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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Objective To investigate the neural correlates of working memory during a spontaneous migraine attack compared to the interictal phase, using functional magnetic resonance imaging (fMRI). Background C...