From Motion to Meaning: A Systematic Review of Motion Tracking in XR-based Experimental Psychology

Immersive technologies such as Virtual Reality (VR), Augmented Reality (AR), and Mixed Reality (MR) are being increasingly used in experimental psychology because they enable controlled environments while simultaneously producing high-frequency motiontracking data from headsets, controllers, and body trackers. These motion traces provide continuous behavioral signals that may reflect affective, behavioral, and cognitive processes during human-human, human-computer, and human-virtual human interactions. Despite the growing use of motion measures in XR (Extended Reality) experiments, there is limited synthesis of how such data are collected, transformed, analyzed, and interpreted. This paper presents a systematic literature review of studies collected from the ACM Digital Library, IEEE Xplore, PsycINFO, PubMed, and Web of Science that use motion-tracking data from XR devices in experimental psychology, focusing on affect, behavior, cognition, or their intersections. The review examines the devices used, the body parts tracked, and the data formats employed in these studies. More importantly, it analyzes how raw motion-tracking data streams are transformed into kinematic or trajectory-level features and the analytical methods used to link them to psychological constructs. Our findings highlight substantial variability in device configurations and motion data extraction methods, but we observe a common pattern of using descriptive statistical measures to summarize motion patterns or applying machine learning models to learn from processed motion features. Based on these observations, we outline practical recommendations for selecting tracking setups, collecting and validating motion data, and designing analysis pipelines in experimental psychological studies. This review aims to support researchers seeking to incorporate motion-tracking data into XR-based psychological experiments and to promote more consistent and interpretable use of motion measures in immersive research.