# TittaLSL: A toolbox for creating networked eye-tracking experiments in Python and MATLAB with Tobii eye trackers

## TL;DR

TittaLSL is a new toolbox that makes it easy to run networked eye-tracking experiments with Tobii eye trackers across multiple participants.

## Contribution

TittaLSL introduces a minimal-effort solution for streaming gaze data across multiple eye-tracking setups with low latency.

## Key findings

- TittaLSL achieved an end-to-end latency of 3.05 ms across 15 eye-tracking stations.
- The latency was only 0.10 ms higher than using a locally connected eye tracker.
- The toolbox is suitable for real-time networked eye-tracking experiments.

## Abstract

Studying the behavior of multiple participants using networked eye-tracking setups is of increasing interest to researchers. However, to conduct such studies, researchers have had to create complicated ad hoc solutions for streaming gaze over a local network. Here we present TittaLSL, a toolbox that enables creating networked multi-participant experiments using Tobii eye trackers with minimal programming effort. An evaluation using 600-Hz gaze streams sent between 15 different eye-tracking stations revealed that the end-to-end latency, including the eye tracker’s gaze estimation processes, achieved by TittaLSL was 3.05 ms. This was only 0.10 ms longer than when gaze samples were received from a locally connected eye tracker. We think that these latencies are low enough that TittaLSL is suitable for the majority of networked eye-tracking experiments, even when the gaze needs to be shown in real time.