Color-Based Visual Coordination Aids for Enhanced Gestural Interaction

As gesture-based contactless interfaces have gained prominence in healthcare, gaming, and industrial automation, performance degradation during rapid interaction remains a critical barrier to widespread adoption. Although existing research has focused predominantly on controlled virtual environments, the role of visual coordination cues in time-sensitive gesture-recognition scenarios remains largely unexplored. This study examined the impact of color-based visual coordination aids on user performance in rapid gesture-based tasks using Leap Motion technology. A game was designed where the participants interacted with the game setup using contactless hand tracking without electronic wearable sensors. Twelve participants were initially enrolled and began the study under two conditions: bare hands and sphere-color-matching gloves; however, two participants did not complete both conditions, and the final analysis included data from ten participants who completed the full protocol. Performance under the glove condition improved compared to bare hands. Accuracy increased from 80.33% to 84.33%, improving by 4 percentage points, and average error per session decreased by 75% from 2.40 to 0.60. Additionally, 70% of participants showed better performance accuracy. A paired t-test revealed statistically significant improvements with gloves, t(9) = 2.102, p = 0.035, α = 0.05, Cohen’s d_z = 0.665, 95% CI for d_z [0.082, 1.248]. Mixed-effects modeling confirmed that the intervention benefit generalized across both standard and accelerated task difficulty conditions (Gloves × Difficulty interaction: p = 0.473). These results show that a simple, low-cost visual coordination technique can significantly improve accuracy in time-sensitive human-computer interactions.