Search research articles

Related Concept Videos

You might also read

Related Articles

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

Sort by

Same author

Human vagus nerve fascicular anatomy and its implications for targeted cardiac stimulation: a microCT segmentation and histological pilot anatomical study.

Frontiers in neuroscience·2026

Same author

Enhancing the functionality of soft continuum robots for minimally invasive and endoluminal interventions: a review.

Progress in biomedical engineering (Bristol, England)·2026

Same author

Beyond CT: Attenuation correction for stand-alone brain PET.

Zeitschrift fur medizinische Physik·2026

Same author

Non-invasive fluorescence sensing reveals changes in intestinal barrier function and gastric emptying rate in a first-in-human study of Crohn's disease.

Therapeutic advances in gastroenterology·2025

Same author

A Soft Inflatable Cable-Driven Parallel Robot With a Variable Stiffness End-Effector for Advanced Interventional Endoscopy.

IEEE transactions on bio-medical engineering·2025

Same author

Optimisation of magnetic field sensing with optically pumped magnetometers for magnetic detection electrical impedance tomography.

Physics in medicine and biology·2025

Same journal

Dissecting the integrated information of cardiovascular and cardiorespiratory systems at rest and during physiological stress.

Physiological measurement·2026

Same journal

Respiratory event type and duration modulate PPG waveforms in OSA.

Physiological measurement·2026

Same journal

Estimating changes in systolic blood pressure based on pulse wave morphology using paired segment comparison.

Physiological measurement·2026

Same journal

Small changes in hand height alter absorbance, but not pulsation, in the finger pulse plethysmograph.

Physiological measurement·2026

Same journal

A Comprehensive Inference-Time Augmentation Framework in Physiological Signals: Application to PPG-Based AF Detection.

Physiological measurement·2026

Same journal

Quantification of pendelluft in electrical impedance tomography data: opening Pandora's box? A literature review of analytical methods.

Physiological measurement·2026

See all related 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: Mar 31, 2026

Personalized 3D-printed Headgear for Multi-electrode Transcranial Electrical Stimulation

Personalized 3D-printed Headgear for Multi-electrode Transcranial Electrical Stimulation

Published on: September 9, 2025

Correcting electrode modelling errors in EIT on realistic 3D head models.

Markus Jehl¹, James Avery, Emma Malone

¹University College London, London WC1E 6BT, UK.

Physiological Measurement

|October 27, 2015

Summary

This summary is machine-generated.

Electrical impedance tomography (EIT) can help distinguish stroke types. Reconstructing electrode positions alongside conductivity in head EIT significantly improves image quality by reducing artefacts caused by electrode movement.

More Related Videos

Computational Modeling of Retinal Neurons for Visual Prosthesis Research - Fundamental Approaches

Computational Modeling of Retinal Neurons for Visual Prosthesis Research - Fundamental Approaches

Published on: June 21, 2022

Bioelectric Analyses of an Osseointegrated Intelligent Implant Design System for Amputees

Bioelectric Analyses of an Osseointegrated Intelligent Implant Design System for Amputees

Published on: July 15, 2009

Related Experiment Videos

Last Updated: Mar 31, 2026

Personalized 3D-printed Headgear for Multi-electrode Transcranial Electrical Stimulation

Personalized 3D-printed Headgear for Multi-electrode Transcranial Electrical Stimulation

Published on: September 9, 2025

Computational Modeling of Retinal Neurons for Visual Prosthesis Research - Fundamental Approaches

Computational Modeling of Retinal Neurons for Visual Prosthesis Research - Fundamental Approaches

Published on: June 21, 2022

Bioelectric Analyses of an Osseointegrated Intelligent Implant Design System for Amputees

Bioelectric Analyses of an Osseointegrated Intelligent Implant Design System for Amputees

Published on: July 15, 2009

Area of Science:

Medical Imaging
Biomedical Engineering
Computational Electromagnetics

Background:

Electrical impedance tomography (EIT) shows promise for pre-hospital stroke diagnosis.
Image reconstruction in EIT is challenged by ill-posed problems, leading to artefacts from measurement and modeling errors.
Inaccurate electrode positioning is a major source of artefacts in head EIT.

Purpose of the Study:

To investigate the use of the Fréchet derivative for simultaneous reconstruction of electrode positions and conductivity changes in head EIT.
To improve the stability and accuracy of EIT image reconstruction algorithms against electrode movement artefacts.

Main Methods:

Development of a fast implementation using the Fréchet derivative on electrode boundaries within a 3D head model.
Simultaneous reconstruction of electrode positions and conductivity variations.
Analysis of performance using simulated and experimental voltage data for both time-difference and absolute imaging.

Main Results:

Simultaneous reconstruction of electrode positions and conductivity significantly enhances image quality in the presence of electrode movement.
The Fréchet derivative approach effectively addresses artefacts caused by electrode displacement.
Demonstrated feasibility in both simulated and experimental settings.

Conclusions:

Simultaneous EIT reconstruction of electrode positions and conductivity is a viable strategy to improve image quality and stability.
This method offers a significant advancement for accurate stroke differentiation using EIT, particularly in mobile environments.
Addresses a key challenge in head EIT, paving the way for more reliable clinical applications.