Related Experiment Video
Updated: Aug 26, 2025
05:48
Author Spotlight: Investigating the Impact of Emotional Prosodies on Voice Recognition and Perception
Published on: August 9, 2024
1.6K
A Novel Domain Adversarial Networks Based on 3D-LSTM and Local Domain Discriminator for Hearing-Impaired Emotion
IEEE Journal of Biomedical and Health Informatics
|October 6, 2022
Summary
This study developed an adversarial neural network to recognize emotions in hearing-impaired individuals using electroencephalography (EEG) data. The model achieved high accuracy, identifying brain regions involved in emotional processing.
Area of Science:
- Neuroscience
- Artificial Intelligence
- Biomedical Engineering
Background:
- Emotion recognition is challenging due to individual differences.
- Deep network-based adversarial learning shows promise for cross-subject emotion recognition.
- Understanding emotions in hearing-impaired individuals requires specialized datasets and methods.
Purpose of the Study:
- To construct a novel hearing-impaired electroencephalography (EEG) emotion dataset.
- To develop and evaluate an emotional domain adversarial neural network (EDANN) for emotion recognition in hearing-impaired subjects.
- To investigate the neural correlates of emotion recognition in this population.
Main Methods:
- A hearing-impaired EEG emotion dataset with positive, neutral, and negative emotions was created from 15 subjects.
- An EDANN was employed, incorporating a spatial filter matrix for reduced overfitting and a 3DLSTM-ConvNET for feature extraction.
- Emotion local domain discriminators were utilized to minimize distribution distances between similar emotions and different film groups.
Main Results:
- Subject-dependent emotion recognition accuracy reached an average of 0.984 (STD: 0.011).
- Subject-independent emotion recognition accuracy averaged 0.679 (STD: 0.140).
- Analysis revealed wider parietal and occipital lobe involvement in emotional recognition for hearing-impaired individuals, potentially linked to visual processing.
Conclusions:
- The proposed EDANN effectively recognizes emotions in hearing-impaired individuals, addressing the cross-subject challenge.
- The study provides valuable insights into the neural basis of emotion processing in the hearing-impaired population.
- The findings suggest a potential role of visual processing in auditory-related emotional responses for this group.
More Related Videos
Related Concept Videos
01:21Perceiving Loudness, Pitch, and Location
401
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...
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...
401
01:20Labeling Emotion
224
Emotional labeling is a cognitive process that involves identifying and naming one's emotions, such as anger, fear, happiness, or sadness. It allows individuals to recognize and express their internal emotional states, a critical aspect of emotional regulation and communication. Labeling emotions requires more than mere recognition; it also involves drawing upon memory and contextual cues to understand the current situation and apply a corresponding emotional label. For instance, feeling...
224