A software package for interactive motor unit potential classification using fuzzy k-NN classifier.
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.
Rasheed
Sarbast
S
Department of Systems Design Engineering, University of Waterloo, Waterloo, Ontario N2L 3G1, Canada. s.rasheed@ieee.org
Stashuk
Daniel
D
Kamel
Mohamed
M
D004576:Electromyography / Q000706:statistics & numerical data*; D004594:Electrophysiology; D017143:Fuzzy Logic; D006801:Humans; D009046:Motor Neurons / Q000145:classification / Q000502:physiology*; D009119:Muscle Contraction / Q000502:physiology; D012815:Signal Processing, Computer-Assisted; D012984:Software; D012985:Software Design