Kinect-Based Vision System of Mine Rescue Robot for Low Illuminous Environment

This paper presents Kinect-based vision system of mine rescue robot working in illuminous underground environment. The somatosensory system of Kinect is used to realize the hand gesture recognition involving static hand gesture and action. A K-curvature based convex detection method is proposed to fit the hand contour with polygon. In addition, the hand action is completed by using the NiTE library with the framework of hand gesture recognition. In addition, the proposed method is compared with BP neural network and template matching. Furthermore, taking advantage of the information of the depth map, the interface of hand gesture recognition is established for human machine interaction of rescue robot. Experimental results verify the effectiveness of Kinect-based vision system as a feasible and alternative technology for HMI of mine rescue robot

Study on synthesis and properties of nanoparticles loaded with amaryllidaceous alkaloids

Alzheimer’s disease (AD) is the most common disease among the elderly people and a major social and medical problem. Amaryllidaceous alkaloids, acting as acetylcholinesterase inhibitors, represent a potential treatment of AD. However, they also have some deficiencies, such as extensive toxicity and widespread side effects. In order to improve the bioavailability and reduce the toxic and side effects, brain targeting of amaryllidaceous alkaloids was enhanced by considering low density lipoprotein (LDL) receptors of blood-brain barrier (BBB) endothelial cells as therapeutic targets. Amaryllidaceous alkaloids were highly selectively and quantitatively riveted to the surface of low density lipoproteins by using a new method - mild click chemistry. The structure of products has been characterized by NMR, FT-IR, and other methods. In addition, drug loading rate, encapsulation rate, and drug release by the nanoparticles were determined to assess the quality of the nanoparticles

Development of a New Robotic Ankle Rehabilitation Platform for Hemiplegic Patients after Stroke

A large amount of hemiplegic survivors are suffering from motor impairment. Ankle rehabilitation exercises act an important role in recovering patients’ walking ability after stroke. Currently, patients mainly perform ankle exercise to reobtain range of motion (ROM) and strength of the ankle joint under a therapist’s assistance by manual operation. However, therapists suffer from high work intensity, and most of the existed rehabilitation devices focus on ankle functional training and ignore the importance of neurological rehabilitation in the early hemiplegic stage. In this paper, a new robotic ankle rehabilitation platform (RARP) is proposed to assist patients in executing ankle exercise. The robotic platform consists of two three-DOF symmetric layer-stacking mechanisms, which can execute ankle internal/external rotation, dorsiflexion/plantarflexion, and inversion/eversion exercise while the rotation center of the distal zone of the robotic platform always coincides with patients’ ankle pivot center. Three exercise modes including constant-speed exercise, constant torque-impedance exercise, and awareness exercise are developed to execute ankle training corresponding to different rehabilitation stages. Experiments corresponding to these three ankle exercise modes are performed, the result demonstrated that the RARP is capable of executing ankle rehabilitation, and the novel awareness exercise mode motivates patients to proactively participate in ankle training