Kazuo, K. and Yoshiaki, H. (2011) Motion Estimation Based on EMG and EEG Signals to Control Wearable Robots. Proceedings of the 2013 IEEE International Conference on Systems, Man, and Cybernetics, Japan, 4213-4218.

has been cited by the following article:

• 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.