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Fuzzy AI Using VR for Collision Prevention

Genetic Fuzzy Artificial Intelligence Driven Virtual Reality for Prevention of Collision-based Injury

Status
Completed
Phases
NA
Study type
Interventional
Source
ClinicalTrials.gov
Registry ID
NCT03915119
Acronym
CAT
Enrollment
45
Registered
2019-04-16
Start date
2018-01-01
Completion date
2019-09-30
Last updated
2020-02-07

For informational purposes only — not medical advice. Sourced from public registries and may not reflect the latest updates. Terms

Conditions

Injuries

Brief summary

The purpose of this study is to develop and test a VR training system that integrates GFT AI with virtual obstacle scenarios that, when compared to a sham-VR training system, is hypothesized to increase neuromechanical and perceptual-motor fitness, decrease collision frequency and impact forces for soccer athletes, during a single training session and also when assessed at approximately 1 week and 1 month following training.

Detailed description

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.

Interventions

OTHERGFT AI training

navigates a cluttered environment of stationary and moving/pursuing virtual obstacles to reach a way-point as quickly and efficiently as possible. Block order and difficulty, as well as the behavior of the obstacles in each block, will be driven by the AI and statistically weighted to specifically target the perceptual-motor and neuromechanical mechanisms based on each athlete's visit 1 performance

Sponsors

Children's Hospital Medical Center, Cincinnati
Lead SponsorOTHER

Study design

Allocation
RANDOMIZED
Intervention model
PARALLEL
Primary purpose
OTHER
Masking
NONE

Eligibility

Sex/Gender
ALL
Age
14 Years to 22 Years
Healthy volunteers
Yes

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

Design outcomes

Primary

MeasureTime frameDescription
Pro-saccades test10 minutesPro-saccades will be tested as participants track discrete target motion that will jump randomly by 14, 16, 18, 20, 22, or 24˚ on the screen in a horizontal and vertical direction, at intervals varying pseudo randomly between 1.0 and 2.0 s. The current fixation target will be extinguished at the same time as the next peripheral target appears. The test sequence will take 30 s/trial (2 trials) and all participants will be instructed to follow the targets as quickly and accurately as possible

Secondary

MeasureTime frameDescription
Self paced saccades10 minutesSelf-paced saccades will be assessed as the participant glances back and forth as quickly and accurately as possible between two constantly visual targets at ± 15˚ horizontally from one another. This test will take 30 s per trial and the participant will perform 2 trials.
Anti-saccades test10 minutesAnti-saccades will be tested as participants are presented discrete targets that jump randomly by 14, 16, 18, 20, 22, or 24˚ on the screen in a horizontal and vertical direction, at intervals varying pseudo randomly between 1.0 and 2.0 s while a cross-hairs is present in the center of the screen. The athletes will be instructed to fixate on the cross-hairs and at the moment each object appears, to saccade in the opposite direction and then return their gaze back to the cross-hairs for the start of the next trial.

Countries

United States

Outcome results

None listed

Source: ClinicalTrials.gov · Data processed: Feb 4, 2026