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Emotions

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Design of Proactive Interaction for In-Vehicle Robots Based on Transparency.

Sensors (Basel, Switzerland)
Based on the transparency theory, this study investigates the appropriate amount of transparency information expressed by the in-vehicle robot under two channels of voice and visual in a proactive interaction scenario. The experiments are to test and...

Hybrid Model-Based Emotion Contextual Recognition for Cognitive Assistance Services.

IEEE transactions on cybernetics
Endowing ubiquitous robots with cognitive capabilities for recognizing emotions, sentiments, affects, and moods of humans in their context is an important challenge, which requires sophisticated and novel approaches of emotion recognition. Most studi...

An Artificial Intelligence-Based Reactive Health Care System for Emotion Detections.

Computational intelligence and neuroscience
In the past few years, remote monitoring technologies have grown increasingly important in the delivery of healthcare. According to healthcare professionals, a variety of factors influence the public perception of connected healthcare systems in a va...

Spatial-frequency-temporal convolutional recurrent network for olfactory-enhanced EEG emotion recognition.

Journal of neuroscience methods
BACKGROUND: Multimedia stimulation of brain activity is important for emotion induction. Based on brain activity, emotion recognition using EEG signals has become a hot issue in the field of affective computing.

Group Emotion Detection Based on Social Robot Perception.

Sensors (Basel, Switzerland)
Social robotics is an emerging area that is becoming present in social spaces, by introducing autonomous social robots. Social robots offer services, perform tasks, and interact with people in such social environments, demanding more efficient and co...

Deep Neural Networks Based on Span Association Prediction for Emotion-Cause Pair Extraction.

Sensors (Basel, Switzerland)
The emotion-cause pair extraction task is a fine-grained task in text sentiment analysis, which aims to extract all emotions and their underlying causes in a document. Recent studies have addressed the emotion-cause pair extraction task in a step-by-...

Emotion Analysis Method of Teaching Evaluation Texts Based on Deep Learning in Big Data Environment.

Computational intelligence and neuroscience
Accurate emotion analysis of teaching evaluation texts can help teachers effectively improve the quality of education and teaching. In order to improve the precision and accuracy of emotion analysis, this paper proposes an emotion recognition and ana...

Emotion Analysis Model of Microblog Comment Text Based on CNN-BiLSTM.

Computational intelligence and neuroscience
Aiming at the problems of over reliance on labor and low generalization of traditional emotion analysis methods based on dictionary and machine learning, an emotion analysis model of microblog comment text based on deep learning is proposed. Firstly,...

Robot touch with speech boosts positive emotions.

Scientific reports
A gentle touch is an essential part of human interaction that produces a positive care effect. Previously, robotics studies have shown that robots can reproduce a gentle touch that elicits similar, positive emotional responses in humans. However, whe...

SCC-MPGCN: self-attention coherence clustering based on multi-pooling graph convolutional network for EEG emotion recognition.

Journal of neural engineering
The emotion recognition with electroencephalography (EEG) has been widely studied using the deep learning methods, but the topology of EEG channels is rarely exploited completely. In this paper, we propose a self-attention coherence clustering based ...