AI Medical Compendium Topic:
Emotions

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A Continuously Updated, Computationally Efficient Stress Recognition Framework Using Electroencephalogram (EEG) by Applying Online Multitask Learning Algorithms (OMTL).

IEEE journal of biomedical and health informatics
Recognizing the factors that cause stress is a crucial step toward early detection of stressors. In this regard, several studies make an effort to recognize individuals' stress using an Electroencephalogram (EEG). However, current EEG-based stress re...

Identifying Suitable Brain Regions and Trial Size Segmentation for Positive/Negative Emotion Recognition.

International journal of neural systems
The development of suitable EEG-based emotion recognition systems has become a main target in the last decades for Brain Computer Interface applications (BCI). However, there are scarce algorithms and procedures for real-time classification of emotio...

Discriminant Functional Learning of Color Features for the Recognition of Facial Action Units and Their Intensities.

IEEE transactions on pattern analysis and machine intelligence
Color is a fundamental image feature of facial expressions. For example, when we furrow our eyebrows in anger, blood rushes in, turning some face areas red; or when one goes white in fear as a result of the drainage of blood from the face. Surprising...

Using person-specific neural networks to characterize heterogeneity in eating disorders: Illustrative links between emotional eating and ovarian hormones.

The International journal of eating disorders
OBJECTIVE: Emotional eating has been linked to ovarian hormone functioning, but no studies to-date have considered the role of brain function. This knowledge gap may stem from methodological challenges: Data are heterogeneous, violating assumptions o...

EEG-Based Emotion Recognition Using Quadratic Time-Frequency Distribution.

Sensors (Basel, Switzerland)
Accurate recognition and understating of human emotions is an essential skill that can improve the collaboration between humans and machines. In this vein, electroencephalogram (EEG)-based emotion recognition is considered an active research field wi...

Exploring the prediction of emotional valence and pharmacologic effect across fMRI studies of antidepressants.

NeuroImage. Clinical
BACKGROUND: Clinically approved antidepressants modulate the brain's emotional valence circuits, suggesting that the response of these circuits could serve as a biomarker for screening candidate antidepressant drugs. However, it is necessary that the...

Representational fluidity in embodied (artificial) cognition.

Bio Systems
Theories of embodied cognition agree that the body plays some role in human cognition, but disagree on the precise nature of this role. While it is (together with the environment) fundamentally engrained in the so-called 4E (or multi-E) cognition sta...

The computerized scoring algorithm for the autobiographical memory test: updates and extensions for analyzing memories of English-speaking adults.

Memory (Hove, England)
The Autobiographical Memory Test (AMT) has been central in psychopathological studies of memory dysfunctions, as reduced memory specificity or overgeneralised autobiographical memory has been recognised as a hallmark vulnerability for depression. In ...

Do a robot's social skills and its objection discourage interactants from switching the robot off?

PloS one
Building on the notion that people respond to media as if they were real, switching off a robot which exhibits lifelike behavior implies an interesting situation. In an experimental lab study with a 2x2 between-subjects-design (N = 85), people were g...

A Systematic Review for Human EEG Brain Signals Based Emotion Classification, Feature Extraction, Brain Condition, Group Comparison.

Journal of medical systems
The study of electroencephalography (EEG) signals is not a new topic. However, the analysis of human emotions upon exposure to music considered as important direction. Although distributed in various academic databases, research on this concept is li...