AIMC Topic: Emotions

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Enhancing aspect-based multi-labeling with ensemble learning for ethical logistics.

PloS one
In the dynamic domain of logistics, effective communication is essential for streamlined operations. Our innovative solution, the Multi-Labeling Ensemble (MLEn), tackles the intricate task of extracting multi-labeled data, employing advanced techniqu...

Analysis of addiction craving onset through natural language processing of the online forum Reddit.

PloS one
AIMS: Alcohol cravings are considered a major factor in relapse among individuals with alcohol use disorder (AUD). This study aims to investigate the frequency and triggers of cravings in the daily lives of people with alcohol-related issues. Large a...

TASA: Temporal Attention With Spatial Autoencoder Network for Odor-Induced Emotion Classification Using EEG.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
The olfactory system enables humans to smell different odors, which are closely related to emotions. The high temporal resolution and non-invasiveness of Electroencephalogram (EEG) make it suitable to objectively study human preferences for odors. Ef...

Multi-scale 3D-CRU for EEG emotion recognition.

Biomedical physics & engineering express
In this paper, we propose a novel multi-scale 3D-CRU model, with the goal of extracting more discriminative emotion feature from EEG signals. By concurrently exploiting the relative electrode locations and different frequency subbands of EEG signals,...

Natural language sentiment as an indicator of depression and anxiety symptoms: a longitudinal mixed methods study.

Cognition & emotion
The study tested how the use of positive- (e.g. beautiful) and negative-valenced (e.g. horrible) words in natural language and its change in time affects the severity of depression and anxiety symptoms among depressed and non-depressed individuals. T...

Detecting emotions through EEG signals based on modified convolutional fuzzy neural network.

Scientific reports
Emotion is a human sense that can influence an individual's life quality in both positive and negative ways. The ability to distinguish different types of emotion can lead researchers to estimate the current situation of patients or the probability o...

Auto Diagnosis of Parkinson's Disease Via a Deep Learning Model Based on Mixed Emotional Facial Expressions.

IEEE journal of biomedical and health informatics
Parkinson's disease (PD) is a common degenerative disease of the nervous system in the elderly. The early diagnosis of PD is very important for potential patients to receive prompt treatment and avoid the aggravation of the disease. Recent studies ha...

Sensing technologies and machine learning methods for emotion recognition in autism: Systematic review.

International journal of medical informatics
BACKGROUND: Human Emotion Recognition (HER) has been a popular field of study in the past years. Despite the great progresses made so far, relatively little attention has been paid to the use of HER in autism. People with autism are known to face pro...

Emotion recognition with reduced channels using CWT based EEG feature representation and a CNN classifier.

Biomedical physics & engineering express
Although emotion recognition has been studied for decades, a more accurate classification method that requires less computing is still needed. At present, in many studies, EEG features are extracted from all channels to recognize emotional states, ho...

A neurofunctional signature of subjective disgust generalizes to oral distaste and socio-moral contexts.

Nature human behaviour
While disgust originates in the hard-wired mammalian distaste response, the conscious experience of disgust in humans strongly depends on subjective appraisal and may even extend to socio-moral contexts. Here, in a series of studies, we combined func...