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

Related Concept Videos

Reconstruction of Signal using Interpolation

Reconstruction of Signal using Interpolation

Signal processing techniques are essential for accurately converting continuous signals to digital formats and vice versa. When a continuous signal is sampled with a period T, the resulting sampled signal exhibits replicas of the original spectrum in the frequency domain, spaced at intervals equal to the sampling frequency. To handle this sampled signal, a zero-order hold method can be applied, which creates a piecewise constant signal by retaining each sample's value until the next...

You might also read

Related Articles

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

Sort by

Same author

JA-CmMYC2 and SA-CmWRKY40 signaling networks relieve the inhibition of CmTLP15/22 on the cold tolerance of melon seedlings.

The Plant journal : for cell and molecular biology·2026

Same author

A dual track predictive model for assessing crow's feet aging across different clinical severity grades.

Scientific reports·2026

Same author

Respiratory Variability in Disorders of Consciousness: Relationship and Clinical Applications.

CNS neuroscience & therapeutics·2026

Same author

Identification of novel CRESS-DNA viruses in the human vaginal microbiome.

Frontiers in microbiology·2026

Same author

Illustrations of Handbook of the Birds of the World: Datasets of RGB values and color classification of birds.

Ecology·2026

Same author

Diagnostic value of somatosensory evoked potentials for paroxysmal sympathetic hyperactivity: a retrospective cohort study.

Frontiers in neurology·2026

Search research articles

Related Experiment Video

Updated: Jul 13, 2025

A Multimodal Imaging- and Stimulation-based Method of Evaluating Connectivity-related Brain Excitability in Patients with Epilepsy

A Multimodal Imaging- and Stimulation-based Method of Evaluating Connectivity-related Brain Excitability in Patients with Epilepsy

Published on: November 13, 2016

A three-dimensional adaptive rational interpolation algorithm for removing TMS-EEG pulse artifacts.

Hui Xiong^1,2, Yajun Di^1,2, Jinzhen Liu^1,2

¹The School of Control Science and Engineering, Tiangong University, Tianjin 300387, People's Republic of China.

Physiological Measurement

|October 18, 2023

Summary

A new 3D adaptive algorithm effectively removes pulse artifacts in Transcranial Magnetic Stimulation combined with Electroencephalography (TMS-EEG) recordings. This method significantly improves signal quality and reduces processing time for brain research.

Keywords:

adaptive algorithm electroencephalogram pulse artifact rational hermite interpolation transcranial magnetic stimulation

More Related Videos

Extracting Visual Evoked Potentials from EEG Data Recorded During fMRI-guided Transcranial Magnetic Stimulation

Extracting Visual Evoked Potentials from EEG Data Recorded During fMRI-guided Transcranial Magnetic Stimulation

Published on: May 12, 2014

Equipment Setup and Artifact Removal for Simultaneous Electroencephalogram and Functional Magnetic Resonance Imaging for Clinical Review in Epilepsy

Equipment Setup and Artifact Removal for Simultaneous Electroencephalogram and Functional Magnetic Resonance Imaging for Clinical Review in Epilepsy

Published on: June 23, 2023

Related Experiment Videos

Last Updated: Jul 13, 2025

A Multimodal Imaging- and Stimulation-based Method of Evaluating Connectivity-related Brain Excitability in Patients with Epilepsy

A Multimodal Imaging- and Stimulation-based Method of Evaluating Connectivity-related Brain Excitability in Patients with Epilepsy

Published on: November 13, 2016

Extracting Visual Evoked Potentials from EEG Data Recorded During fMRI-guided Transcranial Magnetic Stimulation

Extracting Visual Evoked Potentials from EEG Data Recorded During fMRI-guided Transcranial Magnetic Stimulation

Published on: May 12, 2014

Equipment Setup and Artifact Removal for Simultaneous Electroencephalogram and Functional Magnetic Resonance Imaging for Clinical Review in Epilepsy

Equipment Setup and Artifact Removal for Simultaneous Electroencephalogram and Functional Magnetic Resonance Imaging for Clinical Review in Epilepsy

Published on: June 23, 2023

Area of Science:

Neuroscience
Biomedical Engineering
Signal Processing

Background:

Transcranial Magnetic Stimulation combined with Electroencephalography (TMS-EEG) is crucial for studying brain region reactivity and connectivity.
Pulse artifacts generated by TMS electromagnetic pulses significantly contaminate EEG signals, hindering accurate analysis.
Efficient and rapid artifact removal is essential for advancing TMS-EEG applications.

Purpose of the Study:

To develop and validate a novel algorithm for the efficient and fast removal of pulse artifacts in TMS-EEG.
To address the limitations of existing artifact removal techniques in terms of speed and effectiveness.

Main Methods:

A three-dimensional adaptive rational quadratic Hermite interpolation algorithm is proposed.
Signal recombination creates a 3D signal matrix, with artifact windows identified using a derivative threshold.
The identified windows are interpolated using the adaptive rational quartic Hermite interpolation algorithm.

Main Results:

The proposed algorithm demonstrated significant improvements in Signal-to-Noise Ratio (SNR), ranging from 23.88% to 47.60%.
Root Mean Square Error (RMSE) was reduced by 46.52% to 81.11%, and Mean Absolute Error (MAE) by 47.83% to 58.33%.
Time consumption was reduced by 45.90% compared to piecewise cubic Hermite interpolation, indicating enhanced efficiency.

Conclusions:

The proposed 3D adaptive algorithm effectively and rapidly removes TMS-EEG pulse artifacts.
This method offers superior performance in artifact reduction and processing speed compared to traditional methods.
The algorithm facilitates more reliable and efficient analysis of brain activity using TMS-EEG.