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Electromyography (EMG) has been popularly used as interface command to achieve a natural control for myoelectric prosthetic-hands. Traditional EMG-based recognition methods always only focus on the classification of target motion classes that were defined in the training phase, but have no ability to reject outlier motion interferences that did not present before. In this paper, a hybrid classifier...
Missing data are a common drawback that pattern recognition techniques need to handle when solving real-life classification tasks. This paper first discusses problems in handling high-dimensional samples with missing values by the Gaussian mixture model (GMM). Since fitting the GMM by directly using high-dimensional samples as inputs is difficult due to the convergence and stability issues, a novel...
Brain-computer interface (BCI) is currently developed as an alternative technology with a potential to restore lost motor function in patients with neurological injuries. In this paper, we describe an integrated system of a non-invasive electroencephalogram (EEG)-based BCI with a non-invasive functional electrical stimulation (FES). This system enables the direct brain control of upper limbs to achieve...
One of the existing problems of General UKF is the stability problem due to the strong nonlinearity and the complexity of the system. When the algorithm can't ensure the state covariance to be positive semidefinite, the precision will be decreased or even general UKF will be halted. Based on the singular value decomposition of state covariance, this paper proposes a modified UKF algorithm which can...
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