The relationship between spatiotemporal gait parameters and cognitive function in healthy adults: protocol for a...

Area of Science:

• Neuroscience
• Gerontology
• Biomedical Engineering

Background:

• Motor dysfunctions like slower walking speed may precede dementia and mild cognitive impairment.
• Motoric cognitive risk (MCR) syndrome links gait changes with self-reported cognitive issues.
• Previous studies showed correlations between gait parameters and cognitive function but had small sample sizes.

Purpose of the Study:

• To establish the Cognitive-Gait (CoGait) database with multi-dimensional walking and cognitive data from a large, healthy adult sample.
• To identify early sub-clinical cognitive risk by analyzing gait as a biomarker.
• To create a predictive model for cognitive performance based on gait analysis.

Main Methods:

• Recruit 450 healthy participants (aged 20+) without neurological, musculoskeletal, or psychiatric disorders.
• Conduct comprehensive cognitive assessments including reaction time, Go/No-Go, Stroop, N-back, Trail Making Test, digit span, MMSE, MoCA, and GDS-15.
• Measure gait using an inertial measurement unit-based 3D motion capture system, analyzing joint kinematics and lower leg positioning at comfortable and faster paces.

Main Results:

• The study aims to reveal the relationship between walking and cognitive performance in a large, healthy adult population.
• Establish a predictive model for cognitive performance based on gait parameters.
• The CoGait database will serve as a standard for walking and cognitive functions.

Conclusions:

• This study will be the first to investigate walking and cognitive performance relationships using multi-dimensional data from a large, general adult population.
• The CoGait database is expected to become a standard reference for gait and cognitive functions.
• Findings will support the evaluation of psychomotor function for early identification of sub-clinical cognitive risk, including MCR syndrome.