VIVA Stimuli: A Web-Based Platform for Eye Tracking Stimuli

2026-04-21

AI Summary

This study addresses the persistent challenges in eye-tracking research—namely, poor reproducibility due to inconsistent stimulus presentation and reliance on specialized hardware or programming expertise. To overcome these limitations, the authors propose a web-based platform that standardizes stimulus delivery through an integrated visual experiment builder. The system supports multimodal eye-tracking devices, including video-oculography (VOG), light-field imaging (LFI), and electrooculography (EOG), and achieves high-precision temporal synchronization via ArUco markers and WebSocket communication. This platform represents the first implementation of a programming-free, cross-device-compatible experimental environment for eye-tracking studies, substantially enhancing reproducibility and facilitating efficient cross-laboratory collaboration.

Technology Category

• Computer Vision: Motion & Tracking
• Humans and AI: Interaction Techniques and Devices
• Intelligent Robots: Multimodal Perception & Sensor Fusion

Application Category

• Systems and Infrastructure for Web, Mobile and WoT: Experiences and lessons learnt from Web-based algorithms and system deployments
• Economics, Online Markets and Human Computation: Sustainability of Web economics
• Responsible Web: Human-perceived consequences of algorithmic deployment on the web

Abstract

Reproducibility in eye-tracking research is increasingly important as researchers conduct diverse experiments and seek to validate or replicate findings. However, exact replication remains challenging due to differences in laboratory practices and experimental setups. Inconsistent stimulus presentation can yield divergent metrics from identical oculomotor behavior, yet the stimulus layer remains largely unstandardized. Existing tools often require programming expertise or depend on specific hardware vendors. We introduce VIVA Stimuli, a web-based platform for standardized eye-tracking stimulus presentation. It provides configurable task types, including fixation, smooth pursuit, cognitive load, blink, slippage, content display, and questionnaires within a unified environment. The platform supports any eye-tracking technology, including wearable and screen-based VOG trackers, LFI sensors, and EOG devices. ArUco markers enable synchronization for trackers with scene cameras, while a WebSocket architecture ensures temporal synchronization for those without. A visual experiment flow editor allows protocols to be exported and shared, enabling identical stimulus replication across laboratories.

Problem

• eye-tracking
• reproducibility
• stimulus standardization
• experimental replication
• oculomotor behavior

Innovation

• eye-tracking
• stimulus standardization
• web-based platform
• temporal synchronization
• reproducibility