A software package for interactive motor unit potential classification using fuzzy k-NN classifier

Authors:
Sarbast Rasheed;Daniel Stashuk;Mohamed Kamel
Affiliations:
Department of Systems Design Engineering, University of Waterloo, Waterloo, Ontario N2L 3G1, Canada;Department of Systems Design Engineering, University of Waterloo, Waterloo, Ontario N2L 3G1, Canada;Department of Electrical and Computer Engineering, University of Waterloo, Waterloo, Ontario N2L 3G1, Canada
Venue:
Computer Methods and Programs in Biomedicine
Year:
2008

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Abstract

We present an interactive software package for implementing the supervised classification task during electromyographic (EMG) signal decomposition process using a fuzzy k-NN classifier and utilizing the MATLAB high-level programming language and its interactive environment. The method employs an assertion-based classification that takes into account a combination of motor unit potential (MUP) shapes and two modes of use of motor unit firing pattern information: the passive and the active modes. The developed package consists of several graphical user interfaces used to detect individual MUP waveforms from a raw EMG signal, extract relevant features, and classify the MUPs into motor unit potential trains (MUPTs) using assertion-based classifiers.