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

Not Applicable
Recruiting
Conditions
Gait Analysis
Cognitive Load, Performance
Registration Number
NCT06656052
Lead Sponsor
Riphah International University
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.

Detailed Description

Not available

Recruitment & Eligibility

Status
RECRUITING
Sex
All
Target Recruitment
150
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)
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Exclusion Criteria
  • Individuals having any comorbidities.
  • Individuals having diagnosed gait disorders/deviations.
  • Non-cooperative participants
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Study & Design

Study Type
INTERVENTIONAL
Study Design
PARALLEL
Primary Outcome Measures
NameTimeMethod
Step timeImmediately after Cognitive loading tests

A 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.

Walking speedImmediately after Cognitive loading tests

A 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 SymmetryImmediately after Cognitive loading tests

A 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 lengthImmediately after Cognitive loading tests

A 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 variabilityImmediately after Cognitive loading tests

A 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 time variabilityImmediately after Cognitive loading tests

Smartphone-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 asymmetryImmediately after Cognitive loading tests

A 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 asymmetryImmediately after Cognitive loading tests

A 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.

Secondary Outcome Measures
NameTimeMethod

Trial Locations

Locations (1)

Riphah International University

🇵🇰

Islamabad, Pakistan

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