Title
A Hybrid Method to Improve the Reduction of Ballistocardiogram Artifact from EEG Data.
Abstract
Simultaneous recordings of functional magnetic resonance imaging (fMRI) and electroencephalography (EEG) allow acquisition of brain data with high spatial and temporal resolution. However, the EEG data get contaminated by additional artifacts such as Gradient artifact and Ballistocardiogram (BCG) artifact. The BCG artifact's dynamics appear to be more challenging and it hinders in the assessment of the neuronal activities. In this paper, a reference-free method is implemented in which Empirical Mode Decomposition (EMD) and Principal Component Analysis (PCA) has been combined to reduce the BCG artifact while preserving the neuronal activities. The qualitative analysis of the proposed method along with three existing methods demonstrates that the proposed method has improved the quality of the reconstructed data. Moreover, it does not require any reference signal to extract BCG artifact.
Year
DOI
Venue
2014
10.1007/978-3-319-12640-1_23
Lecture Notes in Computer Science
Keywords
Field
DocType
Ballistocardiogram artifact,Simultaneous EEG & fMRI,Principal Component Analysis,Empirical Mode Decomposition
Computer vision,Pattern recognition,Functional magnetic resonance imaging,Computer science,Artificial intelligence,Eeg data,Temporal resolution,Principal component analysis,Electroencephalography,Hilbert–Huang transform
Conference
Volume
ISSN
Citations 
8835
0302-9743
1
PageRank 
References 
Authors
0.37
9
4
Name
Order
Citations
PageRank
Ehtasham Javed111.05
ibrahima faye217919.82
aamir saeed malik337353.61
Jafri Malin Abdullah431.09