TITLE:
Feasibility Assay for Measure of Sternocleidomastoid and Platysma Electromyography Signal for Brain-Computer Interface Feedback
AUTHORS:
Juliet Sánchez Galego, Omar Valle Casas, Alexandre Balbinot
KEYWORDS:
Electromyography, Feature Extraction, Uncertainty, Statistical Analysis, Factors Interactions
JOURNAL NAME:
Intelligent Control and Automation,
Vol.5 No.4,
November
13,
2014
ABSTRACT: A feasibility assay is conducted for electromyography measure in sternocleidomastoid and platysma, tenting to use it on Brain-Computer Interface (BCI) feedback. It is proposed a case of study for four healthy subjects with an average of 35 years old, two females and two males. Methodology proposed includes signal acquisition and processing with feature extraction of RMS, Mean and Variance. The data are acquired with the AD board NI USB-6009, interfaced with LabView and processed in MatLab. An uncertainty analysis was made obtaining a system uncertainty of ±2.31 mV. ANOVA analysis was done, with a Randomized Complete Block Design (RCBD) experiment and interaction of factors and residues obtained with the software Minitab.