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

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Názov: TittaLSL: A toolbox for creating networked eye-tracking experiments in Python and MATLAB with Tobii eye trackers
Autori: Niehorster, Diederick C., Nyström, Marcus
Prispievatelia: Lund University, Joint Faculties of Humanities and Theology, Units, Lund University Humanities Lab, Lunds universitet, Humanistiska och teologiska fakulteterna, Fakultetsgemensamma verksamheter, Humanistlaboratoriet, Originator, Lund University, Profile areas and other strong research environments, Lund University Profile areas, LU Profile Area: Natural and Artificial Cognition, Lunds universitet, Profilområden och andra starka forskningsmiljöer, Lunds universitets profilområden, LU profilområde: Naturlig och artificiell kognition, Originator, Lund University, Faculty of Social Sciences, Departments of Administrative, Economic and Social Sciences, Department of Psychology, Lunds universitet, Samhällsvetenskapliga fakulteten, Samhällsvetenskapliga institutioner och centrumbildningar, Institutionen för psykologi, Originator
Zdroj: Behavior Research Methods. 57(7)
Predmety: Natural Sciences, Computer and Information Sciences, Human Computer Interaction, Naturvetenskap, Data- och informationsvetenskap (Datateknik), Människa-datorinteraktion (Interaktionsdesign), Social Sciences, Other Social Sciences, Other Social Sciences not elsewhere specified, Samhällsvetenskap, Annan samhällsvetenskap, Övrig annan samhällsvetenskap
Popis: 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.
Prístupová URL adresa: https://doi.org/10.3758/s13428-025-02714-2
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  Data: TittaLSL: A toolbox for creating networked eye-tracking experiments in Python and MATLAB with Tobii eye trackers
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  Data: 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.
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