Emotional Daily Life Library (E-DLL): Validation of a database of 3D objects for emotion elicitation

Research on emotional perception often relies on 2D stimuli or highly affective images, limiting ecological validity. We introduce the Emotional Daily Life Library (E-DLL), a database of 132 rotating 3D everyday objects with comprehensive perceptual, cognitive, and emotional normative ratings. In 52 adults, participants provided dimensional (valence-arousal-dominance) and categorical emotion ratings, alongside assessments of recognition, naming, familiarity, contact, usage, and visual complexity. Personality traits (NEO-FFI) and depressive symptoms (BDI-II) were measured to examine individual differences. Cumulative Link Mixed Models (CLMMs) revealed that valence ratings were negatively influenced by the interaction of Neuroticism and subclinical depressive symptoms. For arousal, higher Neuroticism and Conscientiousness demonstrated marginal positive associations, while dominance ratings were unaffected. Generalized Linear Mixed Models (GLMMs) for categorical labels indicated that while emotional attributions were primarily driven by stimulus properties, traits such as Neuroticism and Extraversion significantly predicted the perception of negative emotions (e.g., Sadness). Spearman correlations identified interrelationships among cognitive and perceptual dimensions, and redundant variables (Contact and Usage) were combined into a composite Object Interaction score. By integrating neutral, immersive 3D stimuli with rich multidimensional annotations, E-DLL provides a controlled and ecologically valid tool for experimental and clinical research. Its applicability includes cognitive training, VR-based interventions, and personalized neurorehabilitation platforms such as NeuroAIreh@b, supporting investigations of affective biases and optimizing daily life-oriented therapeutic interventions.