Hongbo Xie

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The mean frequency (MNF) of surface electromyography (EMG) signal is an important index of local muscle fatigue. The purpose of this study is to improve the mean frequency (MNF) estimation. Three methods to estimate the MNF of non-stationary EMG are compared. A novel approach based on Hilbert-Huang transform (HHT), which comprises the empirical mode(More)
This paper presents an effective mutual information-based feature selection approach for EMG-based motion classification task. The wavelet packet transform (WPT) is exploited to decompose the four-class motion EMG signals to the successive and non-overlapped sub-bands. The energy characteristic of each sub-band is adopted to construct the initial full(More)
Predictive data mining typically relies on labeled data without exploiting a much larger amount of available unlabeled data. The goal of this paper is to show that using unlabeled data can be beneficial in a range of important prediction problems and therefore should be an integral part of the learning process. Given an unlabeled dataset representative of(More)
A labeled sequence data set related to a certain biological property is often biased and, therefore, does not completely capture its diversity in nature. To reduce this sampling bias problem a data mining procedure is proposed for detecting underrepresented relevant sequences. The procedure is aimed at helping domain experts achieve a cost-effective(More)
This paper presents an effective classification scheme consisting of the rough set theory (RST)-based feature selection and the fuzzy least squares support vector machine (LS-SVM) classifier for the surface electromyographic (sEMG)-based motion classification. The wavelet packet transform (WPT) is exploited to decompose the four-class motion EMG signals to(More)
Gene expression profiles have been widely used in functional genomic studies. However, not much work in traditional gene expression profiling takes into account the location information of a gene's expressions in the brain. Gene expression maps, which contain spatial information regarding the expression of genes in mice's brain, are obtained by combining(More)
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