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

An effective coding technique for the compression of one-dimensional signals using wavelet transforms.

Mohammed Abo-Zahhad1, Bashar A Rajoub

  • 1Electronics Engineering Department, Hijjawi Faculty for Engineering Technology, Yarmouk University, Irbid, Jordan. zahad@yu.edu.jo

Medical Engineering & Physics
|June 14, 2002
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

An accurate analytical modeling method for microwave-based breast tumor detection and phantom manufacturing.

Biomedical engineering letters·2026
Same author

Development of an AI-powered AR glasses system for real-time first aid guidance in emergency situations.

BioData mining·2025
Same author

Real time intelligent garbage monitoring and efficient collection using Yolov8 and Yolov5 deep learning models for environmental sustainability.

Scientific reports·2025
Same author

Minimization of occurrence of retained surgical items using machine learning and deep learning techniques: a review.

BioData mining·2024
Same author

Virtual and augmented reality in biomedical engineering.

Biomedical engineering online·2023
Same author

Robust Vehicle Detection and Counting Algorithm Employing a Convolution Neural Network and Optical Flow.

Sensors (Basel, Switzerland)·2019

This study presents a novel wavelet transform technique for efficient one-dimensional signal compression. The method achieves high compression ratios for electrocardiogram (ECG) signals with minimal data loss.

Area of Science:

  • Signal Processing
  • Data Compression
  • Biomedical Engineering

Background:

  • Wavelet transforms are effective for signal analysis and compression.
  • Efficient compression of biomedical signals like ECG is crucial for storage and transmission.
  • Existing compression methods may not optimally preserve signal integrity.

Purpose of the Study:

  • To introduce an effective wavelet transform-based compression technique for 1D signals.
  • To develop a new coding algorithm for compressing the binary stream of wavelet coefficients.
  • To evaluate the technique's performance on normal and abnormal ECG signals.

Main Methods:

  • Generating a binary stream encoding wavelet coefficient structure (zero/nonzero locations).
  • Developing a novel run-length encoding-like algorithm for binary stream compression.

Related Experiment Videos

  • Assessing compression ratio (CR) and percent root-mean square difference (PRD) for performance evaluation.

    • Main Results:

    • Achieved compression ratios of 19:1 and 45:1 for ECG signals.
    • Maintained low percent root-mean square differences of 1% and 2.8%.
    • Evaluated the impact of signal length, thresholding, wavelet filters, and finite word length on compression quality.

    Conclusions:

    • The proposed wavelet transform technique offers effective compression for 1D signals, particularly ECG.
    • The novel coding algorithm demonstrates high compression ratios with acceptable signal reconstruction fidelity.
    • The technique's performance is influenced by various parameters, requiring careful selection for optimal results.