Assessment of spatial distortions affecting realism and interaction in mixed and augmented reality

Abstract Mixed and augmented reality applications increasingly rely on head-mounted displays, yet systematic methods for quantifying reality distortion remain underdeveloped. This study establishes a multidimensional kinematic framework to identify and measure perceptual distortions induced by optical see-through (Microsoft HoloLens2) and video pass-through (Varjo XR3) architectures. Fifty participants performed three-dimensional reaching tasks under baseline, HoloLens2, and Varjo XR3 conditions. The framework integrated path tortuosity, linear jerk, and trajectory variance as complementary metrics capturing spatial deviation, movement quality, and consistency. Video pass-through systems exhibited significant distortions across all parameters: 11.3% increased tortuosity (p < 0.001), 217% elevated jerk (p = 0.0015), and reduced trajectory consistency (SD = 0.347 vs. 0.203 baseline). Optical see-through preserved near-baseline performance (2.6% tortuosity increase, p = 0.379). The multidimensional kinematic assessment framework demonstrates that conventional velocity-based metrics inadequately capture device-specific distortion patterns, necessitating comprehensive evaluation protocols for clinical XR system selection, while jerk and trajectory variance provide discriminative power for technology evaluation. For precision-critical applications, e.g., surgical guidance, industrial assembly and rehabilitation, this methodological approach enables evidence-based selection between optical architectures based on quantifiable perceptual fidelity rather than subjective assessment. The multidimensional kinematic framework establishes quantitative benchmarks for evaluating perceptual fidelity in mixed reality systems. The multidimensional kinematic assessment framework demonstrates that conventional velocity-based metrics inadequately capture device-specific distortion patterns, necessitating comprehensive evaluation protocols for clinical XR system selection.