Artifacts Reduction Method in EEG Signals with Wavelet Transform and Adaptive Filter

Aiming at the large calculation workload of adaptive algorithm in adaptive filter based on wavelet transform, affecting the filtering speed, a wavelet-based neural network adaptive filter is constructed in this paper. Since the neural network has the ability of distributed storage and fast self-evolution, use Hopfield neural network to implement adaptive filter LMS algorithm in this filter so as to improve the speed of operation. The simulation results prove that, the new filter can achieve rapid real-time denoising.

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EEG Signals Denoising Using Optimal Wavelet Transform Hybridized With Efficient Metaheuristic Methods

IEEE Access ◽

10.1109/access.2019.2962658 ◽

2020 ◽

Vol 8 ◽

pp. 10584-10605 ◽

Cited By ~ 16

Author(s):

Zaid Abdi Alkareem Alyasseri ◽

Ahamad Tajudin Khader ◽

Mohammed Azmi Al-Betar ◽

Ammar Kamal Abasi ◽

Sharif Naser Makhadmeh

Keyword(s):

Wavelet Transform ◽

Eeg Signals ◽

Metaheuristic Methods

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Cross-wavelet transform as a new prototype for classification of EEG signals

Computer Methods in Biomechanics and Biomedical Engineering Imaging & Visualization ◽

10.1080/21681163.2018.1523749 ◽

2018 ◽

Vol 7 (3) ◽

pp. 348-358 ◽

Cited By ~ 2

Author(s):

Priyadarshiny Dhar ◽

Saibal Dutta ◽

V. Mukherjee ◽

Abhijit Dhar ◽

Prithwiraj Das

Keyword(s):

Wavelet Transform ◽

Eeg Signals ◽

Cross Wavelet Transform ◽

Cross Wavelet

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EOG Artifacts Reduction from EEG Based on Deep Network and Recursive Least Squares Adaptive Filter

Theory, Methodology, Tools and Applications for Modeling and Simulation of Complex Systems - Communications in Computer and Information Science ◽

10.1007/978-981-10-2669-0_44 ◽

2016 ◽

pp. 412-421

Author(s):

Banghua Yang ◽

Kaiwen Duan ◽

Tao Zhang ◽

Yonghuai Zhang

Keyword(s):

Least Squares ◽

Adaptive Filter ◽

Recursive Least Squares ◽

Deep Network ◽

Artifacts Reduction

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An Effective Method to Denoiseeeg, ECG and PPG Signals based on Meyer Wavelet Transform

International Journal of Engineering & Technology ◽

10.14419/ijet.v7i3.34.19415 ◽

2018 ◽

Vol 7 (3.34) ◽

pp. 678

Author(s):

P Thamarai ◽

Dr K.Adalarasu

Keyword(s):

Wavelet Transform ◽

Adaptive Filter ◽

Wavelet Decomposition ◽

Motion Artifact ◽

Signal Quality ◽

Frequency Noise ◽

Meyer Wavelet ◽

Discrete Transform ◽

Reference Input

In this analysis, the prevailing role of the wavelet transform in the interrogation of the ECG is discussed in detail, where both the constant and the discrete transform are considered in turn.A Wavelet denoising is functional on the original signal to eradicate high frequency noise, and then a process based on Meyer wavelet transform combined with adaptive filter is functional to eradicate the motion artifact. This approach uses Meyer Wavelet decomposition to extract the motion artifact, which is subsequently utilized as the reference input of an adaptive filter for noise cancellation. The technique diminishes the overhead of the circuit because it does not need a separate collection of reference input signal which link to noise. Testing results illustrate that this approach can efficiently remove motion artifact and make better the signal quality.

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