Focal Interest
Focal Interest

Emotion and Mood Recognition

External reference: https://openalex.org/T10667

  1. Facial-video heart rate variability modestly distinguished depressive symptoms
    Stacking ensemble classifier combines facial video-derived heart rate variability with demographics to screen depression with moderate discrimination. AUROC 0.64 achieved across 1453 individuals.
  2. Data augmented hybrid GCN transformer for student engagement recognition in E-learning
    Hybrid framework combining graph networks and transformers with synthetic data augmentation for automatic student engagement recognition from facial video in e-learning systems.
  3. A transdiagnostic conflict-square algorithm: a four-node computational framework for psychotherapy and functional diagnosis
    Computational framework for real-time psychotherapy decisions. Operationalizes defense, anxiety tolerance, progression, and shame signals with safety thresholds and auditable documentation.
  4. Adaptive music generation improved emotional matching
    Emotion-Conditioned Deep Reinforcement Learning framework for adaptive music generation. Achieves 98% emotion mapping accuracy with 280ms real-time responsiveness, enabling dynamic musical.
  5. ESR-Coach: Leveraging Large Language Models for Training People to Provide Emotionally Supportive Responses
    LLM-based coaching system for training emotionally supportive communication through AI-generated scenarios, exemplary responses, and assessment feedback.