Reference-free reduction of ballistocardiogram artifact from EEG data using EMD-PCA

Javed, Ehtasham; Faye, Ibrahima; Malik, Aamir Saeed; Abdullah, Jafri Malin

doi:10.1109/icias.2014.6869512

Cited by 5 publications

(3 citation statements)

References 21 publications

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“…This EEG signal is not pure in form; rather it has different contaminations. These contaminations are subjected to certain artefact removal techniques to make it possible for further processing for various EEG applications [5][6][7].The estimation of the sources responsible for electromagnetic activity inside the brain based on the potential recorded through the electrodes is one of major applications of EEG. This problem is termed as EEG source localization or EEG inverse problem as the model is estimated with the available data set [8].…”

Section: Introductionmentioning

confidence: 99%

EEG based brain source localization comparison of sLORETA and eLORETA

Jatoi

Kamel

Malik

et al. 2014

Australas Phys Eng Sci Med

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114

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Human brain generates electromagnetic signals during certain activation inside the brain. The localization of the active sources which are responsible for such activation is termed as brain source localization. This process of source estimation with the help of EEG which is also known as EEG inverse problem is helpful to understand physiological, pathological, mental, functional abnormalities and cognitive behaviour of the brain. This understanding leads for the specification for diagnoses of various brain disorders such as epilepsy and tumour. Different approaches are devised to exactly localize the active sources with minimum localization error, less complexity and more validation which include minimum norm, low resolution brain electromagnetic tomography (LORETA), standardized LORETA, exact LORETA, Multiple Signal classifier, focal under determined system solution etc. This paper discusses and compares the ability of localizing the sources for two low resolution methods i.e., sLORETA and eLORETA respectively. The ERP data with visual stimulus is used for comparison at four different time instants for both methods (sLORETA and eLORETA) and then corresponding activation in terms of scalp map, slice view and cortex map is discussed.

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Section: Introductionmentioning

confidence: 99%

EEG based brain source localization comparison of sLORETA and eLORETA

Jatoi

Kamel

Malik

et al. 2014

Australas Phys Eng Sci Med

Self Cite

114

View full text Add to dashboard Cite

show abstract

“…The combination of EMD and PCA is more sensitive to temporal variation that occurs in BCG, compared to application of PCA or ICA alone ( 89 ). EMD-PCA has been tested for many different EEG-fMRI paradigms, and has shown better removal of BCG from ERP task EEG-fMRI compared with OBS and AAS ( 88 – 90 ). In resting state EEG-fMRI, EMD-PCA removal of BCG improved the detection of most parameters measured from the EEG and was shown to be a useful technique when a reference signal such as ECG is not available to estimate BCG onset ( 91 ).…”

Section: Artifact Reduction: Recommendations and Contemporary Usementioning

confidence: 99%

Artifact Reduction in Simultaneous EEG-fMRI: A Systematic Review of Methods and Contemporary Usage

2021

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Simultaneous electroencephalography-functional MRI (EEG-fMRI) is a technique that combines temporal (largely from EEG) and spatial (largely from fMRI) indicators of brain dynamics. It is useful for understanding neuronal activity during many different event types, including spontaneous epileptic discharges, the activity of sleep stages, and activity evoked by external stimuli and decision-making tasks. However, EEG recorded during fMRI is subject to imaging, pulse, environment and motion artifact, causing noise many times greater than the neuronal signals of interest. Therefore, artifact removal methods are essential to ensure that artifacts are accurately removed, and EEG of interest is retained. This paper presents a systematic review of methods for artifact reduction in simultaneous EEG-fMRI from literature published since 1998, and an additional systematic review of EEG-fMRI studies published since 2016. The aim of the first review is to distill the literature into clear guidelines for use of simultaneous EEG-fMRI artifact reduction methods, and the aim of the second review is to determine the prevalence of artifact reduction method use in contemporary studies. We find that there are many published artifact reduction techniques available, including hardware, model based, and data-driven methods, but there are few studies published that adequately compare these methods. In contrast, recent EEG-fMRI studies show overwhelming use of just one or two artifact reduction methods based on literature published 15–20 years ago, with newer methods rarely gaining use outside the group that developed them. Surprisingly, almost 15% of EEG-fMRI studies published since 2016 fail to adequately describe the methods of artifact reduction utilized. We recommend minimum standards for reporting artifact reduction techniques in simultaneous EEG-fMRI studies and suggest that more needs to be done to make new artifact reduction techniques more accessible for the researchers and clinicians using simultaneous EEG-fMRI.

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“…The proposed method provided a good accuracy and outperformed other conventional BCG processing methods. Javed et al in 2014 [ 154 ] and 2017 [ 155 ] used combination of PCA and EMD methods for BCG processing. This method was named PCA-EMD.…”

Section: Interference and Signal Pre-processingmentioning

confidence: 99%

Vital Sign Monitoring in Car Seats Based on Electrocardiography, Ballistocardiography and Seismocardiography: A Review

Šidiková

Martínek

Kawala-Sterniuk

et al. 2020

Sensors

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This paper focuses on a thorough summary of vital function measuring methods in vehicles. The focus of this paper is to summarize and compare already existing methods integrated into car seats with the implementation of inter alia capacitive electrocardiogram (cECG), mechanical motion analysis Ballistocardiography (BCG) and Seismocardiography (SCG). In addition, a comprehensive overview of other methods of vital sign monitoring, such as camera-based systems or steering wheel sensors, is also presented in this article. Furthermore, this work contains a very thorough background study on advanced signal processing methods and their potential application for the purpose of vital sign monitoring in cars, which is prone to various disturbances and artifacts occurrence that have to be eliminated.

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Reference-free reduction of ballistocardiogram artifact from EEG data using EMD-PCA

Cited by 5 publications

References 21 publications

EEG based brain source localization comparison of sLORETA and eLORETA

EEG based brain source localization comparison of sLORETA and eLORETA

Artifact Reduction in Simultaneous EEG-fMRI: A Systematic Review of Methods and Contemporary Usage

Vital Sign Monitoring in Car Seats Based on Electrocardiography, Ballistocardiography and Seismocardiography: A Review

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