Context
Naturalistic videos better reflect everyday emotion than isolated images, but introduce variable duration, blended affect, and timing challenges across devices.
Naturalistic · Multimodal
From naturalistic video to a synchronized multimodal emotion study
A research pipeline spanning video curation, condition assignment, pseudo-random evaluation, and synchronized event markers across devices.
01
Safe visual placeholder: replace with a de-identified process diagram, anonymized chart, or experiment UI without participant data.
Core question
How can rich naturalistic stimuli remain analyzable across presentation, evaluation, EEG, eye tracking, and peripheral physiology?
My role
Project lead. Detailed responsibilities, independently led work, and collaboration boundaries are to be confirmed.
Approach
Rule-based timing alignment, constrained pseudo-random evaluations tied to the preceding video, and centralized event markers for later synchronization.
Process
Deduplicate and transcode → build condition files → assign sessions and runs → program timing → add ratings → plan device synchronization.
Challenge & response
Variable video length and logically constrained ratings required explicit padding rules and constrained randomization. Device latency still requires lab validation.
Current output
To be confirmed. Sample details, statistics, and decoding performance remain private pending confirmation.
Reflection
A robust experiment depends on alignment between materials, timing, event codes, and documentation—not merely on software that runs.
Related materials
To add after author and collaborator confirmation: de-identified diagrams, anonymized charts, safe UI screenshots, and approved public outputs.