On the use of High-Order Cumulant and Bispectrum for Muscular-Activity Detection

EUGENIO OROSCO; PABLO DIEZ; ERIC LACIAR; VICENTE MUT; CARLOS SORIA; FERNANDO DI SCIASCIO

BIOMEDICAL SIGNAL PROCESSING AND CONTROL

ELSEVIER SCI LTD

Lugar: Amsterdam; Año: 2015 vol. 18 p. 325 - 333

1746-8094

The electromyographic (EMG) signals are extensively used on feature extraction methods for movement classification purposes. High-Order Statistics (HOS) is being employed increasingly in myoelectric research. HOS techniques could be represented in the frequency domain (high-order spectra, e.g., bispectrum, trispectrum) or in the time domain (higher-order cumulants). More calculus is required for computing the HOS in the frequency domain. On the one hand, classical bispectrum-based features were applied to EMG signals. We propose novel third-order cumulant-based features for EMG signals. Three different classifiers are implemented for muscular-activity detection. Different analysis and evaluations were applied to both HOS-based features in order to qualify and quantify similarities. Based on these results, it is possible to conclude that cumulant-based features and bispectrum-based features had comparable behavior and allowed similar classification rates. Hence, extra calculus in order to convert time- to frequency-domain should be avoided.