RADHOME:Radar based Human Activity Dataset in Home Environments
Description
With the rapid advancements in smart home technologies, health monitoring, and safety management systems, there is a growing demand for improving quality of life and ensuring security. In this study, we present a dataset of daily human activities constructed using millimeter-wave (mmWave) radar technology, aimed at providing a robust foundation for non-contact health monitoring, safety management, and smart home systems. The dataset involves 10 participants of diverse genders and body types, performing six activity transitions in a specified sequence: sitting to walking, sitting to stretching, walking to picking up, sitting to drinking water, walking to falling, and falling to waving for help. Each activity was repeated 20 times, resulting in 1,200 activity samples. The radar system was positioned at a height of 0.8–1 meters, with a detection range of 2–5 meters, ensuring precise capture of participants' indoor movements. This dataset is made publicly available with comprehensive documentation to facilitate reproducibility and usability. It offers a valuable resource for developing advanced human activity recognition algorithms and contributes to research on behavioral patterns, with applications in smart home systems, health monitoring, and safety management.