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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...
In this paper, we design a human computer interaction (HCI) system for the locked-in syndrome (LIS) patients which combines the eye movement signals and Electroencephalogram (EEG) signals. The LIS describes patients who are faced with the quadriplegia, aphonia and facial paralysis problems. However, they are still conscious, have the ability to hear and give a hint with the blink or eye movements...
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...
Brain-Machine Interface (BMI), has been becoming gradually an effective way to help and support the disabled person by using his/her brain activity information. It is also expected to be used for both of the disabled and the healthy people. In this paper, aiming to estimate the force/torque information from brain activity to help and support human's daily life, we estimate the humans muscular activity...
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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