Athletic Performance
Conditions
Keywords
virtual reality, football players, sports training, EEG, neurophysiology, athletic performance, cognitive-motor integration, VR training
Brief summary
This study aimed to investigate the effects of virtual reality (VR)-assisted training compared with traditional training and routine practice on physical and neurophysiological performance in young professional football players. Thirty-nine male football players aged 18-19 were randomly assigned to VR training, traditional training, and control groups. The intervention lasted for several weeks and included structured training sessions integrated into regular team practice. Physical performance was assessed using balance, 30-meter sprint, and muscle strength tests, while neurophysiological outcomes were evaluated using electroencephalography (EEG). Measurements were conducted before and after the intervention period. The VR group performed immersive exercise-based training using VR applications designed to improve coordination, strength, endurance, and cognitive-motor interaction, while the traditional group performed the same exercises without VR support. The study hypothesized that VR-assisted training would lead to greater improvements in both physical performance and brain activity compared to traditional and control conditions.
Interventions
BEHAVIORALVirtual Reality Training
Virtual reality (VR)-based training was performed using immersive applications such as Head Football, Rezzil Player, FitXR, and similar platforms. Participants completed structured exercise sessions after regular team practice. The training focused on improving balance, strength, endurance, coordination, and cognitive-motor integration. Sessions were conducted using a VR headset with defined work-rest intervals and consisted of repeated exercise sets designed to simulate sport-specific movements in an immersive environment.
BEHAVIORALTraditional Training
Participants performed the same exercise content as the VR group under coach supervision without the use of virtual reality technology. Training sessions focused on improving balance, strength, endurance, and coordination using conventional training methods. Exercises were structured with similar sets and rest intervals as the VR group and were completed after regular team practice.
Sponsors
Recep Tayyip Erdogan University
The Scientific and Technological Research Council of Turkey
Study design
Allocation
RANDOMIZED
Intervention model
PARALLEL
Primary purpose
OTHER
Masking
NONE
Intervention model description
Participants were randomly assigned into three parallel groups: virtual reality training group, traditional training group, and control group.
Eligibility
Sex/Gender
MALE
Age
18 Years to 19 Years
Healthy volunteers
No
Inclusion criteria
* \- Male professional football players participating in licensed competitions within a professional club youth academy * Age between 18 and 19 years * 5-8 years of active football playing experience * No chronic pain or musculoskeletal injury affecting performance * Willingness to participate and signed informed consent form * Ability to attend both virtual reality and training sessions regularly * Training frequency of approximately 3 sessions per week * Use of supplements only for general health purposes without performance enhancement effects
Exclusion criteria
* \- Any injury that may impair performance or interaction with virtual reality training * Neurological or psychological disorders affecting VR interaction * Previous experience with VR-based training programs * History of epilepsy or seizure disorders * History of frequent headaches or migraines * Balance disorders or vestibular dysfunction * Visual impairments such as depth perception problems or color blindness * Non-compliance with study protocol or missing informed consent
Design outcomes
Primary
| Measure | Time frame | Description |
|---|---|---|
| EEG Spectral Power (Theta, Alpha, Beta Bands - Anterior Region) | Baseline (Week 0) and Post-intervention (Week 8) | EEG was recorded using a 32-channel system (BrainAccess Extended+). Power spectral density was calculated using the Welch method, and absolute power values (µV²) were derived for theta (4-8 Hz), alpha (8-12 Hz), and beta (12-30 Hz) frequency bands. Analyses were performed by averaging electrodes in the anterior region. |
| EEG Functional Connectivity (Anterior-Central Coherence) | Baseline (Week 0) and Post-intervention (Week 8) | Functional connectivity was assessed using coherence analysis between anterior and central brain regions. Coherence values were calculated for theta (4-8 Hz) and alpha (8-12 Hz) frequency bands using Welch-based methods. |
| Dynamic Balance (Togu Challenge Disc Test) | Baseline (Week 0) and Post-intervention (Week 8) | Balance performance was assessed using the Togu Challenge Disc. Participants performed double-leg and single-leg balance tasks (dominant and non-dominant), and the best score based on the device's standardized scoring system (1-5 scale) was recorded. |
| Sprint Speed (30-meter Sprint Test) | Baseline (Week 0) and Post-intervention (Week 8) | Sprint performance was measured using a 30-meter sprint test with a photoelectric timing system. The best time (seconds) from two trials was recorded. |
| Isometric Knee Extension Strength | Baseline (Week 0) and Post-intervention (Week 8) | Muscle strength was assessed using a handheld dynamometer. Maximum isometric knee extension force was measured for 5 seconds, and the highest value (kg) from repeated trials was recorded for the leg. |
Secondary
| Measure | Time frame | Description |
|---|---|---|
| P300 Latency (Event-Related Potential) | Baseline (Week 0) and Post-intervention (Week 8) | P300 latency (ms) was measured using ERP analysis during virtual reality training sessions. The P300 component was identified within the 300-600 ms time window. |
| P300 Amplitude (Event-Related Potential) | Baseline (Week 0) and Post-intervention (Week 8) | P300 amplitude (µV) was recorded during virtual reality training sessions using ERP analysis, reflecting cognitive processing and attentional resource allocation. |
Countries
Turkey (Türkiye)
Outcome results
None listed