Abstract
The rapid acceleration of global aging demographics has elevated the integration of smart technologies to enhance the elderly’s quality of life to a critical societal priority. While existing social robots demonstrate significant potential in health monitoring and emotional companionship, their practical implementation faces substantial barriers, including steep learning curves, limited emotional responsiveness, and insufficient adaptability to heterogeneous geriatric needs. To address these challenges, this study conducts a comprehensive analysis of multimodal interaction modalities (visual, auditory, affective, tactile, electromyographic, and brain-computer interfaces) specifically tailored for older adults through literature synthesis and empirical user surveys. The results of the research and analysis indicate that the application of multimodal interaction is conducive to enhancing the naturalness of human-computer interaction and fostering an emotional connection between elderly users and robots, thereby helping to increase their acceptance and promote continued use. Based on the research results, the study proposes a five-layer architecture of a multimodal interaction system for social robots for elderly care, supplemented by aging-friendly design and information security, which provides theoretical support and practical reference for product innovation, experience optimization, and industry promotion of social robots for seniors. As AI, deep learning, and sensor technologies advance, multimodal interaction will assume greater significance in elderly healthcare, domestic services, and emotional support domains, contributing to the realization of intelligent, inclusive, and sustainable aging societies.
Keywords
Multimodal human-robot interaction; Social robots; Elderly users; Aging-friendly design; Emotional support; System architecture
DOI
https://doi.org/10.21606/iasdr.2025.277
Citation
Zhang, Y., Liu, Y.,and Xiao, L.(2025) The Utilization of Multimodal Interaction in Social Robots for Elderly Care: Interaction types, System Architecture, and Purchasing Motivation., IASDR 2025: Design Next, 02-05 December, Taipei, Taiwan. https://doi.org/10.21606/iasdr.2025.277
Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License
Conference Track
Track 9 - Healthcare Design
The Utilization of Multimodal Interaction in Social Robots for Elderly Care: Interaction types, System Architecture, and Purchasing Motivation
The rapid acceleration of global aging demographics has elevated the integration of smart technologies to enhance the elderly’s quality of life to a critical societal priority. While existing social robots demonstrate significant potential in health monitoring and emotional companionship, their practical implementation faces substantial barriers, including steep learning curves, limited emotional responsiveness, and insufficient adaptability to heterogeneous geriatric needs. To address these challenges, this study conducts a comprehensive analysis of multimodal interaction modalities (visual, auditory, affective, tactile, electromyographic, and brain-computer interfaces) specifically tailored for older adults through literature synthesis and empirical user surveys. The results of the research and analysis indicate that the application of multimodal interaction is conducive to enhancing the naturalness of human-computer interaction and fostering an emotional connection between elderly users and robots, thereby helping to increase their acceptance and promote continued use. Based on the research results, the study proposes a five-layer architecture of a multimodal interaction system for social robots for elderly care, supplemented by aging-friendly design and information security, which provides theoretical support and practical reference for product innovation, experience optimization, and industry promotion of social robots for seniors. As AI, deep learning, and sensor technologies advance, multimodal interaction will assume greater significance in elderly healthcare, domestic services, and emotional support domains, contributing to the realization of intelligent, inclusive, and sustainable aging societies.