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Emotions

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Gait-to-Gait Emotional Human-Robot Interaction Utilizing Trajectories-Aware and Skeleton-Graph-Aware Spatial-Temporal Transformer.

Sensors (Basel, Switzerland)
The emotional response of robotics is crucial for promoting the socially intelligent level of human-robot interaction (HRI). The development of machine learning has extensively stimulated research on emotional recognition for robots. Our research foc...

A temporal-spatial feature fusion network for emotion recognition with individual differences reduction.

Neuroscience
PURPOSE: In the context of EEG-based emotion recognition tasks, a conventional strategy involves the extraction of spatial and temporal features, subsequently fused for emotion prediction. However, due to the pronounced individual variability in EEG ...

On the relationship between music students' negative emotions, artificial intelligence readiness, and their engagement.

Acta psychologica
This study explored the relationship between negative emotions, engagement, and artificial intelligence (AI) readiness among 323 music students. The researchers employed SPSS (version 27) and AMOS (version 24) for analysis using the Emotion Beliefs Q...

Why AI Monitoring Faces Resistance and What Healthcare Organizations Can Do About It: An Emotion-Based Perspective.

Journal of medical Internet research
Continuous monitoring of patients' health facilitated by artificial intelligence (AI) has enhanced the quality of health care, that is, the ability to access effective care. However, AI monitoring often encounters resistance to adoption by decision m...

Exploring the Social Media Discussion of Breast Cancer Treatment Choices: Quantitative Natural Language Processing Study.

JMIR cancer
BACKGROUND: Early-stage breast cancer has the complex challenge of carrying a favorable prognosis with multiple treatment options, including breast-conserving surgery (BCS) or mastectomy. Social media is increasingly used as a source of information a...

TF-BERT: Tensor-based fusion BERT for multimodal sentiment analysis.

Neural networks : the official journal of the International Neural Network Society
Multimodal Sentiment Analysis (MSA) has gained significant attention due to the limitations of unimodal sentiment recognition in complex real-world applications. Traditional approaches typically focus on using the Transformer for fusion. However, the...

Towards a latent space cartography of subjective experience in mental health.

Psychiatry and clinical neurosciences
AIMS: The way that individuals subjectively experience the world greatly influences their own mental well-being. However, it remains a considerable challenge to precisely characterize the breadth and depth of such experiences. One persistent problem ...

Machine learning reveals sex differences in distinguishing between conduct-disordered and neurotypical youth based on emotion processing dysfunction.

BMC psychiatry
BACKGROUND: Theoretical models of conduct disorder (CD) highlight that deficits in emotion recognition, learning, and regulation play a pivotal role in CD etiology. With CD being more prevalent in boys than girls, various theories aim to explain this...

Emotional stimulated speech-based assisted early diagnosis of depressive disorders using personality-enhanced deep learning.

Journal of affective disorders
BACKGROUND: Early diagnosis of depression is crucial, and speech-based early diagnosis of depression is promising, but insufficient data and lack of theoretical support make it difficult to be applied. Therefore, it is valuable to combine psychiatric...

Multi-branch convolutional neural network with cross-attention mechanism for emotion recognition.

Scientific reports
Research on emotion recognition is an interesting area because of its wide-ranging applications in education, marketing, and medical fields. This study proposes a multi-branch convolutional neural network model based on cross-attention mechanism (MCN...