Abstract
In the field of robotics, caregiving robots and personal assistants are assuming an increasingly prominent role, directly impacting human lives. Especially in healthcare domains, these systems are starting to provide continuous 24/7 care by monitoring patients and delivering real-time insights into their activities. The effective deployment of future robots relies on equipping them with sophisticated Human Activity Recognition (HAR) algorithms. Many HAR algorithms are based on Artificial Intelligence (AI) and Machine Learning (ML) models. The development of these models necessitates suitable datasets. This paper introduces a Privacy-preserving Multimodal dataset for HAR in the context of Human-Robot Interaction (HRI) for Care robots (PriMA-Care). Tailored for care robots, PriMA-Care includes 27 diverse user activities, spanning daily tasks to physical HRI, with data from 10 privacy-preserving sensors and 17 participants. PriMA-Care addresses critical gaps in existing datasets, offering a suitable resource for HAR research in care robots.