Accurately capturing, measuring, and analyzing human affective states remains a critical challenge across neuroscience, behavioral psychology, human-computer interaction (HCI), and medical diagnostics. While traditional research has relied heavily on subjective, post hoc self-reporting, modern methodologies leverage multimodal, objective data streams to quantify emotional valence and arousal in real time.

This collection highlights visualizable, reproducible protocols that advance how emotional responses are observed and interpreted. By bridging advanced computational tools with rigorous experimental design, this collection aims to standardize data collection and enhance reproducibility in affective science.

Key Areas of Focus

We welcome video protocol submissions demonstrating standard and emerging techniques, including:

• Physiological and Neuroimaging Methods: High-resolution setups for electroencephalography (EEG), functional near-infrared spectroscopy (fNIRS), galvanic skin response (GSR), and photoplethysmography (PPG).
• Behavioral and Computational Analysis: Computer vision protocols for facial action coding systems (FACS), micro-expression detection, automated vocal acoustic analysis, and eye-tracking/pupillometry paradigms.
• Multimodal Integration: Frameworks and synchronization techniques for merging simultaneous central and peripheral nervous system data streams.
• Applied Environments: Experimental paradigms testing emotion estimation in naturalistic environments, clinical diagnostics, virtual reality (VR), and adaptive AI user testing.

By visualizing these intricate hardware configurations and software pipelines, this collection provides researchers with the concrete, step-by-step guidance needed to implement high-fidelity emotion estimation approaches in their own laboratories.