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

Auditory Perception01:17

Auditory Perception

931
The auditory system is essential for sound perception, utilizing various critical structures. When sound waves enter the outer ear, they travel through the ear canal and cause the eardrum to vibrate. These vibrations are then transmitted to the middle ear, where three tiny bones – the malleus, incus, and stapes – amplify the sound. This amplification is crucial, as it ensures that the sound vibrations are strong enough to be conveyed to the inner ear. These vibrations then reach the...
931
RMS Value in AC Circuit01:13

RMS Value in AC Circuit

3.2K
The root mean square (RMS) value is a measure of the effective or average value of an alternating current (AC) waveform. In AC circuits, the voltage or current waveform constantly changes direction and magnitude, making it difficult to describe with a single value. The RMS value provides a convenient way to calculate the equivalent DC voltage or current that would produce the same heating effect in a resistor as the AC waveform.
Mathematically, the RMS value of an AC waveform is the square root...
3.2K
Average Power01:13

Average Power

941
In practical electrical applications, the concept of time-varying instantaneous power is not frequently utilized. Instead, focus shifts to the more practical quantity known as average power. Average power is determined by integrating the instantaneous power over a specified time period and subsequently dividing it by that duration.
941

You might also read

Related Articles

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

Sort by
Same author

Neurophysiological evidence of human hippocampal longitudinal differentiation in associative memory.

Nature communications·2025
Same author

Repair of bucket handle meniscus tears improves patient outcomes versus partial meniscectomy at the time of ACL reconstruction.

Journal of experimental orthopaedics·2024
Same author

The Effect of Greater Area Deprivation and Medicaid Insurance Status on Timing of Care and Rate of Reinjury After Anterior Cruciate Ligament Reconstruction.

Orthopaedic journal of sports medicine·2024
Same author

Dyslipidaemia is associated with Cutibacterium acnes hip and knee prosthetic joint infection.

International orthopaedics·2023
Same author

Machine learning classifiers for electrode selection in the design of closed-loop neuromodulation devices for episodic memory improvement.

Cerebral cortex (New York, N.Y. : 1991)·2023
Same author

A Control-Theoretical System for Modulating Hippocampal Gamma Oscillations Using Stimulation of the Posterior Cingulate Cortex.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society·2022

Related Experiment Video

Updated: Dec 30, 2025

A Method for Tracking the Time Evolution of Steady-State Evoked Potentials
12:03

A Method for Tracking the Time Evolution of Steady-State Evoked Potentials

Published on: May 25, 2019

8.9K

Subspace Averaging of Auditory Evoked Potentials.

David X Wang, Carlos E Davila

    Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
    |January 18, 2020
    PubMed
    Summary

    Subspace averaging enhances auditory evoked potential (AEP) detection by improving signal-to-noise ratio (SNR). This novel method offers a more efficient way to analyze brain responses to sound, crucial for diagnosing infant hearing loss.

    More Related Videos

    Infant Auditory Processing and Event-related Brain Oscillations
    06:34

    Infant Auditory Processing and Event-related Brain Oscillations

    Published on: July 1, 2015

    16.9K
    Assessment of Audio-Tactile Sensory Substitution Training in Participants with Profound Deafness Using the Event-Related Potential Technique
    11:39

    Assessment of Audio-Tactile Sensory Substitution Training in Participants with Profound Deafness Using the Event-Related Potential Technique

    Published on: September 7, 2022

    2.5K

    Related Experiment Videos

    Last Updated: Dec 30, 2025

    A Method for Tracking the Time Evolution of Steady-State Evoked Potentials
    12:03

    A Method for Tracking the Time Evolution of Steady-State Evoked Potentials

    Published on: May 25, 2019

    8.9K
    Infant Auditory Processing and Event-related Brain Oscillations
    06:34

    Infant Auditory Processing and Event-related Brain Oscillations

    Published on: July 1, 2015

    16.9K
    Assessment of Audio-Tactile Sensory Substitution Training in Participants with Profound Deafness Using the Event-Related Potential Technique
    11:39

    Assessment of Audio-Tactile Sensory Substitution Training in Participants with Profound Deafness Using the Event-Related Potential Technique

    Published on: September 7, 2022

    2.5K

    Area of Science:

    • Neuroscience
    • Biomedical Engineering
    • Signal Processing

    Background:

    • Auditory evoked potentials (AEPs) are crucial for assessing auditory function, particularly in newborns.
    • Low signal-to-noise ratio (SNR) in AEPs necessitates extensive signal averaging, often requiring thousands of trials.
    • Current methods face challenges in efficiently extracting reliable AEP signals.

    Purpose of the Study:

    • To introduce and evaluate a novel signal averaging technique for AEP analysis.
    • To develop an improved SNR estimator for AEP trials.
    • To compare the efficacy of the new subspace averaging method against conventional averaging techniques.

    Main Methods:

    • Developed a subspace averaging method that projects AEP data onto the signal subspace, defined by principal eigenvectors of the autocorrelation matrix.
    • Introduced a new SNR estimator specifically designed for AEP trials.
    • Compared SNR estimates obtained from conventional averaging and the proposed subspace averaging method.

    Main Results:

    • The subspace averaging method effectively captures key signal features within a low-dimensional subspace.
    • The newly developed SNR estimator provides reliable SNR assessments for AEP trials.
    • Subspace averaging demonstrated a significantly higher SNR compared to conventional averaging techniques.

    Conclusions:

    • Subspace averaging is a promising technique for improving AEP signal quality.
    • The enhanced SNR achieved with subspace averaging can lead to more efficient and accurate AEP analysis.
    • This method holds potential for advancing clinical applications of AEPs, such as early detection of hearing impairments.