Page 59 - THEi Student Applied Research Presentations 2024

HOW EFFECTIVE CAN MACHINE LEARNING
ANALYZE LONG-DISTANCE RUNNING PATTERNS

AND PREDICT LOWER LIMB INJURY RISKS

USING MOTIONMETRIX DATA?

ABSTRACT

RESEARCH BACKGROUND
Long-distance running is a beloved activity that brings joy and vitality to individuals
who embrace an active lifestyle. Engaging in long-distance running carries a higher risk
of lower limb overuse injuries. Approximately 50% of runners experienced injuries. The
majority of these injuries (around 70% to 80%) can be attributed to lower limb overuse CHU SAI KIT
damage. Critical lower limb areas, such as the knee, ankle, and calf, are commonly
injured due to overuse by runners.
BSocSc (Hons) in Sports and
FINDINGS Recreation Management
Hip abduction is the most important feature for preventing lower limb injury while Department of Sport and Recreation
running.
• The hip abductors play important role in stabilizing the pelvis. Insufficient strength
of the hip abductors may increase the possibility of injury (Vannatta & Kernozek,
2021) (Heinert et al., 2008). OBJECTIVES
Knee alignment
• Misalignment of the knee can disrupt the kinetic chain and biomechanics of the This study aims to fill in the research
lower limbs. gap on MotionMetrix data and machine
• Knee disruption increases the risk of injuries and may lead to compensatory learning in long-distance running.
movements and alter gait patterns (Tian et al., 2020). 1. Understand the relationship between
running posture, injury risk,
ABOUT THE INVESTIGATOR and performance outcomes in
long-distance runners.
I am a passionate researcher in the field of machine learning. My interests lie in 2. Develop effective training strategies
applying machine learning to solve real-world problems. My career goal is to become and lower limb injury prevention
a proficient data scientist and utilize machine learning techniques to provide innovative programs.
solutions across various domains. I am fortunate to have Mr. HO Man Kit, Indy as my
supervisor for my graduation thesis. He is a highly experienced and knowledgeable
mentor in the field of machine learning, and I am honored to conduct my research
under his guidance.

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