## 1 Introduction  
Augmented reality (AR) has been increasingly used in medical applications [1, 2, 3] as technological advances have resulted in head-mounted displays (HMD) offering higher resolution, larger field-of-view, and increased onboard processing power [4]. AR-based medical training simulation involving visual and haptic interfaces has recently gained popularity and is expected to become a useful education tool in the future [5]. AR can increase the visual realism of conventional virtual reality (VR)-based medical training and reduce the cost and size of a medical simulator by replacing the physical exterior with an augmented virtual scene. There are many challenging issues that need to be addressed to successfully use AR in medical simulation. These include: registration error [6] of the augmented virtual scene onto the real world, synchronisation [7] between visual and haptic feedback, and distortion of haptic perception [8].  
In medical training simulation, organ models are deformed by user interaction through simulated instruments or simulated hands or as part of the training scenario (e.g., dilation of the cervix over time during labour). User interaction is typically performed via a haptic interface able to provide touch feedback to the user. The resulting deformation needs to be displayed in real time on the HMD with synchronised haptic feedback. Existing AR HMDs cannot afford to compute organ deformation in real time because of the computational load. Therefore, the deformation must be computed on a separate computer, and the deformed organ model and instrument/hand must then be displayed on the HMD in real time. However, it might be difficult to transfer and render the updated simulation data on the HMD without latency. This will depend on the target medical simulation, the performance of the HMD, and the bandwidth of the network. A streaming-based method has been used to solve this problem for 3D visualisation on mobile devices [9] and 360\({}^{\circ}\) VR [10], by streaming images instead of rendering 3D objects on low-powered devices. A 3D scene taken by a specific virtual camera is converted to images and then transferred to the HMD. This can reduce both the amount of data transmission and the computational burden of rendering the 3D scene, but it is difficult to align the 3D object to the real world on the HMD as 2D images are transferred without depth information. Real-time tracking of a camera attached to the HMD can be used to generate images aligned to the real world on a PC [9; 10; 11; 12], but this results in a high computational burden and the need for an external tracking system. As HMD technology advances, it becomes affordable and feasible to render the 3D scene to the real world by using a software developer kit (SDK) such as Vuforia on an HMD in real time. This paper proposes a framework that can achieve real-time rendering of the 3D scene aligned to the real world on an off-the-shelf AR HMD by reducing the amount of data transmitted whilst retaining all the necessary information for accurate and high-resolution 3D rendering. The proposed framework allows direct rendering of the transmitted mesh model on the HMD without having to track and send its position and orientation to the PC. The proposed framework is applied and verified on a medical training simulation of vaginal examination during labour.