Open AccessOptimized Algorithm for Muscular Diseases Recognition Based On Temporal Parameters Analysis and Correlation Coefficients
Author(s) -
Efraín A. Mejía-González,
Josué Aarón López-Leyva,
Jessica Estrada-Lechuga,
Miguel A. Ponce-Camacho
Publication year - 2019
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1304/1/012020
Subject(s) - correlation , correlation coefficient , pattern recognition (psychology) , algorithm , computer science , artificial intelligence , speech recognition , mathematics , machine learning , geometry
In this paper, an optimized algorithm based on temporal parameters analysis and correlation coefficients is presented in order to perform muscular diseases recognition. Statistical information was measured of three classes signals (Healthy, Myopathy and Neuropathy conditions). The temporal parameters that were initially proposed (14) were optimized based on the correlation coefficients. Thus, only 9 parameters were selected for optimized the algorithm, and the time required for training and recognition is ≈ 0.2s and ≈ 4ms, respectively.