Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Bode Plots Construction01:24

Bode Plots Construction

734
The Bode plot is an essential tool in control system analysis, mapping the frequency response of a system through a magnitude plot and a phase plot, both against a logarithmic frequency axis. To construct a Bode plot, consider the transfer function H(ω):
734

You might also read

Related Articles

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

Sort by
Same author

A chitosan/rGO/Fe<sub>3</sub>O<sub>4</sub>-modified electrode for sensitive cholesterol determination in blood serum.

RSC advances·2026
Same author

Assessment of gastric electrical impedance tomography by<sup>13</sup>C-acetate breath test for gastric retention evaluation.

Medical engineering & physics·2026
Same author

Simultaneous assessments of local muscle quantity and quality by electrical impedance tomography (EIT) imaging.

Physiological measurement·2026
Same author

Physiological swelling imaging in human calf under stocking compression by sparse Bayesian learning implemented into electrical impedance tomography (SBL-EIT).

Biomedical engineering letters·2026
Same author

Conductive Response Imaging in Thigh Muscle Compartments by Electrical Impedance Tomography for Efficient Bicycle Training Strategy.

Annals of biomedical engineering·2026
Same author

2D boundary shape detection based on camera for enhanced electrode placement in lung electrical impedance tomography.

Biomedical physics & engineering express·2025

Related Experiment Video

Updated: Jul 19, 2025

Conformable Wearable Electrodes: From Fabrication to Electrophysiological Assessment
10:03

Conformable Wearable Electrodes: From Fabrication to Electrophysiological Assessment

Published on: July 22, 2022

4.5K

Skin layer classification by feedforward neural network in bioelectrical impedance spectroscopy.

Kiagus Aufa Ibrahim1, Marlin Ramadhan Baidillah2, Ridwan Wicaksono3

  • 1Department of Mechanical Engineering, Graduate School of Science and Engineering, Chiba University, Chiba, Japan.

Journal of Electrical Bioimpedance
|August 11, 2023
PubMed
Summary

Feedforward neural networks (FNNs) accurately classify skin layer conductivity changes using bioelectrical impedance spectroscopy (BIS). This method enhances dielectric diagnosis by differentiating conductivity in specific skin layers, improving accuracy in research and clinical applications.

Keywords:
Bioelectrical impedance spectroscopyConductivity changeDistribution of relaxation timesFeedforward neural network

More Related Videos

Examining Local Network Processing using Multi-contact Laminar Electrode Recording
13:40

Examining Local Network Processing using Multi-contact Laminar Electrode Recording

Published on: September 8, 2011

12.8K
Author Spotlight: Studying Brain Endothelial Barrier in Metastatic Cancer Using Impedance-Based Biosensors
09:38

Author Spotlight: Studying Brain Endothelial Barrier in Metastatic Cancer Using Impedance-Based Biosensors

Published on: September 22, 2023

591

Related Experiment Videos

Last Updated: Jul 19, 2025

Conformable Wearable Electrodes: From Fabrication to Electrophysiological Assessment
10:03

Conformable Wearable Electrodes: From Fabrication to Electrophysiological Assessment

Published on: July 22, 2022

4.5K
Examining Local Network Processing using Multi-contact Laminar Electrode Recording
13:40

Examining Local Network Processing using Multi-contact Laminar Electrode Recording

Published on: September 8, 2011

12.8K
Author Spotlight: Studying Brain Endothelial Barrier in Metastatic Cancer Using Impedance-Based Biosensors
09:38

Author Spotlight: Studying Brain Endothelial Barrier in Metastatic Cancer Using Impedance-Based Biosensors

Published on: September 22, 2023

591

Area of Science:

  • Biophysics
  • Biomedical Engineering
  • Electrical Engineering

Background:

  • Bioelectrical impedance spectroscopy (BIS) traditionally treats skin as a bulk, limiting differentiation of conductivity changes in individual layers.
  • Accurate classification of skin layers is crucial for diagnosing dielectric characteristics and understanding conductivity variations.
  • Feedforward neural networks (FNNs) offer a promising approach to overcome the limitations of bulk analysis in BIS.

Purpose of the Study:

  • To develop and validate an FNN model for classifying conductivity changes in specific skin layers.
  • To improve the accuracy of skin layer differentiation in BIS for dielectric diagnosis.
  • To investigate the effectiveness of FNN in predicting conductivity changes based on impedance parameters and frequency selection.

Main Methods:

  • Implemented FNN for predicting skin layer conductivity changes (k=1-5).
  • Utilized four impedance inputs (magnitude, phase angle, resistance, reactance) for feature selection.
  • Employed low and high frequency pairs, determined by distribution of relaxation time (DRT), to minimize noise.
  • Generated a training dataset of 10,200 simulated cases for FNN training.
  • Validated the FNN model using porcine skin experiments with varying NaCl concentrations.

Main Results:

  • The FNN model achieved 90.6% accuracy in classifying conductivity changes in the dermis layer of porcine skin.
  • The classification accuracy was consistent for both bipolar and tetrapolar electrode setups at specific frequencies.
  • Feature extraction based on impedance parameters at specific frequencies effectively minimized measurement noise and systematic errors.

Conclusions:

  • FNN-based skin layer classification in BIS is a viable and accurate method for differentiating conductivity changes.
  • This approach enhances the diagnostic potential of BIS for skin dielectric characteristics.
  • The proposed method offers a robust solution for noise reduction and error minimization in impedance measurements.