Next Article in Journal
A Cipher Based on Prefix Codes
Previous Article in Journal
Evaluating the Performance of Speaker Recognition Solutions in E-Commerce Applications
Article

Application of Empirical Mode Decomposition for Decoding Perception of Faces Using Magnetoencephalography

Institute of Cognitive Neuroscience, National Central University, Taoyuan City 320317, Taiwan
*
Author to whom correspondence should be addressed.
Academic Editors: Alexei Ossadtchi, Guido Nolte and Anton Vershovskii
Sensors 2021, 21(18), 6235; https://doi.org/10.3390/s21186235
Received: 29 June 2021 / Revised: 14 September 2021 / Accepted: 14 September 2021 / Published: 17 September 2021
(This article belongs to the Special Issue Brain Activity Exploration with Non-invasive Sensor Arrays)
Neural decoding is useful to explore the timing and source location in which the brain encodes information. Higher classification accuracy means that an analysis is more likely to succeed in extracting useful information from noises. In this paper, we present the application of a nonlinear, nonstationary signal decomposition technique—the empirical mode decomposition (EMD), on MEG data. We discuss the fundamental concepts and importance of nonlinear methods when it comes to analyzing brainwave signals and demonstrate the procedure on a set of open-source MEG facial recognition task dataset. The improved clarity of data allowed further decoding analysis to capture distinguishing features between conditions that were formerly over-looked in the existing literature, while raising interesting questions concerning hemispheric dominance to the encoding process of facial and identity information. View Full-Text
Keywords: magnetoencephalography (MEG); empirical mode decomposition (EMD); neural decoding; face perception magnetoencephalography (MEG); empirical mode decomposition (EMD); neural decoding; face perception
Show Figures

Figure 1

MDPI and ACS Style

Hsu, C.-H.; Wu, Y.-N. Application of Empirical Mode Decomposition for Decoding Perception of Faces Using Magnetoencephalography. Sensors 2021, 21, 6235. https://doi.org/10.3390/s21186235

AMA Style

Hsu C-H, Wu Y-N. Application of Empirical Mode Decomposition for Decoding Perception of Faces Using Magnetoencephalography. Sensors. 2021; 21(18):6235. https://doi.org/10.3390/s21186235

Chicago/Turabian Style

Hsu, Chun-Hsien, and Ya-Ning Wu. 2021. "Application of Empirical Mode Decomposition for Decoding Perception of Faces Using Magnetoencephalography" Sensors 21, no. 18: 6235. https://doi.org/10.3390/s21186235

Find Other Styles
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Article Access Map by Country/Region

1
Back to TopTop