A mixed reality hand fracture simulator for virtual K-wire fixation

Proper management of hand fractures requires accurate reduction of bone fragments and stabilization with Kirschner wire (K-wire) fixation. Limited case exposure in residency and a shortage of feedback-rich skills assessment constrain deliberate practice. This work describes a mixed reality hand fracture simulator that integrates a realistic physical model with instrument tracking, real-time virtual image guidance, and quantitative performance feedback for training percutaneous K-wire fixation.

We developed a benchtop mixed reality (MR) simulator integrating an electromagnetic (EM) tracker, a three-dimensional (3D)-printed hand model with fracture patterns, and a microcontroller-enabled K-wire driver. To ensure high physical-to-virtual geometric correspondence, the 3D-printed components were optically scanned to serve as virtual representations. A custom application provides real-time 3D visualization, guidance, and simulated virtual X-rays. To evaluate system accuracy, five users performed repeated paired-point rigid registrations. Accuracy was assessed by calculating fiducial registration error (FRE) and target registration error (TRE) across 25 attempts using a pre-calibrated stylus and the tracked K-wire driver. Image guidance capabilities were evaluated by measuring positional and angular alignment errors of the tracked K-wire driver against predefined ideal trajectories.

The overall mean FRE was 0.69 ± 0.11 mm for the hand model (11 fiducials) and 0.60 ± 0.09 mm for the K-wire driver (8 fiducials). Target localization to six ground-truth targets yielded a mean TRE of 0.69 ± 0.10 mm with the stylus and 0.82 ± 0.16 mm with the driver. Trajectory alignment demonstrated maximum positional variance during parallel approaches to the bone (K-wire 1), highlighting specific procedural challenges.

The MR hand fracture simulator platform enables repeated practice of fracture reduction and K-wire placement with interactive guidance, simulated X-rays, and objective metrics. The system is able to achieve millimeter-scale alignment suitable for procedural training. Future work will evaluate learning outcomes and skill transfer in surgical trainees.