duet: An R package for dyadic analysis of motion data generated by OpenPose

Research into dyadic social interactions has expanded significantly, enabling a deeper understanding of the dynamic processes underlying interpersonal communication. As the use of larger datasets becomes increasingly common in this field, the need for scalable and efficient analytical tools has grown. Automated coding methods, such as those provided by OpenPose, an open-source software for detecting and tracking human motion, offer significant advantages for analysing the movement of two individuals during an interaction. However, the processing and analysis of large quantities of JSON output files generated by OpenPose remain a considerable challenge. To address this, we introduce duet, an R package designed to streamline the processing and analysis of OpenPose output data, particularly in the context of dyadic interactions. The package provides a suite of functions for data cleaning, interpolation, kinematic analysis, and visualisation, offering researchers a comprehensive and user-friendly workflow. By simplifying the handling of OpenPose data, duet aims to facilitate large-scale, automated analysis of dyadic social interactions, with minimal coding experience, thereby advancing methodological capabilities in social and behavioural sciences.

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Publication Details

Journal
Behavior Research Methods
Published
2025-09-24
DOI
https://doi.org/10.3758/s13428-025-02817-w
Primary Topic
Human Pose and Action Recognition
Type
article
Field-Weighted Citation Impact
0.00

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article

duet: An R package for dyadic analysis of motion data generated by OpenPose

Catherine J Crompton, Themis Nikolas Efthimiou
Behavior Research Methods
Human Pose and Action Recognition
article

duet: An R package for dyadic analysis of motion data generated by OpenPose

Catherine J Crompton, Themis Nikolas Efthimiou
article en

Abstract

Research into dyadic social interactions has expanded significantly, enabling a deeper understanding of the dynamic processes underlying interpersonal communication. As the use of larger datasets becomes increasingly common in this field, the need for scalable and efficient analytical tools has grown. Automated coding methods, such as those provided by OpenPose, an open-source software for detecting and tracking human motion, offer significant advantages for analysing the movement of two individuals during an interaction. However, the processing and analysis of large quantities of JSON output files generated by OpenPose remain a considerable challenge. To address this, we introduce duet, an R package designed to streamline the processing and analysis of OpenPose output data, particularly in the context of dyadic interactions. The package provides a suite of functions for data cleaning, interpolation, kinematic analysis, and visualisation, offering researchers a comprehensive and user-friendly workflow. By simplifying the handling of OpenPose data, duet aims to facilitate large-scale, automated analysis of dyadic social interactions, with minimal coding experience, thereby advancing methodological capabilities in social and behavioural sciences.

Behavior Research MethodsVol. 57(11)
University of Edinburgh (GB)
John Templeton Foundation, Templeton World Charity Foundation
Openalex Percentile: Top 74%
Human Pose and Action Recognition
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