Non-negative matrix factorization for single-channel EEG artifact rejection

Damon, Cécilia; Liutkus, Antoine; Gramfort, Alexandre; Essid, Slim

doi:10.1109/icassp.2013.6637836

Cited by 27 publications

(24 citation statements)

References 20 publications

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“…Damon et al proposed an eye-blink artifact reduction method based on nonnegative matrix factorization (NMF) for a single-channel EEG device [9]. They reported that NMF can effectively decompose recorded EEG signals into brain activity components and eye-blink artifacts.…”

Section: Introductionmentioning

confidence: 99%

Eye-Blink Artifact Reduction Using 2-Step Nonnegative Matrix Factorization for Single-Channel Electroencephalographic Signals

Kanoga

Mitsukura

2014

Journal of Signal Processing

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Artifact reduction from electroencephalographic (EEG) signals is an important process in the numerical analysis of brain activities. In general, independent component analysis (ICA) is employed for artifact reduction from multichannel EEG devices. On the other hand, single-channel EEG devices have recently become attractive because of their usability for measurement and their portability. However, it is ill-defined problem to design a numerical approach for eye-blink artifact reduction from single-channel EEG signals. In this paper, we therefore propose a new artifact reduction method based on 2-step nonnegative matrix factorization (NMF) for single-channel EEG signals. In an experiment, we conducted 2-step NMF to reject eye-blink artifacts using single-channel EEG signals recorded at Fp1. We also applied ICA to multichannel EEG signals and compared the results with those obtained by the proposed method. The experimental results show a relatively high signal-to-noise ratio (SNR) between the signals reconstructed using the proposed method and those obtained by ICA. Moreover, we confirm the coefficient of correlation of over 99% for estimating the recorded EEG signals by the proposed method.

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Section: Introductionmentioning

confidence: 99%

Eye-Blink Artifact Reduction Using 2-Step Nonnegative Matrix Factorization for Single-Channel Electroencephalographic Signals

Kanoga

Mitsukura

2014

Journal of Signal Processing

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“…For example, the automatic transcription [13], the sound emphasis or separation [14], and the band spreading [15]. Recently, a research of artifactitious rejection using single-channel EEG recordings is also reported [7]. However, this research has the following problem.…”

Section: B Preparing Datasets For Proposed Methodsmentioning

confidence: 98%

“…A blink artifact removal method using single-channel EEG recordings and non-negative matrix factorization (NMF) had been reported [7]. The NMF was showed the effectivity for blink artifact rejection.…”

Section: Introductionmentioning

confidence: 98%

Proposed blink artifacts rejection method mixing with electroencephalographic recordings using single-channel electroencephalographic recordings and non-negative matrix factorization

Kanoga

Mitsukura

2014

2014 IEEE 13th International Workshop on Advanced Motion Control (AMC)

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Recently, a lot of research concerning biological signal analysis has been proceeded in various field. Especially, research about electroencephalographic (EEG) signals has attracted attention since the signal contains a mixture of endogenous brain activities. However, the EEG signal is often mixed physiological artifacts such as blink, oculogyration, heart beat or muscle activities. Therefore, it is important to remove these artifacts from the EEG recordings when researchers attempt to analyze brain activities accurately. An independent component analysis (ICA) has been used for removing blink artifacts with over 90 percentage of the repeatability for original signals. However, a common major drawback to the ICA is that this method can only manage overdetermined mixtures, which entails using some EEG electrodes. There is no rejective method for single-channel EEG signals. Therefore, in this paper, we proposed an artifactitious rejection method using single-channel EEG recordings and 2 step non-negative matrix factorization (NMF). We acquired the multi-channel EEG recordings from 3 subjects who blink every 5 seconds according to metronomic sound. Furthermore, we applied the NMF using single-channel EEG (Fp1) recordings to reject blink artifacts, and the ICA using multi-channel EEG recordings to obtain clean Fp1 signals. High SNR between reconstructed signals by the proposed method and the ICA was showed. Moreover, over 99 percentage of the repeatability for original EEG signals was indicated by the proposed method.

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“…Some works reported that the supervised NMF could effectively factorize the observed EEG signals into the brain activity components and the artifacts if the user has artifact data in advance [62,63]. Before applying supervised learning, template matrix X Art has been factorized into H Art and W Art .ThematrixX is continuously factorized into H and W where H contains the elements of matrix H Art .…”

Section: Nonnegative Matrix Factorizationmentioning

confidence: 99%

Review of Artifact Rejection Methods for Electroencephalographic Systems

Kanoga¹,

Mitsukura²

2017

Electroencephalography

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Technologies using electroencephalographic (EEG) signals have been penetrated into public by the development of EEG systems. During EEG system operation, recordings ought to be obtained under no restriction of movement for routine use in the real world. However, the lack of consideration of situational behavior constraints will cause technical/biological artifacts that often mixed with EEG signals and make the signal processing difficult in all respects by ingeniously disguising themselves as EEG components. EEG systems integrating gold standard or specialized device in their processing strategies would appear as daily tools in the future if they are unperturbed to such obstructions. In this chapter, we describe algorithms for artifact rejection in multi-/single-channel. In particular, some existing single-channel artifact rejection methods that will exhibit beneficial information to improve their performance in online EEG systems were summarized by focusing on the advantages and disadvantages of algorithms.

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Non-negative matrix factorization for single-channel EEG artifact rejection

Cited by 27 publications

References 20 publications

Eye-Blink Artifact Reduction Using 2-Step Nonnegative Matrix Factorization for Single-Channel Electroencephalographic Signals

Eye-Blink Artifact Reduction Using 2-Step Nonnegative Matrix Factorization for Single-Channel Electroencephalographic Signals

Proposed blink artifacts rejection method mixing with electroencephalographic recordings using single-channel electroencephalographic recordings and non-negative matrix factorization

Review of Artifact Rejection Methods for Electroencephalographic Systems

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