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Brain-Machine Interface (BMI) has emerged as a powerful tool for assisting disabled people and for augmenting human performance. Up so far, no studies have succeeded in the power augmentation for the multi-DOFs robot based on EEG signals, especially for the complex shoulder joint. In this work, we propose an electromyography (EMG) estimation method based on electroencephalography (EEG) signals to...
Brain-computer interface (BCI) systems can translate the human mind into control commands, which makes it feasible to improve the life quality of physically challenged people. However, in real-life situations, it is still difficult for users to utilize robots to provide basic services with BCI systems. We aimed to propose a BCI-based system with a visual servo module to operate a service robot. We...
Brain-Machine Interface (BMI), has been considered as an effective way to help and support the disabled's daily lives and rehabilitation to use their brain activity information instead of their bodies. As an extension, it is also expected to be used for healthy individuals. In our study, we try to estimate the necessary force/torque information for a subject from his/her EEG signals when using an...
Recently, a lot of BMIs (Brain-Machine Interfaces) using EEG (electroencephalogram) signals are developed to control external devices such as prostheses and robots. In this paper, in order to develop a new BMI for rehabilitation and/or power support, four different tasks corresponding to different brain excitation degrees are designed. Their EEG spectra are analyzed with short-time FFT, and their...
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