Clinical Application to Improve the "Depth Perception Problem" by Combining Augmented Reality and a 3D Printing Model

Area of Science:

• Medical Imaging
• Human-Computer Interaction
• Surgical Technology

Background:

• Augmented reality (AR) technology offers potential for intraoperative evaluation and medical education.
• A significant challenge in AR applications is the illusion of depth, impacting usability.
• Improving depth perception is crucial for effective AR implementation in medicine.

Purpose of the Study:

• To investigate methods for improving depth perception in augmented reality systems.
• To evaluate the impact of different 3D model and hologram combinations on spatial understanding.
• To assess the influence of observation angles on depth perception accuracy in AR.

Main Methods:

• Two experiments were conducted using AR devices with various 3D models and hologram projection depths.
• Experiment 1 assessed the ease of understanding positional relationships with holograms on surface vs. deep layers.
• Experiment 2 quantitatively measured distance errors between surface and deep points from multiple angles.

Main Results:

• Positional relationships were more easily understood with holograms projected on bone models (surface layer) compared to body surface models (deeper layer).
• Distance measurement errors in Experiment 2 were not significantly different across conditions.
• The observed errors were insufficient to cause misunderstandings of depth relationships.

Conclusions:

• AR systems using 3D models and holograms are suitable for preoperative planning and anatomical studies.
• Projecting holograms on deeper models and utilizing multiple observation angles enhances anatomical understanding.
• These approaches mitigate depth perception issues, reducing confusion and improving AR utility in medical applications.