Wenguang Jin

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Gesture recognition in non-intrusive muscle-computer interfaces is usually based on windowed descriptive and discriminatory surface electromyography (sEMG) features because the recorded amplitude of a myoelectric signal may rapidly fluctuate between voltages above and below zero. Here, we present that the patterns inside the instantaneous values of(More)
AVS-M is the recent mobile video coding standard of China. Currently, ARM cores are widely used in mobile applications because of their low power consumption. In this paper, a scheme of the AVS-M decoder realtime implementation on 32 bit MCU RISC processor ARM920T (S3C2440) is presented. The algorithm, redundancy, structure and memory optimization methods(More)
According to the topological feature of the power-line network, an improved On Demand Distance Vector (IPODV) routing is proposed to ensure an efficient data transmission. It is based on Ad hoc On-Demand Distance Vector (AODV) Routing which is a powerful routing protocol used in ad-hoc networks to deal with the fast changing logical topology. IPODV improves(More)
High-density surface electromyography (HD-sEMG) is to record muscles' electrical activity from a restricted area of the skin by using two dimensional arrays of closely spaced electrodes. This technique allows the analysis and modelling of sEMG signals in both the temporal and spatial domains, leading to new possibilities for studying next-generation(More)
Conventionally, gesture recognition based on nonintrusive muscle-computer interfaces required a strongly-supervised learning algorithm and a large amount of labeled training signals of surface electromyography (sEMG). In this work, we show that temporal relationship of sEMG signals and data glove provides implicit supervisory signal for learning the gesture(More)
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