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.
Study Type
INTERVENTIONAL
Allocation
RANDOMIZED
Purpose
HEALTH_SERVICES_RESEARCH
Masking
TRIPLE
Enrollment
150
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.
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.
Riphah International University
Islamabad, Pakistan
Walking speed
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.
Time frame: Baseline
Walking speed
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.
Time frame: During three cognitive tasks
Walking speed
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.
Time frame: Immediately after Cognitive loading tests
Gait Symmetry
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.
Time frame: Baseline
Gait Symmetry
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.
Time frame: During Cognitive loading tests
Gait Symmetry
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.
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Time frame: Immediately after Cognitive loading tests
Step length
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.
Time frame: Baseline
Step length
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.
Time frame: During Cognitive loading tests
Step length
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.
Time frame: Immediately after Cognitive loading tests
Step length variability
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.
Time frame: Baseline
Step length variability
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.
Time frame: During Cognitive loading tests
Step length variability
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.
Time frame: Immediately after Cognitive loading tests
Step time
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.
Time frame: Baseline
Step time
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.
Time frame: During Cognitive loading tests
Step time
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.
Time frame: Immediately after Cognitive loading tests
Step time variability
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.
Time frame: Baseline
Step time variability
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.
Time frame: During Cognitive loading tests
Step time variability
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.
Time frame: Immediately after Cognitive loading tests
Step length asymmetry
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.
Time frame: Baseline
Step length asymmetry
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.
Time frame: During Cognitive loading tests
Step length asymmetry
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.
Time frame: Immediately after Cognitive loading tests
Step time asymmetry
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.
Time frame: Baseline
Step time asymmetry
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.
Time frame: During Cognitive loading tests
Step time asymmetry
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.
Time frame: Immediately after Cognitive loading tests