Stiffness Discrimination Thresholds of Force-Feedback Gloves for Volumetric Data Exploration in Virtual Reality.

Abstract

Can force-feedback gloves deliver the haptic fidelity required for medical training or engineering design in VR? We systematically measured stiffness discrimination thresholds using Dexmo force-feedback gloves through psychophysical experiments with 23 participants exploring virtual volumetric data. Our dual-method approach-adaptive staircase procedures and population-level psychometric functions-revealed Just Noticeable Difference (JND) thresholds of 48.1% (Low Reference) and 26.3% (High Reference), far exceeding the 10-20% thresholds achievable with natural touch. This performance gap, compounded by a 1.8:1 Weber fraction ratio indicating perceptual scaling violations, raises questions about current haptic VR capabilities. However, spatial analysis uncovered actionable insights: positioning interactions at mid-reach positions (avoiding near-body and extended-arm extremes) improves accuracy by 7%. Our findings establish critical benchmarks for haptic VR development and provide evidence-based guidelines for designing applications that work within current technological constraints rather than assuming real-world haptic equivalence.