@inproceedings{vandenitte-etal-2026-towards,
title = "Towards Integrating Pose Estimation with Neuroimaging for the Analysis of Signed Language Video Stimuli",
author = {Vandenitte, S{\'e}bastien and
Hern{\'a}ndez, Doris and
Ker{\"a}nen, Jarkko and
Jantunen, Tommi and
Puupponen, Anna},
editor = "Efthimiou, Eleni and
Fotinea, Stavroula-Evita and
Hanke, Thomas and
Hochgesang, Julie A. and
Mesch, Johanna and
Schulder, Marc",
booktitle = "Proceedings of the {LREC} 2026 12th Workshop on the Representation and Processing of Sign Languages: Language in Motion",
month = may,
year = "2026",
address = "Palma, Mallorca (Spain)",
publisher = "ELRA Language Resources Association (ELRA)",
url = "https://aclanthology.org/2026.signlang-1.49/",
doi = "10.63317/2q3vp6hdx56b",
pages = "477--483",
abstract = "We present our project revisiting the video stimuli of an EEG study in Finnish Sign Language to ask whether kinematic properties of the videos impacted their processing by study participants. For each stimulus, an average measure of brain responses across participants is computed. To analyse movement properties in the video stimuli, we rely on MediaPipe for pose estimation. We subsequently report on our project to perform an exploratory analysis of the kinematic properties of the videos which may affect their processing. We focus on several landmarks: the signer{'}s right and left wrists, nose, and upper torso. Our goal is to obtain a kinematic profile of each stimulus video using several average kinematic variables: velocity and acceleration for all selected landmarks, distance between the wrists, and surface covered by the triangular area defined by the left hand, the right hand, and the nose. We conclude by discussing the potential benefits and limitations of this methodological approach."
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<abstract>We present our project revisiting the video stimuli of an EEG study in Finnish Sign Language to ask whether kinematic properties of the videos impacted their processing by study participants. For each stimulus, an average measure of brain responses across participants is computed. To analyse movement properties in the video stimuli, we rely on MediaPipe for pose estimation. We subsequently report on our project to perform an exploratory analysis of the kinematic properties of the videos which may affect their processing. We focus on several landmarks: the signer’s right and left wrists, nose, and upper torso. Our goal is to obtain a kinematic profile of each stimulus video using several average kinematic variables: velocity and acceleration for all selected landmarks, distance between the wrists, and surface covered by the triangular area defined by the left hand, the right hand, and the nose. We conclude by discussing the potential benefits and limitations of this methodological approach.</abstract>
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%0 Conference Proceedings
%T Towards Integrating Pose Estimation with Neuroimaging for the Analysis of Signed Language Video Stimuli
%A Vandenitte, Sébastien
%A Hernández, Doris
%A Keränen, Jarkko
%A Jantunen, Tommi
%A Puupponen, Anna
%Y Efthimiou, Eleni
%Y Fotinea, Stavroula-Evita
%Y Hanke, Thomas
%Y Hochgesang, Julie A.
%Y Mesch, Johanna
%Y Schulder, Marc
%S Proceedings of the LREC 2026 12th Workshop on the Representation and Processing of Sign Languages: Language in Motion
%D 2026
%8 May
%I ELRA Language Resources Association (ELRA)
%C Palma, Mallorca (Spain)
%F vandenitte-etal-2026-towards
%X We present our project revisiting the video stimuli of an EEG study in Finnish Sign Language to ask whether kinematic properties of the videos impacted their processing by study participants. For each stimulus, an average measure of brain responses across participants is computed. To analyse movement properties in the video stimuli, we rely on MediaPipe for pose estimation. We subsequently report on our project to perform an exploratory analysis of the kinematic properties of the videos which may affect their processing. We focus on several landmarks: the signer’s right and left wrists, nose, and upper torso. Our goal is to obtain a kinematic profile of each stimulus video using several average kinematic variables: velocity and acceleration for all selected landmarks, distance between the wrists, and surface covered by the triangular area defined by the left hand, the right hand, and the nose. We conclude by discussing the potential benefits and limitations of this methodological approach.
%R 10.63317/2q3vp6hdx56b
%U https://aclanthology.org/2026.signlang-1.49/
%U https://doi.org/10.63317/2q3vp6hdx56b
%P 477-483
Markdown (Informal)
[Towards Integrating Pose Estimation with Neuroimaging for the Analysis of Signed Language Video Stimuli](https://aclanthology.org/2026.signlang-1.49/) (Vandenitte et al., SignLang 2026)
ACL