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Sensor-Based and VR-Assisted Visual Training Enhances Visuomotor Reaction Metrics in Youth Handball Players

Sensors (Basel). 2026 Apr 21;26(8):2555. doi: 10.3390/s26082555. ABSTRACT BACKGROUND: Sensor-based systems and virtual reality (VR) technologies provide new opportunities for the objective, technology-driven assessment and training of visuomotor performance in applied contexts s…

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Sensors (Basel). 2026 Apr 21;26(8):2555. doi: 10.3390/s26082555.

ABSTRACT

BACKGROUND: Sensor-based systems and virtual reality (VR) technologies provide new opportunities for the objective, technology-driven assessment and training of visuomotor performance in applied contexts such as sport.

METHODS: This study examined the effects of an integrated visual training program combining stroboscopic stimulation, VR-based vergence exercises, and instrumented reaction-light tasks in adolescent handball players. Twenty-eight adolescent handball players (under-18 competitive level) completed two baseline assessments separated by six weeks, followed by a six-session training program (approximately 15 min per session) integrated into regular team practice. The intervention targeted visuomotor reaction speed, accommodative dynamics, and peripheral visual responsiveness using sensor-based and virtual reality-assisted stimuli.

RESULTS: Compared with both baseline measurements, the intervention produced selective improvements in accommodative facility (cycles per minute, cpm)-particularly near-far focusing speed-and in multiple reaction-time conditions (milliseconds, ms) involving manual and decision-based responses. Specific peripheral-field locations showed increased response scores, whereas binocular alignment, AC/A ratio, near phoria, and stereoscopic acuity remained unchanged.

CONCLUSIONS: These findings indicate that technology-supported visual training protocols incorporating sensor-based reaction systems and VR stimuli were associated with measurable adaptations in dynamic visuomotor processing while preserving fundamental binocular vision parameters.

PMID:42076664 | PMC:PMC13120118 | DOI:10.3390/s26082555