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

Brain Waves01:23

Brain Waves

Brain waves are electrical signals generated by the neurons in the brain, which are regularly monitored to measure mental activities. Brain waves and their frequency ranges can be measured using an electroencephalogram or EEG. There are four main types of brain waves, each with distinct characteristics:

You might also read

Related Articles

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

Sort by
Same author

Cardiorespiratory cross-frequency coupling biomarker for sudden unexpected death in epilepsy.

Epilepsia·2025
Same author

Inhibition of proprotein convertase SKI-1 prevents blood vessel alteration after stroke.

Nature cardiovascular research·2025
Same author

Delta-fast ripple coupling suppression: designing a brain-mimetic stimulation paradigm for seizure abolishment.

Frontiers in neuroscience·2025
Same author

Respiratory Signal Extraction from ECG using a Phase-Amplitude Cross-Frequency Coupling Index.

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

Wavelet phase coherence of ictal scalp EEG-extracted muscle activity (SMA) as a biomarker for sudden unexpected death in epilepsy (SUDEP).

PloS one·2024
Same author

WONOEP appraisal: Modeling early onset epilepsies.

Epilepsia·2024
Same journal

Pulsatile Hemodynamics of Prehypertension and Hypertension: Associations with Pressure and Sex.

Annals of biomedical engineering·2026
Same journal

A Pressure Difference-Based Strategy for Blood Oxygen Control in Membrane Oxygenators: Reduced Modeling, Computational Simulation, and Exploratory In Vivo Evaluation.

Annals of biomedical engineering·2026
Same journal

Multidirectional Optical Bone Densitometry Using a Simulation-Based Machine Learning Model: Experimental Validation with Bone Phantoms.

Annals of biomedical engineering·2026
Same journal

Numerical Study of Human Torso Mechanical Response and Injury Assessment Under Blast Loading with Bulletproof Protection.

Annals of biomedical engineering·2026
Same journal

Immediate and Mid-Long-Term Effects of Foot Orthoses on Gait Biomechanics and Clinical Characteristics in Medial Knee Osteoarthritis: A Systematic Review and Meta-analysis.

Annals of biomedical engineering·2026
Same journal

Screening and Evaluation of Post-stroke Dysphagia: Insights from Neurology, Artificial Intelligence and Data Science-A Scoping Review.

Annals of biomedical engineering·2026
See all related articles

Related Experiment Video

Updated: Jun 26, 2026

Automatic Detection of Highly Organized Theta Oscillations in the Murine EEG
09:35

Automatic Detection of Highly Organized Theta Oscillations in the Murine EEG

Published on: March 10, 2017

A wavelet packet-based algorithm for the extraction of neural rhythms.

Osbert C Zalay1, Eunji E Kang, Marija Cotic

  • 1Institute of Biomaterials and Biomedical Engineering, University of Toronto, 164 College Street, Rosebrugh Building, Room 407, Toronto, ON M5S 3G9, Canada. oz.zalay@utoronto.ca

Annals of Biomedical Engineering
|January 15, 2009
PubMed
Summary
This summary is machine-generated.

We developed neural rhythm extraction (NRE), a wavelet-based method to isolate brain rhythms. NRE effectively separates neural rhythms from complex signals for improved brain function analysis.

More Related Videos

Using Wavelet Entropy to Demonstrate how Mindfulness Practice Increases Coordination between Irregular Cerebral and Cardiac Activities
08:08

Using Wavelet Entropy to Demonstrate how Mindfulness Practice Increases Coordination between Irregular Cerebral and Cardiac Activities

Published on: May 10, 2017

Related Experiment Videos

Last Updated: Jun 26, 2026

Automatic Detection of Highly Organized Theta Oscillations in the Murine EEG
09:35

Automatic Detection of Highly Organized Theta Oscillations in the Murine EEG

Published on: March 10, 2017

Using Wavelet Entropy to Demonstrate how Mindfulness Practice Increases Coordination between Irregular Cerebral and Cardiac Activities
08:08

Using Wavelet Entropy to Demonstrate how Mindfulness Practice Increases Coordination between Irregular Cerebral and Cardiac Activities

Published on: May 10, 2017

Area of Science:

  • Neuroscience
  • Signal Processing

Background:

  • Neural rhythms are crucial for brain function and disease diagnosis.
  • Isolating these rhythms is challenging due to their complex, time-varying nature.

Purpose of the Study:

  • To introduce a novel signal analysis technique, neural rhythm extraction (NRE).
  • To effectively isolate and classify neural rhythms from complex biological signals.

Main Methods:

  • Utilized wavelet packet analysis combined with a threshold-based scheme.
  • Applied the NRE technique to in vitro rat neural recordings and human electroencephalogram (EEG) data.

Main Results:

  • Successfully isolated and classified individual neural rhythms, even low-amplitude ones masked by artifacts.
  • Demonstrated NRE's ability to discriminate features with similar time-frequency localizations.
  • Showcased NRE's effectiveness on both animal and human neural data.

Conclusions:

  • Neural rhythm extraction (NRE) is a versatile and effective method for analyzing neural signals.
  • NRE can enhance other analysis techniques like independent component analysis (ICA) for detection, classification, and tracking.