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- W4213303607 abstract "Bioinformation is information generated from biological movement. By using a variety of modern technologies, we can use this information to form a meaningful model for researchers to study. An electromyographic (EMG) signal is one type of bioinformation that is used in many areas to help people study human muscle movement. This information can help in both clinical areas and industrial areas. EMG is a very complicated signal, so processing it is vital. The processing of EMG signals is divided into collection, denoising, decomposition, feature extraction and classification steps. In this article, the wavelet denoising step and several decomposition processes are discussed to show the usage of this technique in the final classification step. At the end of the study, we find that after the wavelet denoising step, the classification accuracy, which uses the K-nearest neighbor of the independent component analysis features, improves, but the accuracy of the wavelet coefficient features and autoregression coefficient features decreases." @default.
- W4213303607 created "2022-02-24" @default.
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- W4213303607 date "2022-02-18" @default.
- W4213303607 modified "2023-09-26" @default.
- W4213303607 title "Discussion of the Influence of Multiscale PCA Denoising Methods with Three Different Features" @default.
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- W4213303607 doi "https://doi.org/10.3390/s22041604" @default.
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