Javascript must be enabled to continue!
Psychoacoustic Parameters and Variations in Annoyance Perception: An EEG-based Study
View through CrossRef
Studies have indicated that prolonged exposure to unwanted acoustic
stimuli can trigger noise annoyance. Large engines are prevalent in
industrial and traffic settings, but their high performance often comes
with significant radiated noise emissions, leading to relevant staff
members’ annoyance. Traditional evaluations, for example psychoacoustic
parameters, of noise annoyance fail to adequately account for the
physiological processes involved in sound perception.
Electroencephalogram (EEG) signals can provide insights into the
physiological responses to external acoustic stimuli. Here, we design an
experimental paradigm to capture EEG signals and extract spectral and
brain’s functional connectivity features when the participants evaluate
the annoyance of diesel engine radiated noise samples. The correlation
between spectral features and subjective annoyance shows that the delta
and alpha bands’ relative power could reflect noise annoyance.
Delta-band brain network analysis inferred those differences in
exogenous temporal attention networks’ threshold, about 30%, result in
variations in noise annoyance perception.
Title: Psychoacoustic Parameters and Variations in Annoyance Perception: An EEG-based Study
Description:
Studies have indicated that prolonged exposure to unwanted acoustic
stimuli can trigger noise annoyance.
Large engines are prevalent in
industrial and traffic settings, but their high performance often comes
with significant radiated noise emissions, leading to relevant staff
members’ annoyance.
Traditional evaluations, for example psychoacoustic
parameters, of noise annoyance fail to adequately account for the
physiological processes involved in sound perception.
Electroencephalogram (EEG) signals can provide insights into the
physiological responses to external acoustic stimuli.
Here, we design an
experimental paradigm to capture EEG signals and extract spectral and
brain’s functional connectivity features when the participants evaluate
the annoyance of diesel engine radiated noise samples.
The correlation
between spectral features and subjective annoyance shows that the delta
and alpha bands’ relative power could reflect noise annoyance.
Delta-band brain network analysis inferred those differences in
exogenous temporal attention networks’ threshold, about 30%, result in
variations in noise annoyance perception.
Related Results
THE EFFECT OF PETHIDINE ON THE NEONATAL EEG
THE EFFECT OF PETHIDINE ON THE NEONATAL EEG
SUMMARYThirty‐two preterm infants were monitored with an on‐line cotside EEG system for periods of up to nine days. Changes in the normal pattern of discontinuity of the EEG were s...
Computation of the electroencephalogram (EEG) from network models of point neurons
Computation of the electroencephalogram (EEG) from network models of point neurons
Abstract
The electroencephalogram (EEG) is one of the main tools for non-invasively studying brain function and dysfunction. To better interpret EEGs in terms of ne...
Hybrid AI-Based Approach Utilizing EEG-Facial Expression fusion for Human-Machine Interaction
Hybrid AI-Based Approach Utilizing EEG-Facial Expression fusion for Human-Machine Interaction
Approche Hybride Basée sur l'IA, par fusion EEG-Expression Faciale pour l'Interaction Humain-Machine
La reconnaissance des émotions par électroencéphalogramme (EEG)...
Evaluation of Mathematical Cognitive Functions with the Use of EEG Brain Imaging
Evaluation of Mathematical Cognitive Functions with the Use of EEG Brain Imaging
During the last decades, the interest displayed in neurocognitive and brain science research is relatively high. In this chapter, the cognitive neuroscience field approach focuses ...
Comparing Annoyance Potency Assessments for Odors from Different Livestock Animals
Comparing Annoyance Potency Assessments for Odors from Different Livestock Animals
(1) Background: When it comes to estimating the annoyance potency of odors, European countries relate to different guidelines. In a previous study we compared complaint rates for d...
Motion robustness validation of a Phase-Locked Loop for EEG phase tracking in Brain-Computer Interfaces
Motion robustness validation of a Phase-Locked Loop for EEG phase tracking in Brain-Computer Interfaces
Background. Closed loop brain-computer interfaces dynamically adjust stimulation settings and/or timings based upon concurrently measured data. EEG (electroencephalography) is a wi...
Computation of Psycho-Acoustic Annoyance Using Deep Neural Networks
Computation of Psycho-Acoustic Annoyance Using Deep Neural Networks
Psycho-acoustic parameters have been extensively used to evaluate the discomfort or pleasure produced by the sounds in our environment. In this context, wireless acoustic sensor ne...
Riemannian Geometry-Based Advances in Automated EEG Artifact Rejection
Riemannian Geometry-Based Advances in Automated EEG Artifact Rejection
Avancées en rejet automatique des artéfacts EEG basées sur la géométrie riemannienne
L’électroencéphalographie (EEG) mesure les potentiels post-synaptiques générés ...

