A Mixed Reality System for Robust Manikin Localization in Childbirth Training
Haojie Cheng, Chang Liu, Abhiram Kanneganti, Mahesh Arjandas Choolani, Arundhati Tushar Gosavi, and Eng Tat Khoo

TL;DR
This paper presents a mixed reality system for childbirth training that combines virtual guidance with tactile feedback, improving localization accuracy and trainee performance compared to VR-only methods.
Contribution
The paper introduces a novel MR system with a spatially calibrated RGB-D camera and a coarse-to-fine localization pipeline for realistic childbirth training.
Findings
MR system achieves accurate, stable manikin localization on standalone headsets.
Trainees perform better with MR training than VR in delivery tasks.
MR training is preferred by medical students over VR-based methods.
Abstract
Opportunities for medical students to gain practical experience in vaginal births are increasingly constrained by shortened clinical rotations, patient reluctance, and the unpredictable nature of labour. To alleviate clinicians' instructional burden and enhance trainees' learning efficiency, we introduce a mixed reality (MR) system for childbirth training that combines virtual guidance with tactile manikin interaction, thereby preserving authentic haptic feedback while enabling independent practice without continuous on-site expert supervision. The system extends the passthrough capability of commercial head-mounted displays (HMDs) by spatially calibrating an external RGB-D camera, allowing real-time visual integration of physical training objects. Building on this capability, we implement a coarse-to-fine localization pipeline that first aligns the maternal manikin with fiducial…
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Taxonomy
TopicsSurgical Simulation and Training · Augmented Reality Applications · Virtual Reality Applications and Impacts
