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• W2916609993 startingPage "259" @default.
• W2916609993 abstract "The number and position of sEMG electrodes have been studied extensively due to the need to improve the accuracy of the classification they carry out of the intention of movement. Nevertheless, increasing the number of channels used for this classification often increases their processing time as well. This research work contributes with a comparison of the classification accuracy based on the different number of sEMG signal channels (one to four) placed in the right lower limb of healthy subjects. The analysis is performed using Mean Absolute Values, Zero Crossings, Waveform Length, and Slope Sign Changes; these characteristics comprise the feature vector. The algorithm used for the classification is the Support Vector Machine after applying a Principal Component Analysis to the features. The results show that it is possible to reach more than 90% of classification accuracy by using 4 or 3 channels. Moreover, the difference obtained with 500 and 1000 samples, with 2, 3 and 4 channels, is not higher than 5%, which means that increasing the number of channels does not guarantee 100% precision in the classification." @default.
• W2916609993 created "2019-03-02" @default.
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• W2916609993 date "2019-02-27" @default.
• W2916609993 modified "2023-10-15" @default.
• W2916609993 title "A Study of Movement Classification of the Lower Limb Based on up to 4-EMG Channels" @default.
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• W2916609993 doi "https://doi.org/10.3390/electronics8030259" @default.
• W2916609993 hasPublicationYear "2019" @default.
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