Zhang Yuru

A Neurosurgical Robotic System under Image-Guidance

In this paper, a newly designed extrinsic-image-guided robotic system for frameless stereotactic neurosurgery in China is introduced. At first the procedure of stereotactic neurosurgery is summarized. Secondly the main structure of the system is addressed. Medical augmented reality is utilized for surgeon to choose best solution and to simulate the operation. Then the issues about telesurgery and safety are discussed. In the end, the system accuracy test and clinic experiment are presented.

Multi-modal human-machine interaction for human intelligence augmentation

Human-machine symbiosis and harmony is an ultimate goal of human-machine interaction (HMI). Recently, the rapid development of artificial intelligence has given rise to concern regarding the domination of machine intelligence over human intelligence. Enhancing human intelligence through multi-modal HMI technology is becoming an important research topic. The studies on neural plasticity indicate that the core capabilities of human cognition including attention control ability and working memory capacity could be enhanced and trained through several approaches including visual-auditory games, haptic interaction tasks, transcranial electromagnetic stimulation, and brain-computer interfaces. In this paper, we propose a systematic paradigm of augmenting cognition through HMI tasks by seamlessly integrating haptic-visual-aural multisensory feedback. This paradigm is constructed on analyzing the inherent features of virtual reality including immersion, interaction, and imagination. Based on the concept of cybernetics, cognitive enhancement methods based on Hebbian learning are proposed to achieve several goals including the realization of controllable cognitive loads, immediate physiological feedback, and bidirectional mind-body interaction. The proposed paradigm may provide new tools for revealing the mechanism of neural plasticity and promote the development of novel human-machine interaction devices; it is promising in the generation of practical values in the domain of personalized education, neural rehabilitation, and cognitive training of specialized personnel.

Reverse driving character of 2-DOF closed chain haptic device

Reverse driving character plays an important role in evaluating the performance of a haptic device, and it is the primary rule in the mechanical design. This article mainly investigates the problem of 2-DOF haptic device design for improving reverse driving character. Firstly, a 2-DOF closed chain haptic device is designed in the paper and a physical prototype is produced in the factory; Based on the physical prototype, the 2-DOF haptic device is analyzed with the method of dynamics which is called Lagrangian equation, and the reverse driving character of the haptic device is evaluated by the Generalized Inertia Ellipsoid (GIE) which can be directly illustrated by a graph; With the help of changing the material of some components, the reverse driving character of the haptic device can be improved, so that an appropriate 2-DOF haptic device can be obtained in the design aftertime.