TittaLSL : A toolbox for creating networked eye-tracking experiments in Python and MATLAB with Tobii eye trackers
(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)
Please use this url to cite or link to this publication:
https://lup.lub.lu.se/record/46f2a697-62cb-4e55-a32b-e3fac1f98e32
- author
- Niehorster, Diederick C.
LU
and Nyström, Marcus LU
- organization
- publishing date
- 2025
- 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}}, }