A Hybrid Method to Improve the Reduction of Ballistocardiogram Artifact from EEG Data

Javed, Ehtasham and Faye, Ibrahima and Malik, Aamir Saeed and Abdullah, and Jafri Malin (2014) A Hybrid Method to Improve the Reduction of Ballistocardiogram Artifact from EEG Data. In: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Springer Verlag.



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 referencefree 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.

Item Type:Book Section
Subjects:Q Science > Q Science (General)
T Technology > T Technology (General)
Academic Subject One:Biomedical Imaging
Departments / MOR / COE:Centre of Excellence > Center for Intelligent Signal and Imaging Research
Departments > Electrical & Electronic Engineering
Research Institutes > Institute for Health Analytics
ID Code:11384
Deposited By: Dr Aamir Saeed Malik
Deposited On:28 Apr 2015 02:54
Last Modified:28 Apr 2015 02:54

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