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Lower Limb Strength and Power as Predictors of Brain Blood Flow During Exercise
Sponsor: Lincoln University College
Summary
This study aims to investigate the predictive value of lower limb muscle strength and explosive power on exercise-induced prefrontal hemodynamic responses. Using an interpretable machine learning framework (GCAT-Net), the research analyzes how various physical performance indicators-such as isokinetic muscle strength, 1RM leg press, and vertical jump metrics-can predict oxygenated hemoglobin (ΔHbO) changes in the bilateral dorsolateral prefrontal cortex (DLPFC) during moderate-intensity cycling.
Official title: Lower Limb Muscle Strength and Power Predict Exercise-Induced Prefrontal Hemodynamic Response: An Interpretable Machine Learning Study Using fNIRS Data
Key Details
Gender
All
Age Range
18 Years - 60 Years
Study Type
INTERVENTIONAL
Enrollment
256
Start Date
2025-03-01
Completion Date
2025-03-15
Last Updated
2026-05-08
Healthy Volunteers
Yes
Interventions
Standardized Lower-Limb Physical Performance Assessment and Aerobic Exercise Task
Participants undergo a comprehensive physiological and biomechanical assessment protocol divided into three phases. First, demographic and morphological data (Age, Sex, BMI, and Body Fat %) are collected, followed by a maximal oxygen consumption (VO\_2max) test using a Bruce-modified ramp protocol on a cycle ergometer. Second, participants complete a standardized lower-limb neuromuscular battery, including isokinetic strength testing at 60°/s (peak torque for knee, hip, and ankle) via a Biodex System 4 Pro, a 1RM leg press, and explosive power assessments comprising Countermovement Jumps (CMJ), Squat Jumps (SJ), and 30m sprints. Finally, cortical hemodynamic activity is monitored using a 16-channel fNIRS system (NIRSport2) over the bilateral dorsolateral prefrontal cortex (DLPFC) during a 6-minute constant-load cycling task at 60% VO\_2max.
Locations (1)
Moscow State University of Sport and Tourism
Moscow, Russia