Fuzzy AI Using VR for Collision Prevention

Player collisions cause over 70% of concussion injuries in contact sports, in addition to 50% of lower extremity injuries and 40% of catastrophic knee ligament injuries. The majority of these collisions are unanticipated, and associated with reduced neuromechanical and perceptual-motor fitness underlying an athlete's adaptability to on-field conditions. Thus, training collision anticipation necessitates a method that taps into neuromechanical and perceptual-motor fitness. Virtual reality (VR) is a tool that can target these mechanisms, while providing a safe, well-controlled environment for assessment and training. The current proposal innovates on VR with the integration of genetic fuzzy tree (GFT) artificial intelligence (AI) to drive scenario configuration designed to target modifiable mechanisms and tailored to the individual athlete's performance capabilities, for the optimization of behavior modification and skill transfer. The current study will examine test a GFT AI-driven VR collision anticipation training compared to a sham-VR training system in healthy soccer athletes.

Inclusion criteria

• healthy
• varsity high school or collegiate soccer athlete

Exclusion criteria

• unable to participate in soccer
• history of congenital or acquired cognitive, ophthalmologic, or neurological disorders including developmental delay, brain tumor, stroke, or known peripheral or central vestibular disorders
• patients who have begun anti-depressant, stimulant or anti-seizure medications for treatment of their symptoms or for other, unrelated reasons within two months of testing will be excluded from testing