Title :
Statistical approach for angular position separability classes of EMG data
Author :
De Castro, Maria Claudia Ferrari
Author_Institution :
Dept. of Electr. Eng., Centro Univ. da FEI, São Bernardo do Campo, Brazil
Abstract :
This paper focus on the application of a multivariate statistical analysis approach, based on Linear Discriminant Analysis (LDA), of EMG data that aims to identify the angular position of the elbow. Linear transformations applied to EMG signals of the Biceps brachii and Triceps brachii, acquired during flexion / extension movements, enabled good and reliable class separation for future classification.
Keywords :
biomechanics; electromyography; Biceps brachii; EMG data; Linear Discriminant Analysis; Triceps brachii; angular position separability class; elbow; flexion-extension movement; statistical approach; Covariance matrix; Eigenvalues and eigenfunctions; Electromyography; Feature extraction; Linear discriminant analysis; Muscles; Principal component analysis; Arm Angular Position; Biceps brachii; Electromiogram; Linear Discriminant Analysis (LDA); Pattern Recognition; Triceps brachii;
Conference_Titel :
Biosignals and Biorobotics Conference (BRC), 2011 ISSNIP
Conference_Location :
Vitoria
Print_ISBN :
978-1-4244-8212-2
DOI :
10.1109/BRC.2011.5740663
