Co-Designing Dynamic Mixed Reality Drill Positioning Widgets: A Collaborative Approach with Dentists in a Realistic Setup

TL;DR

The paper tackles the challenge of precise dental drill positioning in complex 5-DoF space by co-designing mixed reality widgets with dentists and MR experts. It introduces two static widgets (Entry Point, Target Axis) and two dynamic widgets (DWEP, DWTA) and evaluates them in a realistic VR/AR dental setup, measuring positional and rotational accuracy, task time, and workload via NASA-TLX. Results show dynamic widgets improve both positional and rotational precision over static ones, though at the cost of increased mental and physical demand and longer task times, with age and gaming experience modulating performance. The study provides actionable insights into widget design trade-offs, demonstrates the value of co-design in medical HCI, and offers open-source DW assets to foster future research and broader application across medical/industrial precision tasks.

Abstract

Mixed Reality (MR) is proven in the literature to support precise spatial dental drill positioning by superimposing 3D widgets. Despite this, the related knowledge about widget's visual design and interactive user feedback is still limited. Therefore, this study is contributed to by co-designed MR drill tool positioning widgets with two expert dentists and three MR experts. The results of co-design are two static widgets (SWs): a simple entry point, a target axis, and two dynamic widgets (DWs), variants of dynamic error visualization with and without a target axis (DWTA and DWEP). We evaluated the co-designed widgets in a virtual reality simulation supported by a realistic setup with a tracked phantom patient, a virtual magnifying loupe, and a dentist's foot pedal. The user study involved 35 dentists with various backgrounds and years of experience. The findings demonstrated significant results; DWs outperform SWs in positional and rotational precision, especially with younger generations and subjects with gaming experiences. The user preference remains for DWs (19) instead of SWs (16). However, findings indicated that the precision positively correlates with the time trade-off. The post-experience questionnaire (NASA-TLX) showed that DWs increase mental and physical demand, effort, and frustration more than SWs. Comparisons between DWEP and DWTA show that the DW's complexity level influences time, physical and mental demands. The DWs are extensible to diverse medical and industrial scenarios that demand precision.

Figures (15)

• Figure 1: Static and Dynamic MRDPWs demonstration of only assistive virtual elements; entry point, target axis, DWEP dynamic widget with entry point, DWTA dynamic widget and target axis.
• Figure 2: Compositions of DW: positional and rotational components (a, b), the tool is far from the target, forms are in the periphery and away from each other (c),the tool is on target, forms are nearby (d).
• Figure 3: Implementation of three dynamic visibility areas: Area 1: Invisible forms, Area 2: Visible Collimation Area with dynamic and non-linear behavior, Area 3: Visible static forms.
• Figure 4: Implementation of the virtual magnifying loupe; top view of lenses' angles and positions (left), two quads attached to the headset(right).
• Figure 5: Gender/profession of dentists participated in the user study.