Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Search research articles

Related Experiment Video

Updated: Jun 16, 2026

BrainBeats as an Open-Source EEGLAB Plugin to Jointly Analyze EEG and Cardiovascular Signals

BrainBeats as an Open-Source EEGLAB Plugin to Jointly Analyze EEG and Cardiovascular Signals

Published on: April 26, 2024

[Wavelet-based denoising algorithm for EEG signals--using scale dependent threshold based on median].

Aibin Jia¹, Min Wang, Fasheng Liu

¹College of Information and Electrical Engineering, Shandong University of Science and Technology, Qingdao 266510, China. jiaaibin2006@163.com

Sheng Wu Yi Xue Gong Cheng Xue Za Zhi = Journal of Biomedical Engineering = Shengwu Yixue Gongchengxue Zazhi

|January 26, 2010

Summary

Related Concept Videos

Downsampling

Downsampling

When considering a sampled sequence with zero values between sampling instants, one can replace it by taking every N-th value of the sequence. At these integer multiples of N, the original and sampled sequences coincide. This process, known as decimation, involves extracting every N-th sample from a sequence, thereby creating a more efficient sequence.
The Fourier transform of the decimated sequence reveals a combination of scaled and shifted versions of the original spectrum. This...

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by

Same author

Cordycepin alleviates aluminium chloride-induced neurodevelopmental toxicity in zebrafish embryos by modulating inflammation and Wnt signaling.

Neurochemistry international·2026

Same author

Ochratoxin C induces zebrafish embryonic neurodevelopmental defects and cerebral hemorrhaging by downregulating Notch signaling.

Journal of environmental sciences (China)·2026

Same author

1,6-Dihydroxynaphthalene as a potential environmental obesogen induces lipid accumulation and liver developmental defects in zebrafish.

Ecotoxicology and environmental safety·2026

Same author

Identification of Fentin chloride -induced scoliosis in zebrafish through the regulation of adrenaline by metabolomics and network pharmacology.

Aquatic toxicology (Amsterdam, Netherlands)·2025

Same author

Dicofol induces developmental cardiotoxicity in zebrafish embryos through oxidative stress mechanisms.

Ecotoxicology and environmental safety·2025

Same author

Butylated hydroxytoluene (BHT) induces zebrafish spinal cord defects and scoliosis by inhibiting the hedgehog pathway.

Scientific reports·2025

A new wavelet-based algorithm for electroencephalograph (EEG) signals uses a scale-dependent median threshold. This method enhances signal-to-noise ratio (SNR) and outperforms universal and Sure thresholds for noise reduction.

Area of Science:

Signal Processing
Biomedical Engineering
Neuroscience

Context:

Electroencephalography (EEG) signal analysis is crucial for understanding brain activity.
Traditional noise reduction methods for EEG signals have limitations.
Developing robust and efficient algorithms for EEG signal denoising is an ongoing challenge.

Purpose:

To introduce a novel wavelet-based algorithm for denoising electroencephalograph (EEG) signals.
To propose a scale-dependent thresholding method based on the median for improved noise reduction.
To compare the performance of the proposed thresholding method against universal and Sure thresholds.

Summary:

A wavelet-based algorithm employing a scale-dependent median threshold for EEG signal denoising is presented.

Related Experiment Videos

Last Updated: Jun 16, 2026

BrainBeats as an Open-Source EEGLAB Plugin to Jointly Analyze EEG and Cardiovascular Signals

BrainBeats as an Open-Source EEGLAB Plugin to Jointly Analyze EEG and Cardiovascular Signals

Published on: April 26, 2024

The proposed threshold is adaptive to subband noise, preserving noise-free reconstruction and reducing risk compared to universal thresholds.

This method overcomes limitations of the Sure threshold, offering computational simplicity and higher signal-to-noise ratio (SNR).

Impact:

The algorithm provides a computationally simple and effective solution for EEG signal denoising.
Achieves higher signal-to-noise ratio (SNR) compared to existing universal and Sure thresholding techniques.
Enhances the quality of EEG data, potentially improving the accuracy of neurological diagnoses and research.