Abstract
Independent Component Analysis (ICA) can be used as a signal preprocessing tool to decompose electrode-array surface-electromyogram (s-EMG) signals into their constitutive motor-unit action potentials [García et al., IEEE EMB Mag., vol. 23(5) (2004)]. In the present study, we have established the effectiveness and the limitations of ICA for s-EMG decomposition using a set of synthetic signals. In addition, we have selected the best-suited algorithm to perform s-EMG decomposition by comparing the effectiveness of two of the most popular standard ICA algorithms. © Springer-Verlag 2004.
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CITATION STYLE
García, G. A., Maekawa, K., & Akazawa, K. (2004). Decomposition of synthetic multi-channel surface-electromyogram using independent component analysis. Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 3195, 985–992. https://doi.org/10.1007/978-3-540-30110-3_124
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