named Gait & Balance (G&B app) will be used to detect the gait symmetry of the participant. A decrease in gait symmetry is the usual effect of cognitive loading on this gait parameter.
Step lengthBaselineA smartphone-based accelerometer through a mobile app named Gait & Balance (G&B app) will be used to detect the step length of the participant. An increase in step length is the usual effect of cognitive loading on this gait parameter.
Step length variabilityBaselineA smartphone-based accelerometer through a mobile app named Gait & Balance (G&B app) will be used to detect the step length variability of the participant. An increase in step length variability is the usual effect of cognitive loading on this gait parameter.
Step timeBaselineA smartphone-based accelerometer through a mobile app named Gait & Balance (G&B app) will be used to detect the step time of the participant. An increase in step time is the usual effect of cognitive loading on this gait parameter.
Step time variabilityBaselineSmartphone-based accelerometer through a mobile app named Gait & Balance (G&B app) will be used to detect the step time variability of the participant. An increase in step time variability is the usual effect of cognitive loading on this gait parameter.
Step length asymmetryBaselineA smartphone-based accelerometer through a mobile app named Gait & Balance (G&B app) will be used to detect the step length asymmetry of the participant. An increase in step length asymmetry is the usual effect of cognitive loading on this gait parameter.
Step time asymmetryBaselineA smartphone-based accelerometer through a mobile app named Gait & Balance (G&B app) will be used to detect the step time asymmetry of the participant. An increase in step time asymmetry is the usual effect of cognitive loading on this gait parameter.

Countries

Pakistan

Outcome results

None listed

Source: ClinicalTrials.gov · Data processed: Feb 4, 2026