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

Niehorster, Diederick C. LU orcid and Nyström, Marcus LU orcid (2025) In Behavior Research Methods 57(7).
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... (More)
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. (Less)
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organization
publishing date
type
Contribution to journal
publication status
published
subject
keywords
Eye tracking, Tobii, Toolbox, Multiple participants, Joint attention, Hyperscanning, Lab streaming layer
in
Behavior Research Methods
volume
57
issue
7
article number
190
pages
8 pages
publisher
Springer
ISSN
1554-3528
DOI
10.3758/s13428-025-02714-2
language
English
LU publication?
yes
id
46f2a697-62cb-4e55-a32b-e3fac1f98e32
date added to LUP
2025-06-04 20:46:29
date last changed
2025-06-17 09:25:12
@article{46f2a697-62cb-4e55-a32b-e3fac1f98e32,
  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.}},
  author       = {{Niehorster, Diederick C. and Nyström, Marcus}},
  issn         = {{1554-3528}},
  keywords     = {{Eye tracking; Tobii; Toolbox; Multiple participants; Joint attention; Hyperscanning; Lab streaming layer}},
  language     = {{eng}},
  number       = {{7}},
  publisher    = {{Springer}},
  series       = {{Behavior Research Methods}},
  title        = {{TittaLSL : A toolbox for creating networked eye-tracking experiments in Python and MATLAB with Tobii eye trackers}},
  url          = {{http://dx.doi.org/10.3758/s13428-025-02714-2}},
  doi          = {{10.3758/s13428-025-02714-2}},
  volume       = {{57}},
  year         = {{2025}},
}