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

Real-time detection of the EEG using a two-component wave model

A J Lim, W D Winters

    Computer Programs in Biomedicine
    |June 1, 1980
    PubMed
    Summary

    This study introduces a real-time program for detecting faster and slower wave types in electroencephalogram (EEG) signals. The system provides quantified characterization of brainwave activity for enhanced EEG analysis.

    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

    Comparison of performance and carcass composition of a novel slow-growing crossbred broiler with fast-growing broiler for chicken meat in Australia.

    Poultry science·2021
    Same author

    A Solid State Pulsed Coagulating Diathermy Instrument:1 Preliminary Report.

    The Australian and New Zealand journal of surgery·2017
    Same author

    OBSERVATIONS ON THE INFLUENZA EPIDEMIC IN THE BRISTOL GENERAL HOSPITAL: With Special Reference to the Use of "N. Pane's Siero Anti-pneumonico" for Prophylaxis and Treatment of Pulmonary Complications.

    British medical journal·2010
    Same author

    Congenital masses of the lung: prenatal and postnatal imaging evaluation.

    Journal of thoracic imaging·2001
    Same author

    Increased antibiotic resistance of E. coli exposed to static magnetic fields.

    Bioelectromagnetics·2001
    Same author

    Avascular necrosis of the femoral head in children with chronic renal disease.

    Radiology·2001

    Area of Science:

    • Neuroscience
    • Biomedical Engineering
    • Computer Science

    Background:

    • Electroencephalogram (EEG) signals exhibit complex wave patterns.
    • Characterizing EEG waves is crucial for neurological diagnostics.
    • Existing methods may lack real-time, quantified analysis capabilities.

    Purpose of the Study:

    • To develop a real-time program for detecting and characterizing distinct wave types in EEG signals.
    • To implement a system for continuous, quantified analysis of electroencephalogram data.
    • To integrate EEG analysis within a multitask computing environment.

    Main Methods:

    • Modeling EEG signals as superimposed faster, smaller waves and slower, larger waves.
    • Developing a specialized User Clock Routine for a Data General Corporation NOVA minicomputer.
    • Implementing continuous, real-time detection algorithms for both wave types.

    Main Results:

    • Successful continuous, real-time detection of both faster and slower EEG wave types.
    • Quantified characterization of EEG signal components.
    • Integration into a multitask package for comprehensive EEG analysis.

    Conclusions:

    • The developed program enables efficient, real-time quantification of EEG wave characteristics.
    • This approach facilitates a deeper understanding of brainwave dynamics.
    • The system supports simultaneous data output for diverse applications.

    Related Experiment Videos