AIMC Topic: Emotions

Clear Filters Showing 761 to 770 of 895 articles

The development of the Athens Emotional States Inventory (AESI): collection, validation and automatic processing of emotionally loaded sentences.

The world journal of biological psychiatry : the official journal of the World Federation of Societies of Biological Psychiatry
OBJECTIVES: The development of ecologically valid procedures for collecting reliable and unbiased emotional data towards computer interfaces with social and affective intelligence targeting patients with mental disorders.

Learning Multiscale Active Facial Patches for Expression Analysis.

IEEE transactions on cybernetics
In this paper, we present a new idea to analyze facial expression by exploring some common and specific information among different expressions. Inspired by the observation that only a few facial parts are active in expression disclosure (e.g., aroun...

Humanoid robotics in health care: An exploration of children's and parents' emotional reactions.

Journal of health psychology
A new non-pharmacological method of distraction was tested with 57 children during their annual flu vaccination. Given children's growing enthusiasm for technological devices, a humanoid robot was programmed to interact with them while a nurse admini...

Cyberdelics: Virtual reality hallucinations modulate cognitive-affective processes.

Dialogues in clinical neuroscience
INTRODUCTION: Psychedelics were explored for their potential in the mental health field. However, research was delayed by concerns over short-term side effects and long-term consequences of substance use. Technological advances enabled the developmen...

Investigating the Independent and Combined Effects of Startle and Surprise in a Simulated Flight Task.

Human factors
ObjectiveWe aimed to characterize the impact of startle and surprise, both independently and in combination, on subjective feelings, behavior (task performance and gaze behavior), and several physiological parameters.BackgroundThe effects of startle ...

Hierarchical Dynamic Graph Convolutional Network With Interpretability for EEG-Based Emotion Recognition.

IEEE transactions on neural networks and learning systems
Graph convolutional networks (GCNs) have shown great prowess in learning topological relationships among electroencephalogram (EEG) channels for EEG-based emotion recognition. However, most existing GCN-only methods are designed with a single spatial...

HBUED: An EEG dataset for emotion recognition.

Journal of affective disorders
Emotion recognition via electroencephalogram (EEG) data is crucial for improving human-computer interaction. In practice, researchers require a substantial quantity of EEG samples to train and validate models. However, existing EEG datasets typically...

When Machines Decide: Exploring How Trust in AI Shapes the Relationship Between Clinical Decision Support Systems and Nurses' Decision Regret: A Cross-Sectional Study.

Nursing in critical care
BACKGROUND: Artificial intelligence (AI)-based Clinical Decision Support Systems (AI-CDSS) are increasingly implemented in intensive care settings to support nurses in complex, time-sensitive decisions, aiming to improve accuracy, efficiency and pati...

Artificial intelligence-assisted visual elicitation in anorexia nervosa : Qualitative case studies.

Neuropsychiatrie : Klinik, Diagnostik, Therapie und Rehabilitation : Organ der Gesellschaft Osterreichischer Nervenarzte und Psychiater
PURPOSE: This study explored the feasibility and therapeutic potential of combining artificial intelligence (AI)-assisted visual elicitation with sensory-attuned guided reflection to support emotional expression and engagement in individuals with ano...