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Human-machine interaction (HMI) relies on pattern recognition algorithms that are not perfect. To improve the performance and usability of these systems we can utilize the neural mechanisms in the human brain dealing with error awareness. This study aims at designing a practical error detection algorithm using electroencephalogram signals that can be integrated in an HMI system. Thus, real-time operation,...
The concept of brain-computer interface (BCI) has emerged over the last three decades as a promising alternative to the existing interface methods. However the BCI framework generally spoken only emphasizes on the aspects of BCI signal processing, lacking of the function of visualization and virtual reality (VR) feedback. This paper designs a general and extendable framework which has the ability...
Stroke is the leading cause of adult disability, and training in voluntary movement has been shown to be effective in rebuilding motor skills. We propose an EEG-FES system that can assist in the reconstruction of a closed-loop between motor commands and sensory feedbacks in stroke patients. The system uses event-related desynchronization (ERD) to reflect motor intentions. We did two pilot studies...
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