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Portable/implantable multimedia tools have become increasingly popular in recent years, and data transfer’s security is so important in models of these tools. To ensure data’s stable transfer, a robust voltage regulator is required. Meanwhile, this data transfer usually requires relative complex voltage supplies from limited voltage sources. These specific voltage supplies, which are usually higher than the battery’s output voltage, are widely used by multimedia tools to accomplish interactive communication with the human body. This paper describes a novel regulator design to generate higher voltages from a lower voltage supply (e.g. battery’s voltage), and the robustness of this regulator could ensure data transfer’s security in multimedia models. We first designed a reconfigurable output voltage for compatibility with different multimedia applications. The regulator was made to be highly efficient, fulfilling a critical characteristic for portable/implantable multimedia models. This design also demonstrated reliability and robustness, allowing the highest output voltage to approach to the process tolerance. From simulation, it was indicated that the regulator design had better electrical parameters and more robustness than previous studies, which could ensure the data security for multimedia models.

Advanced wireless technology in multimedia devices that is used widely in daily life can be applied to medical devices, such as spinal cord stimulator (SCS), for functioning as a multimedia node. This paper describes a SCS prototype that functions as a sensor and actuator for scientific research and potential clinical applications. The SCS is able to generate voltage/current outputs in 4 channels (with 16 electrodes selection) and has the capacity to sense tissue impedance in real-time. Furthermore, the SCS allows for wireless communication with high power efficiency at a long range (up to 2 m). Benefiting from its novel designs for high power efficiency and wireless signal/power transmission, the SCS also satisfies the long-term animal/clinical test requirements for maintaining multimedia link. Our experiments also indicate that the SCS has better performance, such as in electrical parameters and versatility, to relevant studies.

Aerial image categorization framework.Discriminative subgraphs.Subgraph mining.SVM. Aerial image categorization plays an indispensable role in remote sensing and artificial intelligence. In this paper, we propose a new aerial image categorization framework, focusing on organizing the local patches of each aerial image into multiple discriminative subgraphs. These meaningful subgraphs reflect both the geometric property and the color distribution of an aerial image. First, each aerial image is decomposed into a collection of regions in terms of their color intensities. Thereby region connected graph (RCG), which models the connection between the spatial neighboring regions, is constructed to encode the spatial context of an aerial image. Second, a novel subgraph mining technique is adopted to discover the frequent structures in the RCGs constructed from the training aerial images. Thereafter, a set of refined structures is selected among the frequent ones toward being highly discriminative and low redundant. Lastly, given a new aerial image, its sub-RCGs corresponding to the refined structures are extracted. They are further quantized into a discriminative vector for SVM classification. Thorough experimental results validate the effectiveness of the proposed method. In addition, the visualized mined subgraphs show that the discriminative topologies of each aerial image are discovered.

Deep brain stimulation is an important therapy for Parkinson's disease patients. However, the current deep brain stimulator is open loop and cannot automatically adapt the stimulation according to the patient's condition. In this reported study a real-time wake/sleep identification device has been developed to wirelessly control the stimulation according to the patient's wake/sleep states. The wake/sleep identification was based on the wrist movement, and the identified result was transmitted wirelessly to the implantable pulse generator. This device showed a reliable radio frequency communication within 2 m and a low level of current consumption. This device also showed a good performance of real-time wake/sleep identification on Parkinson's disease patients. This study provides a promising application in the closed-loop deep brain stimulation, as well as other applications in medical services, such as night care, and fall alarm.

A new robust method for image recognition based on iterative oblique projection is presented. By oblique projection, both the unstructured and structured noises can be suppressed. To improve recognition accuracy, an iterative process is adopted to reduce interference further. Experiments show that the proposed approach offers better performance than the conventional template matching method.