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 markers to define a delivery region and then registers the pre-scanned neonatal head within this area. This process enables spatially accurate overlay of virtual guiding hands near the manikin, allowing trainees to follow expert trajectories reinforced by haptic interaction. Experimental evaluations demonstrate that the system achieves accurate and stable manikin localization on a standalone headset, ensuring practical deployment without external computing resources. A large-scale user study involving 83 fourth-year medical students was subsequently conducted to compare MR-based and virtual reality (VR)-based childbirth training. Four senior obstetricians independently assessed performance using standardized criteria. Results showed that MR training achieved significantly higher scores in delivery, post-delivery, and overall task performance, and was consistently preferred by trainees over VR training.

翻译：医学生获得阴道分娩实践操作的机会日益受到临床轮转时间缩短、患者抵触情绪以及分娩过程不可预测性的限制。为减轻临床医师的教学负担并提高学员的学习效率，我们提出了一种用于分娩训练的混合现实（MR）系统，该系统将虚拟引导与触觉人体模型交互相结合，从而在保留真实触觉反馈的同时，实现无需现场专家持续监督的独立训练。该系统通过空间标定外部RGB-D相机，扩展了商用头戴式显示器（HMD）的透视功能，实现了物理训练对象的实时视觉融合。基于此功能，我们实现了一种由粗到精的定位流程：首先通过基准标记对齐产妇人体模型以定义分娩区域，然后在该区域内配准预先扫描的新生儿头部。这一过程使得虚拟引导手能够以空间精确的方式叠加在人体模型附近，让学员能够遵循通过触觉交互强化的专家操作轨迹。实验评估表明，该系统在独立头显设备上实现了准确稳定的人体模型定位，确保了无需外部计算资源的实际部署。随后开展了一项涉及83名四年级医学生的大规模用户研究，以比较基于MR和基于虚拟现实（VR）的分娩训练。四位资深产科医师依据标准化标准独立评估操作表现。结果显示，MR训练在分娩阶段、分娩后阶段及整体任务表现上均获得显著更高的评分，并且学员对其的偏好持续高于VR训练。