Peripheral nerve disconnections cause severe muscle atrophy and consequently, paralysis of limbs. Reinnervation of denervated muscle by transplanting motor neurons and applying Functional Electrical Stimulation (FES) onto peripheral nerves is an important procedure for preventing irreversible degeneration of muscle tissues. After the reinnervation of denervated muscles, multiple peripheral nerves should be stimulated independently to control joint motion and reconstruct functional movements of limbs by the FES. In this study, a wirelessly powered two-channel neurostimulator was developed with the purpose of applying selective FES to two peripheral nerves—the peroneal nerve and the tibial nerve in a rat. The neurostimulator was designed in such a way that power could be supplied wirelessly, from a transmitter coil to a receiver coil. The receiver coil was connected, in turn, to the peroneal and tibial nerves in the rat. The receiver circuit had a low pass filter to allow detection of the frequency of the transmitter signal. The stimulation of the nerves was switched according to the frequency of the transmitter signal. Dorsal/plantar flexion of the rat ankle joint was selectively induced by the developed neurostimulator. The rat ankle joint angle was controlled by changing the stimulation electrode and the stimulation current, based on the Proportional Integral (PI) control method using a visual feedback control system. This study was aimed at controlling the leg motion by stimulating the peripheral nerves using the neurostimulator.
English skills are becoming necessary for students who would like to give a presentation at international conferences. However, it is very difficult for non-native English speakers to speak in English because of the differences between English and their native languages. There are some ways to practice speaking English such as Shadowing, and if the audio is similar to the learner's voices inside their heads, it should be more comfortable for the learners to listen to it and repeat after the audio. We propose a method to make English voices similar to the user's voice by using Interactive Differential Evolution. Experiments were conducted with the concrete system of IDE. 9 examinees participated in the experiments through 10 generations with 6 vectors in each generation and kept choosing the better option. After the experiment, we randomly chose 2 voices from the initial and final generation and asked the examinees to evaluate them. As a result, significantly higher evaluations were obtained in the voices from the final generation.
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