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The use of robots in elderly care represents a dynamic field of study aimed at meeting the growing demand for home-based health care services. This article examines the application of robots in elderly home care and contributes to the literature by introducing a comprehensive and functional architecture within the realm of theInternet of Robotic Things (IoRT). This architecture amalgamates robots, sensors, and Artificial Intelligence (AI) to monitor the health status of the elderly. This study presented a four-actor system comprising a stationary humanoid robot, elderly individuals, medical personnel, and caregivers. This system enables continuous monitoring of the physical and emotional well-being of the elderly through specific sensors that measure vital signs, with real-time updates relayed to physicians and assistants, thereby ensuring timely and appropriate care. Our research endeavors to develop a fully integrated architecture that seamlessly integrates robots, sensors, and AI, enabling comprehensive care for elderly individuals in the comfort of their homes, thus reducing their reliance on institutional hospitalization. In particular, the methodology used was based on a user-centered approach involving geriatricians from the outset. This has been of fundamental importance in assessing their receptivity to the adoption of an intelligent information system, and above all, in understanding the issues most relevant to the elderly. The humanoid robot is specifically designed for close interaction with the elderly, capturing vital signs, emotional states, and cognitive conditions while providing assistance in daily routines and alerting family members and physicians to anomalies. Furthermore, communication was facilitated through an external Telegram bot. To predict the health status of the elderly, a machine learning model based on the Modified Early Warning Score (MEWS), a medical scoring scale, was developed. Five key lessons emerged from the study, showing how the system presented can provide valuable support to physicians, caregivers, and older people. Full article

In this study, we implemented a four-stage service design process to analyze the home-based interaction behavior between elderly and other family members to identify hidden needs for strengthening inter-generational relationships and creating harmony as a turning point for new product innovations in home-based interactive devices. In the demand exploration stage and demand definition stage, context inquiry and service modeling were applied to understand the intergenerational relationship between the elderly and other family members and the potential needs and expectations of family interactions. The overall demand mainly includes four points: (1) the improvement in inter-generational relationships requires the active care of family members, (2) the improvement in inter-generational emotional interactions requires accurate mastery of parental responsibilities, (3) the chairing design of the living room can be used to understand and document parental life practice, and (4) big data parental lifestyle records can be analyzed. Based on hidden demands, a smart care interactive system (SCIS) with a chair was designed for improving emotional interactions and parent-child interaction between the elderly and other family members. The results of the verification experiment show that the smart care interactive chair (SCIC) can significantly help the elderly with intergenerational relationships in terms of emotional support and parent-child interactions. The family emotional support and parent-child interactions are the foundation of the sustainability of family relationships and the cornerstone of social stability. Full article