Exploration of Foundation Model-Based Robots in Patient and Elderly Care
Zhiwen Qiu, Wei Liu, Yuexing Hao
Why It Matters
What makes this one worth your time
Understanding the limitations and potential of foundation model-based robots in healthcare is crucial for developing effective and reliable care technologies as populations age.
This paper evaluates the integration of foundation models in care robots and their clinical implications.
Summary
The paper synthesizes the current state of foundation model-based robots in patient and elderly care, discussing design features, user experience, and evidence for care-related outcomes while highlighting the limitations of existing systems.
Key contributions
- Synthesis of existing literature on foundation model-based care robots.
- Identification of key design features and user experience factors.
- Call for care-specific evaluation standards and integration into workflows.
Notable insights
- Current systems primarily utilize foundation models for conversational interfaces, but their physical autonomy and multimodal capabilities are underdeveloped.
- Empirical evaluations show positive user engagement, yet significant reliability issues like hallucinations remain unaddressed.
Possible limitations
- Limited evidence for validated clinical or care-related outcomes.
- Reliability failures in interaction pipelines are noted but not deeply explored.
Abstract
arXiv:2606.10208v1 Announce Type: cross Abstract: Demand for older-adult and patient care is growing rapidly as populations age worldwide. Foundation models are increasingly being integrated into robots and interactive agents, with the promise of more flexible communication and personalized assistance. However, care settings require reliable and workflow-compatible systems with accountable human oversight, and it remains unclear whether current embodied systems can translate technical advances into clinical impact. This Perspective synthesizes foundation model-based care robots across three areas: design features, user experience, and evidence for care-related outcomes. Current systems most commonly use foundation models as conversational and reasoning layers within voice-centered socially assistive embodiments, while multimodal grounding and physical autonomy remain limited. Empirical evaluations report positive usability and engagement benefits, but reliability failures persist across the interaction pipeline such as hallucinations and conversational breakdowns. Evidence for care impact remains concentrated in proximal outcomes such as cognitive engagement and participation, with limited evidence for validated clinical or care-related changes. We argue that future research should transition toward care-specific evaluation standards, accountable autonomy, and integration into care workflows to support more responsive and responsible care technologies.