Abstract
Human action recognition and heart rate estimation for indoor human targets carry significant applications in many fields such as smart homes, health care, sports analysis, etc., and have attracted increasing attention in recent years. Impulse-Radio Ultra-Wideband (IR-UWB) radar, with its advantages in privacy protection, environmental requirements and performance, has found extensive applications in indoor human target monitoring. In view of the data demand for indoor human perception related research based on IR-UWB radar, and the issues with a lack of relevant public data and inadequacy in the authenticity of simulation data, this paper presents a dataset of human action recognition and heart rate estimation based on IR-UWB radar through typical indoor scene measurement experiments and data processing and annotation. The dataset collects 1,629 groups of action recognition data (i.e. unmanned scene data and 10 common actions such as walking, waving, squatting, etc.) from 10 human targets as well as 4,670 groups of heart rate estimation data. All data are presented in a standardized format with precise labeling, making it a valuable resource for research in relevant fields.
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