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

1.4K
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...
1.4K
Perceiving Loudness, Pitch, and Location01:21

Perceiving Loudness, Pitch, and Location

1.2K
The human brain perceives pitch through two primary mechanisms reflected in place theory and frequency theory. Each mechanism describes how sound waves are interpreted as specific pitches by the brain, offering insights into the intricate processes of auditory perception.
Place theory, or place coding, suggests that different pitches are heard because various sound waves activate specific locations along the cochlea's basilar membrane. The brain determines the pitch of a sound by...
1.2K
Classification of Signals01:30

Classification of Signals

1.5K
In signal processing, signals are classified based on various characteristics: continuous-time versus discrete-time, periodic versus aperiodic, analog versus digital, and causal versus noncausal. Each category highlights distinct properties crucial for understanding and manipulating signals.
A continuous-time signal holds a value at every instant in time, representing information seamlessly. In contrast, a discrete-time signal holds values only at specific moments, often denoted as x(n), where...
1.5K

You might also read

Related Articles

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

Sort by
Same author

Error-related potentials detection to enhance human-robot collaboration: a mini review.

Frontiers in neuroergonomics·2026
Same author

Near-invisible c-VEP-based passive BCI for mental workload monitoring.

Journal of neural engineering·2026
Same author

A Unified Framework for Matrix Backpropagation.

IEEE transactions on neural networks and learning systems·2025
Same author

Compact Colocated Bimodal EEG/fNIRS Multi-Distance Sensor.

Sensors (Basel, Switzerland)·2025
Same author

Does topological data analysis work for EEG-based brain-computer interfaces?

Journal of neural engineering·2025
Same author

Optimizing multimodal alarms to mitigate inattentional blindness in air traffic control.

Applied ergonomics·2025

Related Experiment Video

Updated: Mar 13, 2026

A Cognitive Paradigm to Investigate Interference in Working Memory by Distractions and Interruptions
10:38

A Cognitive Paradigm to Investigate Interference in Working Memory by Distractions and Interruptions

Published on: July 16, 2015

14.2K

Efficient Workload Classification based on Ignored Auditory Probes: A Proof of Concept.

Raphaëlle N Roy1, Stéphane Bonnet2, Sylvie Charbonnier1

  • 1Université Grenoble AlpesGrenoble, France; Gipsa-Lab, Centre National de la Recherche ScientifiqueGrenoble, France.

Frontiers in Human Neuroscience
|October 30, 2016
PubMed
Summary
This summary is machine-generated.

This study shows that ignored auditory probes can accurately classify mental workload using electroencephalography (EEG). This method offers a non-intrusive way to estimate cognitive load for adaptive interfaces.

Keywords:
auditory evoked potentialsclassificationspatial filteringworkload

More Related Videos

Measurement of Neurophysiological Signals of Ignoring and Attending Processes in Attention Control
09:37

Measurement of Neurophysiological Signals of Ignoring and Attending Processes in Attention Control

Published on: July 5, 2015

9.6K
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

2.7K

Related Experiment Videos

Last Updated: Mar 13, 2026

A Cognitive Paradigm to Investigate Interference in Working Memory by Distractions and Interruptions
10:38

A Cognitive Paradigm to Investigate Interference in Working Memory by Distractions and Interruptions

Published on: July 16, 2015

14.2K
Measurement of Neurophysiological Signals of Ignoring and Attending Processes in Attention Control
09:37

Measurement of Neurophysiological Signals of Ignoring and Attending Processes in Attention Control

Published on: July 5, 2015

9.6K
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

2.7K

Area of Science:

  • Neuroergonomics
  • Cognitive Science
  • Signal Processing

Background:

  • Mental workload estimation is crucial in neuroergonomics, with electroencephalography (EEG) offering direct assessment.
  • Event-related potentials (ERPs) elicited by auditory probes can reflect workload, but research on ignored probes for classification is limited.

Purpose of the Study:

  • To develop and validate a method for efficient mental workload classification using ignored auditory probes.
  • To demonstrate the effectiveness of a single-stimulus paradigm and spatial filtering in EEG-based workload estimation.

Main Methods:

  • Utilized ignored auditory probes within a single-stimulus paradigm during the Multi-Attribute Task Battery - II.
  • Applied signal processing including denoising, ERP extraction, and spatial filtering (canonical correlation analysis).
  • Performed binary classification using Fisher Linear Discriminant Analysis (LDA) with fivefold cross-validation.

Main Results:

  • Achieved classification accuracy exceeding 80% for all participants.
  • Demonstrated minimal intrusiveness due to the single-stimulus approach.
  • Validated the efficacy of spatial filtering for ignored auditory probe ERPs.

Conclusions:

  • Ignored auditory probes are effective for high-performance mental workload classification.
  • The proposed method enables efficient and non-intrusive mental state monitoring.
  • This research supports the development of adaptive user interfaces in real-world settings.