A Review of Human Synchronization Datasets

Human synchronization refers to the coordination in time of individuals’ actions, movements, or physiological processes, often considered within a rhythmical context. This phenomenon can occur in various forms such as matching rhythmic movements, aligning speech patterns, or synchronizing biological rhythms. It plays a crucial role in social interactions, effective communication, sports, and musical performance. This work aims to reference accessible online datasets related to human synchronization, to increase their visibility and availability. Notably, it compiles 75 directly accessible datasets and 26 with indirect access to study synchronization in various contexts. It reviews all types of synchronization tasks and contexts found in the datasets. Results are clustered into four categories: discontinuous movement, continuous movement, social interactions, and musical performance. Then, this review explores the signals and acquisition methods used across human synchronization datasets, ranging from simple touchpads, and kinematic sensors, to expansive motion capture and hyperscanning technologies. This paper surveys objective measures of synchronization used in the gathered papers and reveals some heterogeneity in the quantification of synchronization. Furthermore, it points out a lack of annotated datasets, which limits the development of machine learning methods. By compiling accessible datasets, this review centralizes valuable experimental data, providing a foundation for more collaborative, comprehensive, and standardized approaches to studying human synchronization.