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| Funder | National Science Foundation (US) |
|---|---|
| Recipient Organization | University of California-Santa Barbara |
| Country | United States |
| Start Date | May 15, 2025 |
| End Date | Oct 31, 2025 |
| Duration | 169 days |
| Number of Grantees | 1 |
| Roles | Principal Investigator |
| Data Source | National Science Foundation (US) |
| Grant ID | 2516386 |
This I-Corps project is based on the development of an interactive social robot, called a socialbot, that interacts and communicates with older adults facing cognitive decline. Currently, family caregivers lack structured, easy-to-use tools that prompt meaningful memory-sharing activities and enhance emotional well-being. This technology is designed to record, retrieve, and discuss personal memories to improve the quality of interactions.
This digital platform technology provides caregivers with the ability to engage emotionally with older adults, stimulate memory recall, and ease caregiving challenges. In addition, this platform may offer a scalable and adaptable service to individual caregivers, senior living communities, and dementia care programs. The goal is to address dementia care needs, potentially delaying the need for institutional care, strengthening family relationships, and significantly improving the quality of life for older adults and their families.
This I-Corps project utilizes experiential learning coupled with a first-hand investigation of the industry ecosystem to assess the translation potential of a conversational socialbot technology for use in reminiscence therapy. Reminiscence therapy is a psychosocial intervention that stimulates long-term memory and emotional well-being among older adults.
It has demonstrated benefits in improving social engagement and life satisfaction by fostering reflection on personal experiences and memories. This technology incorporates advancements in proactive, multi-turn conversational artificial intelligence (AI), integrated with knowledge graph-driven management of personalized multimedia content (photos, audio, and videos).
Unlike traditional conversational systems limited by passive interactions and short-term memory, this technology leverages long-context AI models to dynamically retrieve and organize meaningful content, delivering personalized, sustained, and emotionally engaging conversations. Users benefit from improved social interaction, enhanced emotional well-being, and sustained cognitive engagement, highlighting a substantial advancement in AI-driven healthcare solutions.
The goal is to meet caregivers’ needs and support older adults’ emotional health and cognitive engagement.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
University of California-Santa Barbara
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