BrainTrain: brain simulator for medical VR application.

Abstract

The brain is known as the most complex organ in the human body. Due to its complexity, learning and understanding the anatomy and functions of the cerebral cortex without effective learning assistance is rather difficult for medical novices and students in health and biological sciences. In this paper, we present a new virtual reality (VR) simulator for neurological education and neurosurgery. The system is based on a new three-dimensional (3D) user-computer interface design with a tangible object and a force-torque sensor. The system is combined with highly interactive computer-generated graphics and acoustics to provide multi-modal interactions through the user's sensory channels (vision, tactile, haptic and auditory). The system allows the user to feel the simulated object from its physical model that formed the interface device, while exploring or interacting with the mimicked computer-generated object in the virtual environment (VE). Unlike other passive interface devices, our system can detect the position and orientation of the interacting force in real-time, based on the system's set-up and a force-torque data acquisition technique. As long as the user is touching the model, the positions of the user's fingertip in the VE can be determined and is synchronized with the finger's motion in the physical world without requirement of an additional six-degree-of-freedom tracking device. The prior works have shown the use of the system set-up in medical applications. We demonstrate the system for neurological education and neurosurgery as a recent application. The main functions of the simulator contribute to education in neuroanatomy and visualization for diagnostic and pre-surgery planning. Once the user has touched the model, the system will mark the associated anatomy region and will provide the information of the region in terms of text note and/or sound. The user can switch from anatomy to the brain's function module, which will give details of motor, sensory or other cortical functions associated to the touch areas. In addition, the user can generate and visualize arbitrary cross-sectional images from corresponding to the magnetic resonance imaging (MRI) datasets either for training or for diagnostic purpose. The user can manipulate the cross-section image interactively and intuitively by moving the finger on the interface device.