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 Experiment Videos

ECG data compression using Jacobi polynomials.

Daniel Tchiotsop1, Didier Wolf, Valérie Louis-Dorr

  • 1Electrical Engineering Department, IUT FOTSO Victor, University of Dschang, Cameroon. dtchiot@yahoo.fr

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
|November 16, 2007
PubMed
Summary
This summary is machine-generated.

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

A lightweight 1D convolutional neural network model for arrhythmia diagnosis from electrocardiogram signal.

Physical and engineering sciences in medicine·2025
Same author

A Variational Network for Biomedical Images Denoising using Bayesian model and Auto-Encoder.

Biomedical physics & engineering express·2024
Same author

Visual electrophysiology and neuropsychology in bipolar disorders: A review on current state and perspectives.

Neuroscience and biobehavioral reviews·2022
Same author

An Overview of Supervised Machine Learning Methods and Data Analysis for COVID-19 Detection.

Journal of healthcare engineering·2021
Same author

Anatomical 3D Modeling Using IR Sensors and Radiometric Processing Based on Structure from Motion: Towards a Tool for the Diabetic Foot Diagnosis.

Sensors (Basel, Switzerland)·2021
Same author

Biomedical Image Classification in a Big Data Architecture Using Machine Learning Algorithms.

Journal of healthcare engineering·2021
Same journal

Analysis of End-Tidal CO2 Variability During Plateau Waves Episodes: An Information Theoretic Approach<sup></sup>.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference·2025
Same journal

AI and Tomosynthesis for Breast Cancer Molecular Subtyping: A step toward precision medicine<sup></sup>.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference·2025
Same journal

Towards Sustainable Protein Recovery from Biological Waste: Assessing Polyethersulfone-based Microfiltration.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference·2025
Same journal

Analysis of the cardiovascular response to standardized polymicrobial peritonitis experimental model.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference·2025
Same journal

Automated Wrist Ultrasound Image Bone Enhancement and Segmentation Using Deep Learning.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference·2025
Same journal

A Deep Learning approach for Depressive Symptoms assessment in Parkinson's disease patients using facial videos.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference·2025
See all related articles

This study introduces a novel Electrocardiogram (ECG) data compression method using Jacobi polynomials, achieving competitive results compared to wavelet decomposition. The technique effectively reduces ECG data size by decomposing signals and discarding small coefficients.

Area of Science:

  • Biomedical Engineering
  • Signal Processing
  • Data Compression

Background:

  • Electrocardiogram (ECG) data compression is crucial for efficient storage and transmission in healthcare.
  • Existing methods like wavelet decomposition have limitations in ECG signal processing.
  • Novel approaches are needed to improve the efficiency and accuracy of ECG compression.

Purpose of the Study:

  • To present a new method for ECG data compression utilizing Jacobi polynomials.
  • To evaluate the performance of this Jacobi polynomial-based compression against established techniques.
  • To explore strategies for optimizing ECG compression using polynomial decomposition.

Main Methods:

  • ECG signals segmented into blocks corresponding to cardiac cycles.

Related Experiment Videos

  • Decomposition of segmented ECG signals into Jacobi polynomial bases.
  • Computation of Jacobi transform coefficients using Gauss quadratures.
  • Discarding small-valued coefficients during the reconstruction phase.
  • Consideration of various segmentation strategies and Jacobi polynomial families.
  • Development of a strategy to mitigate boundary effects.

    • Main Results:

    • The proposed Jacobi polynomial-based ECG compression method yielded interesting results.
    • Performance was compared favorably against ECG compression using wavelet decomposition.
    • The method demonstrated potential for effective ECG data size reduction.
    • Boundary effect cancellation strategy proved efficient.

    Conclusions:

    • Jacobi polynomials offer a viable and effective alternative for ECG data compression.
    • The presented method shows promise for improving diagnostic data management.
    • Further research can enhance the compression ratios and accuracy.